Infrastructure sensing.

PubMed

Soga, Kenichi; Schooling, Jennifer

2016-08-06

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors.

Infrastructure sensing

PubMed Central

Soga, Kenichi; Schooling, Jennifer

2016-01-01

Design, construction, maintenance and upgrading of civil engineering infrastructure requires fresh thinking to minimize use of materials, energy and labour. This can only be achieved by understanding the performance of the infrastructure, both during its construction and throughout its design life, through innovative monitoring. Advances in sensor systems offer intriguing possibilities to radically alter methods of condition assessment and monitoring of infrastructure. In this paper, it is hypothesized that the future of infrastructure relies on smarter information; the rich information obtained from embedded sensors within infrastructure will act as a catalyst for new design, construction, operation and maintenance processes for integrated infrastructure systems linked directly with user behaviour patterns. Some examples of emerging sensor technologies for infrastructure sensing are given. They include distributed fibre-optics sensors, computer vision, wireless sensor networks, low-power micro-electromechanical systems, energy harvesting and citizens as sensors. PMID:27499845

Advances in Spatial Data Infrastructure, Acquisition, Analysis, Archiving and Dissemination

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuran K.; Rochon, Gilbert L.; Duerr, Ruth; Rank, Robert; Nativi, Stefano; Stocker, Erich Franz

2010-01-01

The authors review recent contributions to the state-of-thescience and benign proliferation of satellite remote sensing, spatial data infrastructure, near-real-time data acquisition, analysis on high performance computing platforms, sapient archiving, multi-modal dissemination and utilization for a wide array of scientific applications. The authors also address advances in Geoinformatics and its growing ubiquity, as evidenced by its inclusion as a focus area within the American Geophysical Union (AGU), European Geosciences Union (EGU), as well as by the evolution of the IEEE Geoscience and Remote Sensing Society's (GRSS) Data Archiving and Distribution Technical Committee (DAD TC).

Critical Infrastructure Protection II, The International Federation for Information Processing, Volume 290.

NASA Astrophysics Data System (ADS)

Papa, Mauricio; Shenoi, Sujeet

The information infrastructure -- comprising computers, embedded devices, networks and software systems -- is vital to day-to-day operations in every sector: information and telecommunications, banking and finance, energy, chemicals and hazardous materials, agriculture, food, water, public health, emergency services, transportation, postal and shipping, government and defense. Global business and industry, governments, indeed society itself, cannot function effectively if major components of the critical information infrastructure are degraded, disabled or destroyed. Critical Infrastructure Protection II describes original research results and innovative applications in the interdisciplinary field of critical infrastructure protection. Also, it highlights the importance of weaving science, technology and policy in crafting sophisticated, yet practical, solutions that will help secure information, computer and network assets in the various critical infrastructure sectors. Areas of coverage include: - Themes and Issues - Infrastructure Security - Control Systems Security - Security Strategies - Infrastructure Interdependencies - Infrastructure Modeling and Simulation This book is the second volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.10 on Critical Infrastructure Protection, an international community of scientists, engineers, practitioners and policy makers dedicated to advancing research, development and implementation efforts focused on infrastructure protection. The book contains a selection of twenty edited papers from the Second Annual IFIP WG 11.10 International Conference on Critical Infrastructure Protection held at George Mason University, Arlington, Virginia, USA in the spring of 2008.

2008 Defense Industrial Base Critical Infrastructure Protection Conference (DIB-CBIP)

DTIC Science & Technology

2008-04-09

a cloak -and- dagger thing. It’s about computer architecture and the soundness of electronic systems." Joel Brenner, ODNI Counterintelligence Office...to support advanced network exploitation and launch attacks on the informational and physical elements of our cyber infrastructure. In order to...entities and is vulnerable to attacks and manipulation. Operations in the cyber domain have the ability to impact operations in other war-fighting

Grid computing in large pharmaceutical molecular modeling.

PubMed

Claus, Brian L; Johnson, Stephen R

2008-07-01

Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.

Bioinformatics clouds for big data manipulation.

PubMed

Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang

2012-11-28

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

Infrastructure Systems for Advanced Computing in E-science applications

NASA Astrophysics Data System (ADS)

Terzo, Olivier

2013-04-01

In the e-science field are growing needs for having computing infrastructure more dynamic and customizable with a model of use "on demand" that follow the exact request in term of resources and storage capacities. The integration of grid and cloud infrastructure solutions allows us to offer services that can adapt the availability in terms of up scaling and downscaling resources. The main challenges for e-sciences domains will on implement infrastructure solutions for scientific computing that allow to adapt dynamically the demands of computing resources with a strong emphasis on optimizing the use of computing resources for reducing costs of investments. Instrumentation, data volumes, algorithms, analysis contribute to increase the complexity for applications who require high processing power and storage for a limited time and often exceeds the computational resources that equip the majority of laboratories, research Unit in an organization. Very often it is necessary to adapt or even tweak rethink tools, algorithms, and consolidate existing applications through a phase of reverse engineering in order to adapt them to a deployment on Cloud infrastructure. For example, in areas such as rainfall monitoring, meteorological analysis, Hydrometeorology, Climatology Bioinformatics Next Generation Sequencing, Computational Electromagnetic, Radio occultation, the complexity of the analysis raises several issues such as the processing time, the scheduling of tasks of processing, storage of results, a multi users environment. For these reasons, it is necessary to rethink the writing model of E-Science applications in order to be already adapted to exploit the potentiality of cloud computing services through the uses of IaaS, PaaS and SaaS layer. An other important focus is on create/use hybrid infrastructure typically a federation between Private and public cloud, in fact in this way when all resources owned by the organization are all used it will be easy with a federate cloud infrastructure to add some additional resources form the Public cloud for following the needs in term of computational and storage resources and release them where process are finished. Following the hybrid model, the scheduling approach is important for managing both cloud models. Thanks to this model infrastructure every time resources are available for additional request in term of IT capacities that can used "on demand" for a limited time without having to proceed to purchase additional servers.

Waggle: A Framework for Intelligent Attentive Sensing and Actuation

NASA Astrophysics Data System (ADS)

Sankaran, R.; Jacob, R. L.; Beckman, P. H.; Catlett, C. E.; Keahey, K.

2014-12-01

Advances in sensor-driven computation and computationally steered sensing will greatly enable future research in fields including environmental and atmospheric sciences. We will present "Waggle," an open-source hardware and software infrastructure developed with two goals: (1) reducing the separation and latency between sensing and computing and (2) improving the reliability and longevity of sensing-actuation platforms in challenging and costly deployments. Inspired by "deep-space probe" systems, the Waggle platform design includes features that can support longitudinal studies, deployments with varying communication links, and remote management capabilities. Waggle lowers the barrier for scientists to incorporate real-time data from their sensors into their computations and to manipulate the sensors or provide feedback through actuators. A standardized software and hardware design allows quick addition of new sensors/actuators and associated software in the nodes and enables them to be coupled with computational codes both insitu and on external compute infrastructure. The Waggle framework currently drives the deployment of two observational systems - a portable and self-sufficient weather platform for study of small-scale effects in Chicago's urban core and an open-ended distributed instrument in Chicago that aims to support several research pursuits across a broad range of disciplines including urban planning, microbiology and computer science. Built around open-source software, hardware, and Linux OS, the Waggle system comprises two components - the Waggle field-node and Waggle cloud-computing infrastructure. Waggle field-node affords a modular, scalable, fault-tolerant, secure, and extensible platform for hosting sensors and actuators in the field. It supports insitu computation and data storage, and integration with cloud-computing infrastructure. The Waggle cloud infrastructure is designed with the goal of scaling to several hundreds of thousands of Waggle nodes. It supports aggregating data from sensors hosted by the nodes, staging computation, relaying feedback to the nodes and serving data to end-users. We will discuss the Waggle design principles and their applicability to various observational research pursuits, and demonstrate its capabilities.

Open Component Portability Infrastructure (OPENCPI)

DTIC Science & Technology

2009-11-01

Disk Drive 7 1 www.antec.com P182 $120. ATX Mid Tower Computer Case 8 1 www.xilinx.com HW-V5-ML555-G $2200. Xilinx ML555 V5 Dev Kit Notes: Cost...s/ GEORGE RAMSEYER EDWARD J. JONES, Deputy Chief Work Unit Manager Advanced Computing ...uniquely positioned to meet the goals of the Software Systems Stockroom (S3) since in some sense component-based systems are computer -science’s

Towards Portable Large-Scale Image Processing with High-Performance Computing.

PubMed

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

Bioinformatics clouds for big data manipulation

PubMed Central

2012-01-01

Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. PMID:23190475

Computation Directorate Annual Report 2003

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crawford, D L; McGraw, J R; Ashby, S F

Big computers are icons: symbols of the culture, and of the larger computing infrastructure that exists at Lawrence Livermore. Through the collective effort of Laboratory personnel, they enable scientific discovery and engineering development on an unprecedented scale. For more than three decades, the Computation Directorate has supplied the big computers that enable the science necessary for Laboratory missions and programs. Livermore supercomputing is uniquely mission driven. The high-fidelity weapon simulation capabilities essential to the Stockpile Stewardship Program compel major advances in weapons codes and science, compute power, and computational infrastructure. Computation's activities align with this vital mission of the Departmentmore » of Energy. Increasingly, non-weapons Laboratory programs also rely on computer simulation. World-class achievements have been accomplished by LLNL specialists working in multi-disciplinary research and development teams. In these teams, Computation personnel employ a wide array of skills, from desktop support expertise, to complex applications development, to advanced research. Computation's skilled professionals make the Directorate the success that it has become. These individuals know the importance of the work they do and the many ways it contributes to Laboratory missions. They make appropriate and timely decisions that move the entire organization forward. They make Computation a leader in helping LLNL achieve its programmatic milestones. I dedicate this inaugural Annual Report to the people of Computation in recognition of their continuing contributions. I am proud that we perform our work securely and safely. Despite increased cyber attacks on our computing infrastructure from the Internet, advanced cyber security practices ensure that our computing environment remains secure. Through Integrated Safety Management (ISM) and diligent oversight, we address safety issues promptly and aggressively. The safety of our employees, whether at work or at home, is a paramount concern. Even as the Directorate meets today's supercomputing requirements, we are preparing for the future. We are investigating open-source cluster technology, the basis of our highly successful Mulitprogrammatic Capability Resource (MCR). Several breakthrough discoveries have resulted from MCR calculations coupled with theory and experiment, prompting Laboratory scientists to demand ever-greater capacity and capability. This demand is being met by a new 23-TF system, Thunder, with architecture modeled on MCR. In preparation for the ''after-next'' computer, we are researching technology even farther out on the horizon--cell-based computers. Assuming that the funding and the technology hold, we will acquire the cell-based machine BlueGene/L within the next 12 months.« less

Intelligent transportation systems, shared resource projects : an action guide : telecommunications infrastructure in transportation right-of-way

DOT National Transportation Integrated Search

1997-01-01

Intelligent transportation systems (ITS) use advances in communications, computer and information systems to create technologies that can improve traffic, transit and commercial vehicle operations. Essentially, ITS provides the right people in the tr...

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Modeling, Simulation and Analysis of Public Key Infrastructure

NASA Technical Reports Server (NTRS)

Liu, Yuan-Kwei; Tuey, Richard; Ma, Paul (Technical Monitor)

1998-01-01

Security is an essential part of network communication. The advances in cryptography have provided solutions to many of the network security requirements. Public Key Infrastructure (PKI) is the foundation of the cryptography applications. The main objective of this research is to design a model to simulate a reliable, scalable, manageable, and high-performance public key infrastructure. We build a model to simulate the NASA public key infrastructure by using SimProcess and MatLab Software. The simulation is from top level all the way down to the computation needed for encryption, decryption, digital signature, and secure web server. The application of secure web server could be utilized in wireless communications. The results of the simulation are analyzed and confirmed by using queueing theory.

Towards an advanced e-Infrastructure for Civil Protection applications: Research Strategies and Innovation Guidelines

NASA Astrophysics Data System (ADS)

Mazzetti, P.; Nativi, S.; Verlato, M.; Angelini, V.

2009-04-01

In the context of the EU co-funded project CYCLOPS (http://www.cyclops-project.eu) the problem of designing an advanced e-Infrastructure for Civil Protection (CP) applications has been addressed. As a preliminary step, some studies about European CP systems and operational applications were performed in order to define their specific system requirements. At a higher level it was verified that CP applications are usually conceived to map CP Business Processes involving different levels of processing including data access, data processing, and output visualization. At their core they usually run one or more Earth Science models for information extraction. The traditional approach based on the development of monolithic applications presents some limitations related to flexibility (e.g. the possibility of running the same models with different input data sources, or different models with the same data sources) and scalability (e.g. launching several runs for different scenarios, or implementing more accurate and computing-demanding models). Flexibility can be addressed adopting a modular design based on a SOA and standard services and models, such as OWS and ISO for geospatial services. Distributed computing and storage solutions could improve scalability. Basing on such considerations an architectural framework has been defined. It is made of a Web Service layer providing advanced services for CP applications (e.g. standard geospatial data sharing and processing services) working on the underlying Grid platform. This framework has been tested through the development of prototypes as proof-of-concept. These theoretical studies and proof-of-concept demonstrated that although Grid and geospatial technologies would be able to provide significant benefits to CP applications in terms of scalability and flexibility, current platforms are designed taking into account requirements different from CP. In particular CP applications have strict requirements in terms of: a) Real-Time capabilities, privileging time-of-response instead of accuracy, b) Security services to support complex data policies and trust relationships, c) Interoperability with existing or planned infrastructures (e.g. e-Government, INSPIRE compliant, etc.). Actually these requirements are the main reason why CP applications differ from Earth Science applications. Therefore further research is required to design and implement an advanced e-Infrastructure satisfying those specific requirements. In particular five themes where further research is required were identified: Grid Infrastructure Enhancement, Advanced Middleware for CP Applications, Security and Data Policies, CP Applications Enablement, and Interoperability. For each theme several research topics were proposed and detailed. They are targeted to solve specific problems for the implementation of an effective operational European e-Infrastructure for CP applications.

Grid computing technology for hydrological applications

NASA Astrophysics Data System (ADS)

Lecca, G.; Petitdidier, M.; Hluchy, L.; Ivanovic, M.; Kussul, N.; Ray, N.; Thieron, V.

2011-06-01

SummaryAdvances in e-Infrastructure promise to revolutionize sensing systems and the way in which data are collected and assimilated, and complex water systems are simulated and visualized. According to the EU Infrastructure 2010 work-programme, data and compute infrastructures and their underlying technologies, either oriented to tackle scientific challenges or complex problem solving in engineering, are expected to converge together into the so-called knowledge infrastructures, leading to a more effective research, education and innovation in the next decade and beyond. Grid technology is recognized as a fundamental component of e-Infrastructures. Nevertheless, this emerging paradigm highlights several topics, including data management, algorithm optimization, security, performance (speed, throughput, bandwidth, etc.), and scientific cooperation and collaboration issues that require further examination to fully exploit it and to better inform future research policies. The paper illustrates the results of six different surface and subsurface hydrology applications that have been deployed on the Grid. All the applications aim to answer to strong requirements from the Civil Society at large, relatively to natural and anthropogenic risks. Grid technology has been successfully tested to improve flood prediction, groundwater resources management and Black Sea hydrological survey, by providing large computing resources. It is also shown that Grid technology facilitates e-cooperation among partners by means of services for authentication and authorization, seamless access to distributed data sources, data protection and access right, and standardization.

Advanced propulsion for LEO-Moon transport. 3: Transportation model. M.S. Thesis - California Univ.

NASA Technical Reports Server (NTRS)

Henley, Mark W.

1992-01-01

A simplified computational model of low Earth orbit-Moon transportation system has been developed to provide insight into the benefits of new transportation technologies. A reference transportation infrastructure, based upon near-term technology developments, is used as a departure point for assessing other, more advanced alternatives. Comparison of the benefits of technology application, measured in terms of a mass payback ratio, suggests that several of the advanced technology alternatives could substantially improve the efficiency of low Earth orbit-Moon transportation.

Storing and using health data in a virtual private cloud.

PubMed

Regola, Nathan; Chawla, Nitesh V

2013-03-13

Electronic health records are being adopted at a rapid rate due to increased funding from the US federal government. Health data provide the opportunity to identify possible improvements in health care delivery by applying data mining and statistical methods to the data and will also enable a wide variety of new applications that will be meaningful to patients and medical professionals. Researchers are often granted access to health care data to assist in the data mining process, but HIPAA regulations mandate comprehensive safeguards to protect the data. Often universities (and presumably other research organizations) have an enterprise information technology infrastructure and a research infrastructure. Unfortunately, both of these infrastructures are generally not appropriate for sensitive research data such as HIPAA, as they require special accommodations on the part of the enterprise information technology (or increased security on the part of the research computing environment). Cloud computing, which is a concept that allows organizations to build complex infrastructures on leased resources, is rapidly evolving to the point that it is possible to build sophisticated network architectures with advanced security capabilities. We present a prototype infrastructure in Amazon's Virtual Private Cloud to allow researchers and practitioners to utilize the data in a HIPAA-compliant environment.

Leveraging e-Science infrastructure for electrochemical research.

PubMed

Peachey, Tom; Mashkina, Elena; Lee, Chong-Yong; Enticott, Colin; Abramson, David; Bond, Alan M; Elton, Darrell; Gavaghan, David J; Stevenson, Gareth P; Kennedy, Gareth F

2011-08-28

As in many scientific disciplines, modern chemistry involves a mix of experimentation and computer-supported theory. Historically, these skills have been provided by different groups, and range from traditional 'wet' laboratory science to advanced numerical simulation. Increasingly, progress is made by global collaborations, in which new theory may be developed in one part of the world and applied and tested in the laboratory elsewhere. e-Science, or cyber-infrastructure, underpins such collaborations by providing a unified platform for accessing scientific instruments, computers and data archives, and collaboration tools. In this paper we discuss the application of advanced e-Science software tools to electrochemistry research performed in three different laboratories--two at Monash University in Australia and one at the University of Oxford in the UK. We show that software tools that were originally developed for a range of application domains can be applied to electrochemical problems, in particular Fourier voltammetry. Moreover, we show that, by replacing ad-hoc manual processes with e-Science tools, we obtain more accurate solutions automatically.

@neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

PubMed

Benkner, Siegfried; Arbona, Antonio; Berti, Guntram; Chiarini, Alessandro; Dunlop, Robert; Engelbrecht, Gerhard; Frangi, Alejandro F; Friedrich, Christoph M; Hanser, Susanne; Hasselmeyer, Peer; Hose, Rod D; Iavindrasana, Jimison; Köhler, Martin; Iacono, Luigi Lo; Lonsdale, Guy; Meyer, Rodolphe; Moore, Bob; Rajasekaran, Hariharan; Summers, Paul E; Wöhrer, Alexander; Wood, Steven

2010-11-01

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy. PMID:29485990

INFN-Pisa scientific computation environment (GRID, HPC and Interactive Analysis)

NASA Astrophysics Data System (ADS)

Arezzini, S.; Carboni, A.; Caruso, G.; Ciampa, A.; Coscetti, S.; Mazzoni, E.; Piras, S.

2014-06-01

The INFN-Pisa Tier2 infrastructure is described, optimized not only for GRID CPU and Storage access, but also for a more interactive use of the resources in order to provide good solutions for the final data analysis step. The Data Center, equipped with about 6700 production cores, permits the use of modern analysis techniques realized via advanced statistical tools (like RooFit and RooStat) implemented in multicore systems. In particular a POSIX file storage access integrated with standard SRM access is provided. Therefore the unified storage infrastructure is described, based on GPFS and Xrootd, used both for SRM data repository and interactive POSIX access. Such a common infrastructure allows a transparent access to the Tier2 data to the users for their interactive analysis. The organization of a specialized many cores CPU facility devoted to interactive analysis is also described along with the login mechanism integrated with the INFN-AAI (National INFN Infrastructure) to extend the site access and use to a geographical distributed community. Such infrastructure is used also for a national computing facility in use to the INFN theoretical community, it enables a synergic use of computing and storage resources. Our Center initially developed for the HEP community is now growing and includes also HPC resources fully integrated. In recent years has been installed and managed a cluster facility (1000 cores, parallel use via InfiniBand connection) and we are now updating this facility that will provide resources for all the intermediate level HPC computing needs of the INFN theoretical national community.

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

Chaos Breeds Life: Finding Opportunities for Library Advancement during a Period of Collection Schizophrenia.

ERIC Educational Resources Information Center

Neal, James G.

1999-01-01

Examines the changes that are affecting academic library collection development. Highlights include computer technology; digital information; networking; virtual reality; hypertext; fair use and copyrights; technological infrastructure; digital libraries; information policy; academic and scholarly publishing; and experiences at the Johns Hopkins…

Collaborative Working Architecture for IoT-Based Applications.

PubMed

Mora, Higinio; Signes-Pont, María Teresa; Gil, David; Johnsson, Magnus

2018-05-23

The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.« less

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

DOE PAGES

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; ...

2015-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-end NGS analysis requirements. The Globus Genomicsmore » system is built on Amazon's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.« less

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

PubMed Central

Bhuvaneshwar, Krithika; Sulakhe, Dinanath; Gauba, Robinder; Rodriguez, Alex; Madduri, Ravi; Dave, Utpal; Lacinski, Lukasz; Foster, Ian; Gusev, Yuriy; Madhavan, Subha

2014-01-01

Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon 's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research. PMID:26925205

Storing and Using Health Data in a Virtual Private Cloud

PubMed Central

Regola, Nathan

2013-01-01

Electronic health records are being adopted at a rapid rate due to increased funding from the US federal government. Health data provide the opportunity to identify possible improvements in health care delivery by applying data mining and statistical methods to the data and will also enable a wide variety of new applications that will be meaningful to patients and medical professionals. Researchers are often granted access to health care data to assist in the data mining process, but HIPAA regulations mandate comprehensive safeguards to protect the data. Often universities (and presumably other research organizations) have an enterprise information technology infrastructure and a research infrastructure. Unfortunately, both of these infrastructures are generally not appropriate for sensitive research data such as HIPAA, as they require special accommodations on the part of the enterprise information technology (or increased security on the part of the research computing environment). Cloud computing, which is a concept that allows organizations to build complex infrastructures on leased resources, is rapidly evolving to the point that it is possible to build sophisticated network architectures with advanced security capabilities. We present a prototype infrastructure in Amazon’s Virtual Private Cloud to allow researchers and practitioners to utilize the data in a HIPAA-compliant environment. PMID:23485880

System Architecture Development for Energy and Water Infrastructure Data Management and Geovisual Analytics

NASA Astrophysics Data System (ADS)

Berres, A.; Karthik, R.; Nugent, P.; Sorokine, A.; Myers, A.; Pang, H.

2017-12-01

Building an integrated data infrastructure that can meet the needs of a sustainable energy-water resource management requires a robust data management and geovisual analytics platform, capable of cross-domain scientific discovery and knowledge generation. Such a platform can facilitate the investigation of diverse complex research and policy questions for emerging priorities in Energy-Water Nexus (EWN) science areas. Using advanced data analytics, machine learning techniques, multi-dimensional statistical tools, and interactive geovisualization components, such a multi-layered federated platform is being developed, the Energy-Water Nexus Knowledge Discovery Framework (EWN-KDF). This platform utilizes several enterprise-grade software design concepts and standards such as extensible service-oriented architecture, open standard protocols, event-driven programming model, enterprise service bus, and adaptive user interfaces to provide a strategic value to the integrative computational and data infrastructure. EWN-KDF is built on the Compute and Data Environment for Science (CADES) environment in Oak Ridge National Laboratory (ORNL).

NHERI: Advancing the Research Infrastructure of the Multi-Hazard Community

NASA Astrophysics Data System (ADS)

Blain, C. A.; Ramirez, J. A.; Bobet, A.; Browning, J.; Edge, B.; Holmes, W.; Johnson, D.; Robertson, I.; Smith, T.; Zuo, D.

2017-12-01

The Natural Hazards Engineering Research Infrastructure (NHERI), supported by the National Science Foundation (NSF), is a distributed, multi-user national facility that provides the natural hazards research community with access to an advanced research infrastructure. Components of NHERI are comprised of a Network Coordination Office (NCO), a cloud-based cyberinfrastructure (DesignSafe-CI), a computational modeling and simulation center (SimCenter), and eight Experimental Facilities (EFs), including a post-disaster, rapid response research facility (RAPID). Utimately NHERI enables researchers to explore and test ground-breaking concepts to protect homes, businesses and infrastructure lifelines from earthquakes, windstorms, tsunamis, and surge enabling innovations to help prevent natural hazards from becoming societal disasters. When coupled with education and community outreach, NHERI will facilitate research and educational advances that contribute knowledge and innovation toward improving the resiliency of the nation's civil infrastructure to withstand natural hazards. The unique capabilities and coordinating activities over Year 1 between NHERI's DesignSafe-CI, the SimCenter, and individual EFs will be presented. Basic descriptions of each component are also found at https://www.designsafe-ci.org/facilities/. Additionally to be discussed are the various roles of the NCO in leading development of a 5-year multi-hazard science plan, coordinating facility scheduling and fostering the sharing of technical knowledge and best practices, leading education and outreach programs such as the recent Summer Institute and multi-facility REU program, ensuring a platform for technology transfer to practicing engineers, and developing strategic national and international partnerships to support a diverse multi-hazard research and user community.

Achievements and Challenges: Implementing a 1:1 Program in a Secondary School

ERIC Educational Resources Information Center

Keane, Therese; Keane, William

2017-01-01

This longitudinal study explores one secondary school's approach towards implementing a one computer to one student (1:1) program, which commenced in 2011. Prior to 2011, the school was not very technologically advanced, mainly due to financial constraints which impacted on infrastructure, procurement of hardware and software, the availability of…

Genomic cloud computing: legal and ethical points to consider

PubMed Central

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Burton, Paul; Chisholm, Rex; Fortier, Isabel; Goodwin, Pat; Harris, Jennifer; Hveem, Kristian; Kaye, Jane; Kent, Alistair; Knoppers, Bartha Maria; Lindpaintner, Klaus; Little, Julian; Riegman, Peter; Ripatti, Samuli; Stolk, Ronald; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn; Joly, Yann; Kato, Kazuto; Knoppers, Bartha Maria; Rodriguez, Laura Lyman; McPherson, Treasa; Nicolás, Pilar; Ouellette, Francis; Romeo-Casabona, Carlos; Sarin, Rajiv; Wallace, Susan; Wiesner, Georgia; Wilson, Julia; Zeps, Nikolajs; Simkevitz, Howard; De Rienzo, Assunta; Knoppers, Bartha M

2015-01-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These ‘points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure. PMID:25248396

Genomic cloud computing: legal and ethical points to consider.

PubMed

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M

2015-10-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

Digital Rocks Portal: Preservation, Sharing, Remote Visualization and Automated Analysis of Imaged Datasets

NASA Astrophysics Data System (ADS)

Prodanovic, M.; Esteva, M.; Ketcham, R. A.; Hanlon, M.; Pettengill, M.; Ranganath, A.; Venkatesh, A.

2016-12-01

Due to advances in imaging modalities such as X-ray microtomography and scattered electron microscopy, 2D and 3D imaged datasets of rock microstructure on nanometer to centimeter length scale allow investigation of nonlinear flow and mechanical phenomena using numerical approaches. This in turn produces various upscaled parameters required by subsurface flow and deformation simulators. However, a single research group typically specializes in an imaging modality and/or related modeling on a single length scale, and lack of data-sharing infrastructure makes it difficult to integrate different length scales. We developed a sustainable, open and easy-to-use repository called the Digital Rocks Portal (http://www.digitalrocksportal.org), that (1) organizes images and related experimental measurements of different porous materials, (2) improves access to them for a wider community of geosciences or engineering researchers not necessarily trained in computer science or data analysis. Our objective is to enable scientific inquiry and engineering decisions founded on a data-driven basis. We show how the data loaded in the portal can be documented, referenced in publications via digital object identifiers, visualize and linked to other repositories. We then show preliminary results on integrating remote parallel visualization and flow simulation workflow with the pore structures currently stored in the repository. We finally discuss the issues of collecting correct metadata, data discoverability and repository sustainability. This is the first repository for this particular data, but is part of the wider ecosystem of geoscience data and model cyber-infrastructure called "Earthcube" (http://earthcube.org/) sponsored by National Science Foundation. For data sustainability and continuous access, the portal is implemented within the reliable, 24/7 maintained High Performance Computing Infrastructure supported by the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. Long-term storage is provided through the University of Texas System Research Cyber-infrastructure initiative.

Next Generation Distributed Computing for Cancer Research

PubMed Central

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing. PMID:25983539

Next generation distributed computing for cancer research.

PubMed

Agarwal, Pankaj; Owzar, Kouros

2014-01-01

Advances in next generation sequencing (NGS) and mass spectrometry (MS) technologies have provided many new opportunities and angles for extending the scope of translational cancer research while creating tremendous challenges in data management and analysis. The resulting informatics challenge is invariably not amenable to the use of traditional computing models. Recent advances in scalable computing and associated infrastructure, particularly distributed computing for Big Data, can provide solutions for addressing these challenges. In this review, the next generation of distributed computing technologies that can address these informatics problems is described from the perspective of three key components of a computational platform, namely computing, data storage and management, and networking. A broad overview of scalable computing is provided to set the context for a detailed description of Hadoop, a technology that is being rapidly adopted for large-scale distributed computing. A proof-of-concept Hadoop cluster, set up for performance benchmarking of NGS read alignment, is described as an example of how to work with Hadoop. Finally, Hadoop is compared with a number of other current technologies for distributed computing.

Parallel high-performance grid computing: capabilities and opportunities of a novel demanding service and business class allowing highest resource efficiency.

PubMed

Kepper, Nick; Ettig, Ramona; Dickmann, Frank; Stehr, Rene; Grosveld, Frank G; Wedemann, Gero; Knoch, Tobias A

2010-01-01

Especially in the life-science and the health-care sectors the huge IT requirements are imminent due to the large and complex systems to be analysed and simulated. Grid infrastructures play here a rapidly increasing role for research, diagnostics, and treatment, since they provide the necessary large-scale resources efficiently. Whereas grids were first used for huge number crunching of trivially parallelizable problems, increasingly parallel high-performance computing is required. Here, we show for the prime example of molecular dynamic simulations how the presence of large grid clusters including very fast network interconnects within grid infrastructures allows now parallel high-performance grid computing efficiently and thus combines the benefits of dedicated super-computing centres and grid infrastructures. The demands for this service class are the highest since the user group has very heterogeneous requirements: i) two to many thousands of CPUs, ii) different memory architectures, iii) huge storage capabilities, and iv) fast communication via network interconnects, are all needed in different combinations and must be considered in a highly dedicated manner to reach highest performance efficiency. Beyond, advanced and dedicated i) interaction with users, ii) the management of jobs, iii) accounting, and iv) billing, not only combines classic with parallel high-performance grid usage, but more importantly is also able to increase the efficiency of IT resource providers. Consequently, the mere "yes-we-can" becomes a huge opportunity like e.g. the life-science and health-care sectors as well as grid infrastructures by reaching higher level of resource efficiency.

VERCE, Virtual Earthquake and Seismology Research Community in Europe, a new ESFRI initiative integrating data infrastructure, Grid and HPC infrastructures for data integration, data analysis and data modeling in seismology

NASA Astrophysics Data System (ADS)

van Hemert, Jano; Vilotte, Jean-Pierre

2010-05-01

Research in earthquake and seismology addresses fundamental problems in understanding Earth's internal wave sources and structures, and augment applications to societal concerns about natural hazards, energy resources and environmental change. This community is central to the European Plate Observing System (EPOS)—the ESFRI initiative in solid Earth Sciences. Global and regional seismology monitoring systems are continuously operated and are transmitting a growing wealth of data from Europe and from around the world. These tremendous volumes of seismograms, i.e., records of ground motions as a function of time, have a definite multi-use attribute, which puts a great premium on open-access data infrastructures that are integrated globally. In Europe, the earthquake and seismology community is part of the European Integrated Data Archives (EIDA) infrastructure and is structured as "horizontal" data services. On top of this distributed data archive system, the community has developed recently within the EC project NERIES advanced SOA-based web services and a unified portal system. Enabling advanced analysis of these data by utilising a data-aware distributed computing environment is instrumental to fully exploit the cornucopia of data and to guarantee optimal operation of the high-cost monitoring facilities. The strategy of VERCE is driven by the needs of data-intensive applications in data mining and modelling and will be illustrated through a set of applications. It aims to provide a comprehensive architecture and framework adapted to the scale and the diversity of these applications, and to integrate the community data infrastructure with Grid and HPC infrastructures. A first novel aspect is a service-oriented architecture that provides well-equipped integrated workbenches, with an efficient communication layer between data and Grid infrastructures, augmented with bridges to the HPC facilities. A second novel aspect is the coupling between Grid data analysis and HPC data modelling applications through workflow and data sharing mechanisms. VERCE will develop important interactions with the European infrastructure initiatives in Grid and HPC computing. The VERCE team: CNRS-France (IPG Paris, LGIT Grenoble), UEDIN (UK), KNMI-ORFEUS (Holland), EMSC, INGV (Italy), LMU (Germany), ULIV (UK), BADW-LRZ (Germany), SCAI (Germany), CINECA (Italy)

Advanced Decentralized Water/Energy Network Design for Sustainable Infrastructure presentation at the 2012 National Association of Home Builders (NAHB) International Builders'Show

EPA Science Inventory

A university/industry panel will report on the progress and findings of a fivesteve-year project funded by the US Environmental Protection Agency. The project's end product will be a Web-based, 3D computer-simulated residential environment with a decision support system to assist...

Infrastructure for Training and Partnershipes: California Water and Coastal Ocean Resources

NASA Technical Reports Server (NTRS)

Siegel, David A.; Dozier, Jeffrey; Gautier, Catherine; Davis, Frank; Dickey, Tommy; Dunne, Thomas; Frew, James; Keller, Arturo; MacIntyre, Sally; Melack, John

2000-01-01

The purpose of this project was to advance the existing ICESS/Bren School computing infrastructure to allow scientists, students, and research trainees the opportunity to interact with environmental data and simulations in near-real time. Improvements made with the funding from this project have helped to strengthen the research efforts within both units, fostered graduate research training, and helped fortify partnerships with government and industry. With this funding, we were able to expand our computational environment in which computer resources, software, and data sets are shared by ICESS/Bren School faculty researchers in all areas of Earth system science. All of the graduate and undergraduate students associated with the Donald Bren School of Environmental Science and Management and the Institute for Computational Earth System Science have benefited from the infrastructure upgrades accomplished by this project. Additionally, the upgrades fostered a significant number of research projects (attached is a list of the projects that benefited from the upgrades). As originally proposed, funding for this project provided the following infrastructure upgrades: 1) a modem file management system capable of interoperating UNIX and NT file systems that can scale to 6.7 TB, 2) a Qualstar 40-slot tape library with two AIT tape drives and Legato Networker backup/archive software, 3) previously unavailable import/export capability for data sets on Zip, Jaz, DAT, 8mm, CD, and DLT media in addition to a 622Mb/s Internet 2 connection, 4) network switches capable of 100 Mbps to 128 desktop workstations, 5) Portable Batch System (PBS) computational task scheduler, and vi) two Compaq/Digital Alpha XP1000 compute servers each with 1.5 GB of RAM along with an SGI Origin 2000 (purchased partially using funds from this project along with funding from various other sources) to be used for very large computations, as required for simulation of mesoscale meteorology or climate.

Advancing Cyberinfrastructure to support high resolution water resources modeling

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Ogden, F. L.; Jones, N.; Horsburgh, J. S.

2012-12-01

Addressing the problem of how the availability and quality of water resources at large scales are sensitive to climate variability, watershed alterations and management activities requires computational resources that combine data from multiple sources and support integrated modeling. Related cyberinfrastructure challenges include: 1) how can we best structure data and computer models to address this scientific problem through the use of high-performance and data-intensive computing, and 2) how can we do this in a way that discipline scientists without extensive computational and algorithmic knowledge and experience can take advantage of advances in cyberinfrastructure? This presentation will describe a new system called CI-WATER that is being developed to address these challenges and advance high resolution water resources modeling in the Western U.S. We are building on existing tools that enable collaboration to develop model and data interfaces that link integrated system models running within an HPC environment to multiple data sources. Our goal is to enhance the use of computational simulation and data-intensive modeling to better understand water resources. Addressing water resource problems in the Western U.S. requires simulation of natural and engineered systems, as well as representation of legal (water rights) and institutional constraints alongside the representation of physical processes. We are establishing data services to represent the engineered infrastructure and legal and institutional systems in a way that they can be used with high resolution multi-physics watershed modeling at high spatial resolution. These services will enable incorporation of location-specific information on water management infrastructure and systems into the assessment of regional water availability in the face of growing demands, uncertain future meteorological forcings, and existing prior-appropriations water rights. This presentation will discuss the informatics challenges involved with data management and easy-to-use access to high performance computing being tackled in this project.

Model development, testing and experimentation in a CyberWorkstation for Brain-Machine Interface research.

PubMed

Rattanatamrong, Prapaporn; Matsunaga, Andrea; Raiturkar, Pooja; Mesa, Diego; Zhao, Ming; Mahmoudi, Babak; Digiovanna, Jack; Principe, Jose; Figueiredo, Renato; Sanchez, Justin; Fortes, Jose

2010-01-01

The CyberWorkstation (CW) is an advanced cyber-infrastructure for Brain-Machine Interface (BMI) research. It allows the development, configuration and execution of BMI computational models using high-performance computing resources. The CW's concept is implemented using a software structure in which an "experiment engine" is used to coordinate all software modules needed to capture, communicate and process brain signals and motor-control commands. A generic BMI-model template, which specifies a common interface to the CW's experiment engine, and a common communication protocol enable easy addition, removal or replacement of models without disrupting system operation. This paper reviews the essential components of the CW and shows how templates can facilitate the processes of BMI model development, testing and incorporation into the CW. It also discusses the ongoing work towards making this process infrastructure independent.

Cloud computing approaches to accelerate drug discovery value chain.

PubMed

Garg, Vibhav; Arora, Suchir; Gupta, Chitra

2011-12-01

Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

Digital Rocks Portal: a sustainable platform for imaged dataset sharing, translation and automated analysis

NASA Astrophysics Data System (ADS)

Prodanovic, M.; Esteva, M.; Hanlon, M.; Nanda, G.; Agarwal, P.

2015-12-01

Recent advances in imaging have provided a wealth of 3D datasets that reveal pore space microstructure (nm to cm length scale) and allow investigation of nonlinear flow and mechanical phenomena from first principles using numerical approaches. This framework has popularly been called "digital rock physics". Researchers, however, have trouble storing and sharing the datasets both due to their size and the lack of standardized image types and associated metadata for volumetric datasets. This impedes scientific cross-validation of the numerical approaches that characterize large scale porous media properties, as well as development of multiscale approaches required for correct upscaling. A single research group typically specializes in an imaging modality and/or related modeling on a single length scale, and lack of data-sharing infrastructure makes it difficult to integrate different length scales. We developed a sustainable, open and easy-to-use repository called the Digital Rocks Portal, that (1) organizes images and related experimental measurements of different porous materials, (2) improves access to them for a wider community of geosciences or engineering researchers not necessarily trained in computer science or data analysis. Once widely accepter, the repository will jumpstart productivity and enable scientific inquiry and engineering decisions founded on a data-driven basis. This is the first repository of its kind. We show initial results on incorporating essential software tools and pipelines that make it easier for researchers to store and reuse data, and for educators to quickly visualize and illustrate concepts to a wide audience. For data sustainability and continuous access, the portal is implemented within the reliable, 24/7 maintained High Performance Computing Infrastructure supported by the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. Long-term storage is provided through the University of Texas System Research Cyber-infrastructure initiative.

AstroGrid-D: Grid technology for astronomical science

NASA Astrophysics Data System (ADS)

Enke, Harry; Steinmetz, Matthias; Adorf, Hans-Martin; Beck-Ratzka, Alexander; Breitling, Frank; Brüsemeister, Thomas; Carlson, Arthur; Ensslin, Torsten; Högqvist, Mikael; Nickelt, Iliya; Radke, Thomas; Reinefeld, Alexander; Reiser, Angelika; Scholl, Tobias; Spurzem, Rainer; Steinacker, Jürgen; Voges, Wolfgang; Wambsganß, Joachim; White, Steve

2011-02-01

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites (Section 2.1), and advanced applications for specific scientific purposes (Section 2.2), such as a connection to robotic telescopes (Section 2.2.3). We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.

EduCloud: PaaS versus IaaS Cloud Usage for an Advanced Computer Science Course

ERIC Educational Resources Information Center

Vaquero, L. M.

2011-01-01

The cloud has become a widely used term in academia and the industry. Education has not remained unaware of this trend, and several educational solutions based on cloud technologies are already in place, especially for software as a service cloud. However, an evaluation of the educational potential of infrastructure and platform clouds has not…

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Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-10

...-01] Draft NIST Interagency Report (NISTIR) 7823, Advanced Metering Infrastructure Smart Meter... Technology (NIST) seeks comments on Draft NISTIR 7823, Advanced Metering Infrastructure Smart Meter.... Electronic comments should be sent to: Michaela Iorga at [email protected]nist.gov , with a Subject line...

Computer network access to scientific information systems for minority universities

NASA Astrophysics Data System (ADS)

Thomas, Valerie L.; Wakim, Nagi T.

1993-08-01

The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.

NCI's High Performance Computing (HPC) and High Performance Data (HPD) Computing Platform for Environmental and Earth System Data Science

NASA Astrophysics Data System (ADS)

Evans, Ben; Allen, Chris; Antony, Joseph; Bastrakova, Irina; Gohar, Kashif; Porter, David; Pugh, Tim; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

2015-04-01

The National Computational Infrastructure (NCI) has established a powerful and flexible in-situ petascale computational environment to enable both high performance computing and Data-intensive Science across a wide spectrum of national environmental and earth science data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress so far to harmonise the underlying data collections for future interdisciplinary research across these large volume data collections. NCI has established 10+ PBytes of major national and international data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the major Australian national-scale scientific collections), leading research communities, and collaborating overseas organisations. New infrastructures created at NCI mean the data collections are now accessible within an integrated High Performance Computing and Data (HPC-HPD) environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large-scale high-bandwidth Lustre filesystems. The hardware was designed at inception to ensure that it would allow the layered software environment to flexibly accommodate the advancement of future data science. New approaches to software technology and data models have also had to be developed to enable access to these large and exponentially increasing data volumes at NCI. Traditional HPC and data environments are still made available in a way that flexibly provides the tools, services and supporting software systems on these new petascale infrastructures. But to enable the research to take place at this scale, the data, metadata and software now need to evolve together - creating a new integrated high performance infrastructure. The new infrastructure at NCI currently supports a catalogue of integrated, reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. One of the challenges for NCI has been to support existing techniques and methods, while carefully preparing the underlying infrastructure for the transition needed for the next class of Data-intensive Science. In doing so, a flexible range of techniques and software can be made available for application across the corpus of data collections available, and to provide a new infrastructure for future interdisciplinary research.

EarthCube: A Community-Driven Cyberinfrastructure for the Geosciences

NASA Astrophysics Data System (ADS)

Koskela, Rebecca; Ramamurthy, Mohan; Pearlman, Jay; Lehnert, Kerstin; Ahern, Tim; Fredericks, Janet; Goring, Simon; Peckham, Scott; Powers, Lindsay; Kamalabdi, Farzad; Rubin, Ken; Yarmey, Lynn

2017-04-01

EarthCube is creating a dynamic, System of Systems (SoS) infrastructure and data tools to collect, access, analyze, share, and visualize all forms of geoscience data and resources, using advanced collaboration, technological, and computational capabilities. EarthCube, as a joint effort between the U.S. National Science Foundation Directorate for Geosciences and the Division of Advanced Cyberinfrastructure, is a quickly growing community of scientists across all geoscience domains, as well as geoinformatics researchers and data scientists. EarthCube has attracted an evolving, dynamic virtual community of more than 2,500 contributors, including earth, ocean, polar, planetary, atmospheric, geospace, computer and social scientists, educators, and data and information professionals. During 2017, EarthCube will transition to the implementation phase. The implementation will balance "innovation" and "production" to advance cross-disciplinary science goals as well as the development of future data scientists. This presentation will describe the current architecture design for the EarthCube cyberinfrastructure and implementation plan.

75 FR 24973 - Notice Pursuant to the National Cooperative Research and Production Act of 1993-Advanced Coatings...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-06

... Production Act of 1993--Advanced Coatings for Infrastructure Joint Venture Agreement Notice is hereby given... Act of 1993, 15 U.S.C. 4301 et seq. (``the Act''), Advanced Coatings for Infrastructure Joint Venture... and wear resistant coatings to infrastructure. Patricia A. Brink, Deputy Director of Operations...

Bytes: Weapons of Mass Disruption

DTIC Science & Technology

2002-04-01

advances compound the problems of protecting complex global infrastructures from attacks. How should the U.S. integrate the many disparate...deploy and sustain military forces.".16 According to the direst of information warfare theories , all computer systems are vulnerable to attack. The...Crisis Show of Force Punitive Strikes Armed Intervention Regional Conflict Regional War Global Conventional War Strategic Nuclear War IW & C2W area of

Lowering the barriers to computational modeling of Earth's surface: coupling Jupyter Notebooks with Landlab, HydroShare, and CyberGIS for research and education.

NASA Astrophysics Data System (ADS)

Bandaragoda, C.; Castronova, A. M.; Phuong, J.; Istanbulluoglu, E.; Strauch, R. L.; Nudurupati, S. S.; Tarboton, D. G.; Wang, S. W.; Yin, D.; Barnhart, K. R.; Tucker, G. E.; Hutton, E.; Hobley, D. E. J.; Gasparini, N. M.; Adams, J. M.

2017-12-01

The ability to test hypotheses about hydrology, geomorphology and atmospheric processes is invaluable to research in the era of big data. Although community resources are available, there remain significant educational, logistical and time investment barriers to their use. Knowledge infrastructure is an emerging intellectual framework to understand how people are creating, sharing and distributing knowledge - which has been dramatically transformed by Internet technologies. In addition to the technical and social components in a cyberinfrastructure system, knowledge infrastructure considers educational, institutional, and open source governance components required to advance knowledge. We are designing an infrastructure environment that lowers common barriers to reproducing modeling experiments for earth surface investigation. Landlab is an open-source modeling toolkit for building, coupling, and exploring two-dimensional numerical models. HydroShare is an online collaborative environment for sharing hydrologic data and models. CyberGIS-Jupyter is an innovative cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using the Jupyter Notebook based on ROGER - the first cyberGIS supercomputer, so that models that can be elastically reproduced through cloud computing approaches. Our team of geomorphologists, hydrologists, and computer geoscientists has created a new infrastructure environment that combines these three pieces of software to enable knowledge discovery. Through this novel integration, any user can interactively execute and explore their shared data and model resources. Landlab on HydroShare with CyberGIS-Jupyter supports the modeling continuum from fully developed modelling applications, prototyping new science tools, hands on research demonstrations for training workshops, and classroom applications. Computational geospatial models based on big data and high performance computing can now be more efficiently developed, improved, scaled, and seamlessly reproduced among multidisciplinary users, thereby expanding the active learning curriculum and research opportunities for students in earth surface modeling and informatics.

Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

Data issues in the life sciences.

PubMed

Thessen, Anne E; Patterson, David J

2011-01-01

We review technical and sociological issues facing the Life Sciences as they transform into more data-centric disciplines - the "Big New Biology". Three major challenges are: 1) lack of comprehensive standards; 2) lack of incentives for individual scientists to share data; 3) lack of appropriate infrastructure and support. Technological advances with standards, bandwidth, distributed computing, exemplar successes, and a strong presence in the emerging world of Linked Open Data are sufficient to conclude that technical issues will be overcome in the foreseeable future. While motivated to have a shared open infrastructure and data pool, and pressured by funding agencies in move in this direction, the sociological issues determine progress. Major sociological issues include our lack of understanding of the heterogeneous data cultures within Life Sciences, and the impediments to progress include a lack of incentives to build appropriate infrastructures into projects and institutions or to encourage scientists to make data openly available.

Data issues in the life sciences

PubMed Central

Thessen, Anne E.; Patterson, David J.

2011-01-01

Abstract We review technical and sociological issues facing the Life Sciences as they transform into more data-centric disciplines - the “Big New Biology”. Three major challenges are: 1) lack of comprehensive standards; 2) lack of incentives for individual scientists to share data; 3) lack of appropriate infrastructure and support. Technological advances with standards, bandwidth, distributed computing, exemplar successes, and a strong presence in the emerging world of Linked Open Data are sufficient to conclude that technical issues will be overcome in the foreseeable future. While motivated to have a shared open infrastructure and data pool, and pressured by funding agencies in move in this direction, the sociological issues determine progress. Major sociological issues include our lack of understanding of the heterogeneous data cultures within Life Sciences, and the impediments to progress include a lack of incentives to build appropriate infrastructures into projects and institutions or to encourage scientists to make data openly available. PMID:22207805

HPCC and the National Information Infrastructure: an overview.

PubMed Central

Lindberg, D A

1995-01-01

The National Information Infrastructure (NII) or "information superhighway" is a high-priority federal initiative to combine communications networks, computers, databases, and consumer electronics to deliver information services to all U.S. citizens. The NII will be used to improve government and social services while cutting administrative costs. Operated by the private sector, the NII will rely on advanced technologies developed under the direction of the federal High Performance Computing and Communications (HPCC) Program. These include computing systems capable of performing trillions of operations (teraops) per second and networks capable of transmitting billions of bits (gigabits) per second. Among other activities, the HPCC Program supports the national supercomputer research centers, the federal portion of the Internet, and the development of interface software, such as Mosaic, that facilitates access to network information services. Health care has been identified as a critical demonstration area for HPCC technology and an important application area for the NII. As an HPCC participant, the National Library of Medicine (NLM) assists hospitals and medical centers to connect to the Internet through projects directed by the Regional Medical Libraries and through an Internet Connections Program cosponsored by the National Science Foundation. In addition to using the Internet to provide enhanced access to its own information services, NLM sponsors health-related applications of HPCC technology. Examples include the "Visible Human" project and recently awarded contracts for test-bed networks to share patient data and medical images, telemedicine projects to provide consultation and medical care to patients in rural areas, and advanced computer simulations of human anatomy for training in "virtual surgery." PMID:7703935

Using Cloud Computing infrastructure with CloudBioLinux, CloudMan and Galaxy

PubMed Central

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-01-01

Cloud computing has revolutionized availability and access to computing and storage resources; making it possible to provision a large computational infrastructure with only a few clicks in a web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this protocol, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatics analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to setup the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command line interface, and the web-based Galaxy interface. PMID:22700313

Using cloud computing infrastructure with CloudBioLinux, CloudMan, and Galaxy.

PubMed

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-06-01

Cloud computing has revolutionized availability and access to computing and storage resources, making it possible to provision a large computational infrastructure with only a few clicks in a Web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this unit, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatic analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy, into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to set up the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command-line interface, and the Web-based Galaxy interface.

Swiss Experiment: Design, implemention and use of a cross-disciplinary infrastructure for data intensive science

NASA Astrophysics Data System (ADS)

Dawes, N.; Salehi, A.; Clifton, A.; Bavay, M.; Aberer, K.; Parlange, M. B.; Lehning, M.

2010-12-01

It has long been known that environmental processes are cross-disciplinary, but data has continued to be acquired and held for a single purpose. Swiss Experiment is a rapidly evolving cross-disciplinary, distributed sensor data infrastructure, where tools for the environmental science community stem directly from computer science research. The platform uses the bleeding edge of computer science to acquire, store and distribute data and metadata from all environmental science disciplines at a variety of temporal and spatial resolutions. SwissEx is simultaneously developing new technologies to allow low cost, high spatial and temporal resolution measurements such that small areas can be intensely monitored. This data is then combined with existing widespread, low density measurements in the cross-disciplinary platform to provide well documented datasets, which are of use to multiple research disciplines. We present a flexible, generic infrastructure at an advanced stage of development. The infrastructure makes the most of Web 2.0 technologies for a collaborative working environment and as a user interface for a metadata database. This environment is already closely integrated with GSN, an open-source database middleware developed under Swiss Experiment for acquisition and storage of generic time-series data (2D and 3D). GSN can be queried directly by common data processing packages and makes data available in real-time to models and 3rd party software interfaces via its web service interface. It also provides real-time push or pull data exchange between instances, a user management system which leaves data owners in charge of their data, advanced real-time processing and much more. The SwissEx interface is increasingly gaining users and supporting environmental science in Switzerland. It is also an integral part of environmental education projects ClimAtscope and O3E, where the technologies can provide rapid feedback of results for children of all ages and where the data from their own stations can be compared to national data networks.

Optimization and parallelization of the thermal–hydraulic subchannel code CTF for high-fidelity multi-physics applications

DOE PAGES

Salko, Robert K.; Schmidt, Rodney C.; Avramova, Maria N.

2014-11-23

This study describes major improvements to the computational infrastructure of the CTF subchannel code so that full-core, pincell-resolved (i.e., one computational subchannel per real bundle flow channel) simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis.

Systems Biology and Cancer Prevention: All Options on the Table

PubMed Central

Rosenfeld, Simon; Kapetanovic, Izet

2008-01-01

In this paper, we outline the status quo and approaches to further development of the systems biology concepts with focus on applications in cancer prevention science. We discuss the biological aspects of cancer research that are of primary importance in cancer prevention, motivations for their mathematical modeling and some recent advances in computational oncology. We also make an attempt to outline in big conceptual terms the contours of future work aimed at creation of large-scale computational and informational infrastructure for using as a routine tool in cancer prevention science and decision making. PMID:19787092

NFFA-Europe: enhancing European competitiveness in nanoscience research and innovation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Carsughi, Flavio; Fonseca, Luis

2017-06-01

NFFA-EUROPE is an European open access resource for experimental and theoretical nanoscience and sets out a platform to carry out comprehensive projects for multidisciplinary research at the nanoscale extending from synthesis to nanocharacterization to theory and numerical simulation. Advanced infrastructures specialized on growth, nano-lithography, nano-characterization, theory and simulation and fine-analysis with Synchrotron, FEL and Neutron radiation sources are integrated in a multi-site combination to develop frontier research on methods for reproducible nanoscience research and to enable European and international researchers from diverse disciplines to carry out advanced proposals impacting science and innovation. NFFA-EUROPE will enable coordinated access to infrastructures on different aspects of nanoscience research that is not currently available at single specialized ones and without duplicating their specific scopes. Approved user projects will have access to the best suited instruments and support competences for performing the research, including access to analytical large scale facilities, theory and simulation and high-performance computing facilities. Access is offered free of charge to European users and users will receive a financial contribution for their travel, accommodation and subsistence costs. The users access will include several "installations" and will be coordinated through a single entry point portal that will activate an advanced user-infrastructure dialogue to build up a personalized access programme with an increasing return on science and innovation production. The own research activity of NFFA-EUROPE will address key bottlenecks of nanoscience research: nanostructure traceability, protocol reproducibility, in-operando nano-manipulation and analysis, open data.

Quantum Accelerators for High-performance Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Humble, Travis S.; Britt, Keith A.; Mohiyaddin, Fahd A.

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, themore » prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.« less

Unidata Cyberinfrastructure in the Cloud

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.; Young, J. W.

2016-12-01

Data services, software, and user support are critical components of geosciences cyber-infrastructure to help researchers to advance science. With the maturity of and significant advances in cloud computing, it has recently emerged as an alternative new paradigm for developing and delivering a broad array of services over the Internet. Cloud computing is now mature enough in usability in many areas of science and education, bringing the benefits of virtualized and elastic remote services to infrastructure, software, computation, and data. Cloud environments reduce the amount of time and money spent to procure, install, and maintain new hardware and software, and reduce costs through resource pooling and shared infrastructure. Given the enormous potential of cloud-based services, Unidata has been moving to augment its software, services, data delivery mechanisms to align with the cloud-computing paradigm. To realize the above vision, Unidata has worked toward: * Providing access to many types of data from a cloud (e.g., via the THREDDS Data Server, RAMADDA and EDEX servers); * Deploying data-proximate tools to easily process, analyze, and visualize those data in a cloud environment cloud for consumption by any one, by any device, from anywhere, at any time; * Developing and providing a range of pre-configured and well-integrated tools and services that can be deployed by any university in their own private or public cloud settings. Specifically, Unidata has developed Docker for "containerized applications", making them easy to deploy. Docker helps to create "disposable" installs and eliminates many configuration challenges. Containerized applications include tools for data transport, access, analysis, and visualization: THREDDS Data Server, Integrated Data Viewer, GEMPAK, Local Data Manager, RAMADDA Data Server, and Python tools; * Leveraging Jupyter as a central platform and hub with its powerful set of interlinking tools to connect interactively data servers, Python scientific libraries, scripts, and workflows; * Exploring end-to-end modeling and prediction capabilities in the cloud; * Partnering with NOAA and public cloud vendors (e.g., Amazon and OCC) on the NOAA Big Data Project to harness their capabilities and resources for the benefit of the academic community.

Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.

A model to forecast data centre infrastructure costs.

NASA Astrophysics Data System (ADS)

Vernet, R.

2015-12-01

The computing needs in the HEP community are increasing steadily, but the current funding situation in many countries is tight. As a consequence experiments, data centres, and funding agencies have to rationalize resource usage and expenditures. CC-IN2P3 (Lyon, France) provides computing resources to many experiments including LHC, and is a major partner for astroparticle projects like LSST, CTA or Euclid. The financial cost to accommodate all these experiments is substantial and has to be planned well in advance for funding and strategic reasons. In that perspective, leveraging infrastructure expenses, electric power cost and hardware performance observed in our site over the last years, we have built a model that integrates these data and provides estimates of the investments that would be required to cater to the experiments for the mid-term future. We present how our model is built and the expenditure forecast it produces, taking into account the experiment roadmaps. We also examine the resource growth predicted by our model over the next years assuming a flat-budget scenario.

The Sunrise project: An R&D project for a national information infrastructure prototype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Juhnyoung

1995-02-01

Sunrise is a Los Alamos National Laboratory (LANL) project started in October 1993. It is intended to a prototype National Information Infrastructure (NII) development project. A main focus of Sunrise is to tie together enabling technologies (networking, object-oriented distributed computing, graphical interfaces, security, multimedia technologies, and data mining technologies) with several specific applications. A diverse set of application areas was chosen to ensure that the solutions developed in the project are as generic as possible. Some of the application areas are materials modeling, medical records and image analysis, transportation simulations, and education. This paper provides a description of Sunrise andmore » a view of the architecture and objectives of this evolving project. The primary objectives of Sunrise are three-fold: (1) To develop common information-enabling tools for advanced scientific research and its applications to industry; (2) To enhance the capabilities of important research programs at the Laboratory; and (3) To define a new way of collaboration between computer science and industrially relevant research.« less

Data Mining as a Service (DMaaS)

NASA Astrophysics Data System (ADS)

Tejedor, E.; Piparo, D.; Mascetti, L.; Moscicki, J.; Lamanna, M.; Mato, P.

2016-10-01

Data Mining as a Service (DMaaS) is a software and computing infrastructure that allows interactive mining of scientific data in the cloud. It allows users to run advanced data analyses by leveraging the widely adopted Jupyter notebook interface. Furthermore, the system makes it easier to share results and scientific code, access scientific software, produce tutorials and demonstrations as well as preserve the analyses of scientists. This paper describes how a first pilot of the DMaaS service is being deployed at CERN, starting from the notebook interface that has been fully integrated with the ROOT analysis framework, in order to provide all the tools for scientists to run their analyses. Additionally, we characterise the service backend, which combines a set of IT services such as user authentication, virtual computing infrastructure, mass storage, file synchronisation, development portals or batch systems. The added value acquired by the combination of the aforementioned categories of services is discussed, focusing on the opportunities offered by the CERNBox synchronisation service and its massive storage backend, EOS.

Optimisation of Critical Infrastructure Protection: The SiVe Project on Airport Security

NASA Astrophysics Data System (ADS)

Breiing, Marcus; Cole, Mara; D'Avanzo, John; Geiger, Gebhard; Goldner, Sascha; Kuhlmann, Andreas; Lorenz, Claudia; Papproth, Alf; Petzel, Erhard; Schwetje, Oliver

This paper outlines the scientific goals, ongoing work and first results of the SiVe research project on critical infrastructure security. The methodology is generic while pilot studies are chosen from airport security. The outline proceeds in three major steps, (1) building a threat scenario, (2) development of simulation models as scenario refinements, and (3) assessment of alternatives. Advanced techniques of systems analysis and simulation are employed to model relevant airport structures and processes as well as offences. Computer experiments are carried out to compare and optimise alternative solutions. The optimality analyses draw on approaches to quantitative risk assessment recently developed in the operational sciences. To exploit the advantages of the various techniques, an integrated simulation workbench is build up in the project.

A sustainability model based on cloud infrastructures for core and downstream Copernicus services

NASA Astrophysics Data System (ADS)

Manunta, Michele; Calò, Fabiana; De Luca, Claudio; Elefante, Stefano; Farres, Jordi; Guzzetti, Fausto; Imperatore, Pasquale; Lanari, Riccardo; Lengert, Wolfgang; Zinno, Ivana; Casu, Francesco

2014-05-01

The incoming Sentinel missions have been designed to be the first remote sensing satellite system devoted to operational services. In particular, the Synthetic Aperture Radar (SAR) Sentinel-1 sensor, dedicated to globally acquire over land in the interferometric mode, guarantees an unprecedented capability to investigate and monitor the Earth surface deformations related to natural and man-made hazards. Thanks to the global coverage strategy and 12-day revisit time, jointly with the free and open access data policy, such a system will allow an extensive application of Differential Interferometric SAR (DInSAR) techniques. In such a framework, European Commission has been funding several projects through the GMES and Copernicus programs, aimed at preparing the user community to the operational and extensive use of Sentinel-1 products for risk mitigation and management purposes. Among them, the FP7-DORIS, an advanced GMES downstream service coordinated by Italian National Council of Research (CNR), is based on the fully exploitation of advanced DInSAR products in landslides and subsidence contexts. In particular, the DORIS project (www.doris-project.eu) has developed innovative scientific techniques and methodologies to support Civil Protection Authorities (CPA) during the pre-event, event, and post-event phases of the risk management cycle. Nonetheless, the huge data stream expected from the Sentinel-1 satellite may jeopardize the effective use of such data in emergency response and security scenarios. This potential bottleneck can be properly overcome through the development of modern infrastructures, able to efficiently provide computing resources as well as advanced services for big data management, processing and dissemination. In this framework, CNR and ESA have tightened up a cooperation to foster the use of GRID and cloud computing platforms for remote sensing data processing, and to make available to a large audience advanced and innovative tools for DInSAR products generation and exploitation. In particular, CNR is porting the multi-temporal DInSAR technique referred to as Small Baseline Subset (SBAS) into the ESA G-POD (Grid Processing On Demand) and CIOP (Cloud Computing Operational Pilot) platforms (Elefante et al., 2013) within the SuperSites Exploitation Platform (SSEP) project, which aim is contributing to the development of an ecosystem for big geo-data processing and dissemination. This work focuses on presenting the main results that have been achieved by the DORIS project concerning the use of advanced DInSAR products for supporting CPA during the risk management cycle. Furthermore, based on the DORIS experience, a sustainability model for Core and Downstream Copernicus services based on the effective exploitation of cloud platforms is proposed. In this framework, remote sensing community, both service providers and users, can significantly benefit from the Helix Nebula-The Science Cloud initiative, created by European scientific institutions, agencies, SMEs and enterprises to pave the way for the development and exploitation of a cloud computing infrastructure for science. REFERENCES Elefante, S., Imperatore, P. , Zinno, I., M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, F. Casu, 2013, "SBAS-DINSAR Time series generation on cloud computing platforms". IEEE IGARSS Conference, Melbourne (AU), July 2013.

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

A parallel-processing approach to computing for the geographic sciences

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Haga, Jim; Maddox, Brian; Feller, Mark

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting research into various areas, such as advanced computer architecture, algorithms to meet the processing needs for real-time image and data processing, the creation of custom datasets from seamless source data, rapid turn-around of products for emergency response, and support for computationally intense spatial and temporal modeling.

Current Grid operation and future role of the Grid

NASA Astrophysics Data System (ADS)

Smirnova, O.

2012-12-01

Grid-like technologies and approaches became an integral part of HEP experiments. Some other scientific communities also use similar technologies for data-intensive computations. The distinct feature of Grid computing is the ability to federate heterogeneous resources of different ownership into a seamless infrastructure, accessible via a single log-on. Like other infrastructures of similar nature, Grid functioning requires not only technologically sound basis, but also reliable operation procedures, monitoring and accounting. The two aspects, technological and operational, are closely related: weaker is the technology, more burden is on operations, and other way around. As of today, Grid technologies are still evolving: at CERN alone, every LHC experiment uses an own Grid-like system. This inevitably creates a heavy load on operations. Infrastructure maintenance, monitoring and incident response are done on several levels, from local system administrators to large international organisations, involving massive human effort worldwide. The necessity to commit substantial resources is one of the obstacles faced by smaller research communities when moving computing to the Grid. Moreover, most current Grid solutions were developed under significant influence of HEP use cases, and thus need additional effort to adapt them to other applications. Reluctance of many non-HEP researchers to use Grid negatively affects the outlook for national Grid organisations, which strive to provide multi-science services. We started from the situation where Grid organisations were fused with HEP laboratories and national HEP research programmes; we hope to move towards the world where Grid will ultimately reach the status of generic public computing and storage service provider and permanent national and international Grid infrastructures will be established. How far will we be able to advance along this path, depends on us. If no standardisation and convergence efforts will take place, Grid will become limited to HEP; if however the current multitude of Grid-like systems will converge to a generic, modular and extensible solution, Grid will become true to its name.

Characterizing Crowd Participation and Productivity of Foldit Through Web Scraping

DTIC Science & Technology

2016-03-01

Berkeley Open Infrastructure for Network Computing CDF Cumulative Distribution Function CPU Central Processing Unit CSSG Crowdsourced Serious Game...computers at once can create a similar capacity. According to Anderson [6], principal investigator for the Berkeley Open Infrastructure for Network...extraterrestrial life. From this project, a software-based distributed computing platform called the Berkeley Open Infrastructure for Network Computing

Laboratory directed research and development annual report 2004.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

This report summarizes progress from the Laboratory Directed Research and Development (LDRD) program during fiscal year 2004. In addition to a programmatic and financial overview, the report includes progress reports from 352 individual R and D projects in 15 categories. The 15 categories are: (1) Advanced Concepts; (2) Advanced Manufacturing; (3) Biotechnology; (4) Chemical and Earth Sciences; (5) Computational and Information Sciences; (6) Differentiating Technologies; (7) Electronics and Photonics; (8) Emerging Threats; (9) Energy and Critical Infrastructures; (10) Engineering Sciences; (11) Grand Challenges; (12) Materials Science and Technology; (13) Nonproliferation and Materials Control; (14) Pulsed Power and High Energy Densitymore » Sciences; and (15) Corporate Objectives.« less

International Symposium on Grids and Clouds (ISGC) 2014

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2014 will be held at Academia Sinica in Taipei, Taiwan from 23-28 March 2014, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC).“Bringing the data scientist to global e-Infrastructures” is the theme of ISGC 2014. The last decade has seen the phenomenal growth in the production of data in all forms by all research communities to produce a deluge of data from which information and knowledge need to be extracted. Key to this success will be the data scientist - educated to use advanced algorithms, applications and infrastructures - collaborating internationally to tackle society’s challenges. ISGC 2014 will bring together researchers working in all aspects of data science from different disciplines around the world to collaborate and educate themselves in the latest achievements and techniques being used to tackle the data deluge. In addition to the regular workshops, technical presentations and plenary keynotes, ISGC this year will focus on how to grow the data science community by considering the educational foundation needed for tomorrow’s data scientist. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities & Social Sciences Application, Virtual Research Environment (including Middleware, tools, services, workflow, ... etc.), Data Management, Big Data, Infrastructure & Operations Management, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC).

The Next Generation of Lab and Classroom Computing - The Silver Lining

DTIC Science & Technology

2016-12-01

desktop infrastructure (VDI) solution, as well as the computing solutions at three universities, was selected as the basis for comparison. The research... infrastructure , VDI, hardware cost, software cost, manpower, availability, cloud computing, private cloud, bring your own device, BYOD, thin client...virtual desktop infrastructure (VDI) solution, as well as the computing solutions at three universities, was selected as the basis for comparison. The

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

LXtoo: an integrated live Linux distribution for the bioinformatics community

PubMed Central

2012-01-01

Background Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Findings Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. Conclusions LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo. PMID:22813356

LXtoo: an integrated live Linux distribution for the bioinformatics community.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu

2012-07-19

Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

Advanced Metering Infrastructure based on Smart Meters

NASA Astrophysics Data System (ADS)

Suzuki, Hiroshi

By specifically designating penetrations rates of advanced meters and communication technologies, devices and systems, this paper introduces that the penetration of advanced metering is important for the future development of electric power system infrastructure. It examines the state of the technology and the economical benefits of advanced metering. One result of the survey is that advanced metering currently has a penetration of about six percent of total installed electric meters in the United States. Applications to the infrastructure differ by type of organization. Being integrated with emerging communication technologies, smart meters enable several kinds of features such as, not only automatic meter reading but also distribution management control, outage management, remote switching, etc.

Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

NASA Astrophysics Data System (ADS)

Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

2016-05-01

Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments.

PubMed

Burdick, David B; Cavnor, Chris C; Handcock, Jeremy; Killcoyne, Sarah; Lin, Jake; Marzolf, Bruz; Ramsey, Stephen A; Rovira, Hector; Bressler, Ryan; Shmulevich, Ilya; Boyle, John

2010-07-14

High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

PubMed Central

2010-01-01

Background High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Results Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. Conclusion The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services. PMID:20630057

The dependence of educational infrastructure on clinical infrastructure.

PubMed Central

Cimino, C.

1998-01-01

The Albert Einstein College of Medicine needed to assess the growth of its infrastructure for educational computing as a first step to determining if student needs were being met. Included in computing infrastructure are space, equipment, software, and computing services. The infrastructure was assessed by reviewing purchasing and support logs for a six year period from 1992 to 1998. This included equipment, software, and e-mail accounts provided to students and to faculty for educational purposes. Student space has grown at a constant rate (averaging 14% increase each year respectively). Student equipment on campus has grown by a constant amount each year (average 8.3 computers each year). Student infrastructure off campus and educational support of faculty has not kept pace. It has either declined or remained level over the six year period. The availability of electronic mail clearly demonstrates this with accounts being used by 99% of students, 78% of Basic Science Course Leaders, 38% of Clerkship Directors, 18% of Clerkship Site Directors, and 8% of Clinical Elective Directors. The collection of the initial descriptive infrastructure data has revealed problems that may generalize to other medical schools. The discrepancy between infrastructure available to students and faculty on campus and students and faculty off campus creates a setting where students perceive a paradoxical declining support for computer use as they progress through medical school. While clinical infrastructure may be growing, it is at the expense of educational infrastructure at affiliate hospitals. PMID:9929262

Interoperability and security in wireless body area network infrastructures.

PubMed

Warren, Steve; Lebak, Jeffrey; Yao, Jianchu; Creekmore, Jonathan; Milenkovic, Aleksandar; Jovanov, Emil

2005-01-01

Wireless body area networks (WBANs) and their supporting information infrastructures offer unprecedented opportunities to monitor state of health without constraining the activities of a wearer. These mobile point-of-care systems are now realizable due to the convergence of technologies such as low-power wireless communication standards, plug-and-play device buses, off-the-shelf development kits for low-power microcontrollers, handheld computers, electronic medical records, and the Internet. To increase acceptance of personal monitoring technology while lowering equipment cost, advances must be made in interoperability (at both the system and device levels) and security. This paper presents an overview of WBAN infrastructure work in these areas currently underway in the Medical Component Design Laboratory at Kansas State University (KSU) and at the University of Alabama in Huntsville (UAH). KSU efforts include the development of wearable health status monitoring systems that utilize ISO/IEEE 11073, Bluetooth, Health Level 7, and OpenEMed. WBAN efforts at UAH include the development of wearable activity and health monitors that incorporate ZigBee-compliant wireless sensor platforms with hardware-level encryption and the TinyOS development environment. WBAN infrastructures are complex, requiring many functional support elements. To realize these infrastructures through collaborative efforts, organizations such as KSU and UAH must define and utilize standard interfaces, nomenclature, and security approaches.

Infrastructures for Distributed Computing: the case of BESIII

NASA Astrophysics Data System (ADS)

Pellegrino, J.

2018-05-01

The BESIII is an electron-positron collision experiment hosted at BEPCII in Beijing and aimed to investigate Tau-Charm physics. Now BESIII has been running for several years and gathered more than 1PB raw data. In order to analyze these data and perform massive Monte Carlo simulations, a large amount of computing and storage resources is needed. The distributed computing system is based up on DIRAC and it is in production since 2012. It integrates computing and storage resources from different institutes and a variety of resource types such as cluster, grid, cloud or volunteer computing. About 15 sites from BESIII Collaboration from all over the world joined this distributed computing infrastructure, giving a significant contribution to the IHEP computing facility. Nowadays cloud computing is playing a key role in the HEP computing field, due to its scalability and elasticity. Cloud infrastructures take advantages of several tools, such as VMDirac, to manage virtual machines through cloud managers according to the job requirements. With the virtually unlimited resources from commercial clouds, the computing capacity could scale accordingly in order to deal with any burst demands. General computing models have been discussed in the talk and are addressed herewith, with particular focus on the BESIII infrastructure. Moreover new computing tools and upcoming infrastructures will be addressed.

A Development of Lightweight Grid Interface

NASA Astrophysics Data System (ADS)

Iwai, G.; Kawai, Y.; Sasaki, T.; Watase, Y.

2011-12-01

In order to help a rapid development of Grid/Cloud aware applications, we have developed API to abstract the distributed computing infrastructures based on SAGA (A Simple API for Grid Applications). SAGA, which is standardized in the OGF (Open Grid Forum), defines API specifications to access distributed computing infrastructures, such as Grid, Cloud and local computing resources. The Universal Grid API (UGAPI), which is a set of command line interfaces (CLI) and APIs, aims to offer simpler API to combine several SAGA interfaces with richer functionalities. These CLIs of the UGAPI offer typical functionalities required by end users for job management and file access to the different distributed computing infrastructures as well as local computing resources. We have also built a web interface for the particle therapy simulation and demonstrated the large scale calculation using the different infrastructures at the same time. In this paper, we would like to present how the web interface based on UGAPI and SAGA achieve more efficient utilization of computing resources over the different infrastructures with technical details and practical experiences.

The Satellite Data Thematic Core Service within the EPOS Research Infrastructure

NASA Astrophysics Data System (ADS)

Manunta, Michele; Casu, Francesco; Zinno, Ivana; De Luca, Claudio; Buonanno, Sabatino; Zeni, Giovanni; Wright, Tim; Hooper, Andy; Diament, Michel; Ostanciaux, Emilie; Mandea, Mioara; Walter, Thomas; Maccaferri, Francesco; Fernandez, Josè; Stramondo, Salvatore; Bignami, Christian; Bally, Philippe; Pinto, Salvatore; Marin, Alessandro; Cuomo, Antonio

2017-04-01

EPOS, the European Plate Observing System, is a long-term plan to facilitate the integrated use of data, data products, software and services, available from distributed Research Infrastructures (RI), for solid Earth science in Europe. Indeed, EPOS integrates a large number of existing European RIs belonging to several fields of the Earth science, from seismology to geodesy, near fault and volcanic observatories as well as anthropogenic hazards. The EPOS vision is that the integration of the existing national and trans-national research infrastructures will increase access and use of the multidisciplinary data recorded by the solid Earth monitoring networks, acquired in laboratory experiments and/or produced by computational simulations. The establishment of EPOS will foster the interoperability of products and services in the Earth science field to a worldwide community of users. Accordingly, the EPOS aim is to integrate the diverse and advanced European Research Infrastructures for solid Earth science, and build on new e-science opportunities to monitor and understand the dynamic and complex solid-Earth System. One of the EPOS Thematic Core Services (TCS), referred to as Satellite Data, aims at developing, implementing and deploying advanced satellite data products and services, mainly based on Copernicus data (namely Sentinel acquisitions), for the Earth science community. This work intends to present the technological enhancements, fostered by EPOS, to deploy effective satellite services in a harmonized and integrated way. In particular, the Satellite Data TCS will deploy five services, EPOSAR, GDM, COMET, 3D-Def and MOD, which are mainly based on the exploitation of SAR data acquired by the Sentinel-1 constellation and designed to provide information on Earth surface displacements. In particular, the planned services will provide both advanced DInSAR products (deformation maps, velocity maps, deformation time series) and value-added measurements (source model, 3D displacement maps, seismic hazard maps). Moreover, the services will release both on-demand and systematic products. The latter will be generated and made available to the users on a continuous basis, by processing each Sentinel-1 data once acquired, over a defined number of areas of interest; while the former will allow users to select data, areas, and time period to carry out their own analyses via an on-line platform. The satellite components will be integrated within the EPOS infrastructure through a common and harmonized interface that will allow users to search, process and share remote sensing images and results. This gateway to the satellite services will be represented by the ESA- Geohazards Exploitation Platform (GEP), a new cloud-based platform for the satellite Earth Observations designed to support the scientific community in the understanding of high impact natural disasters. Satellite Data TCS will use GEP as the common interface toward the main EPOS portal to provide EPOS users not only with data products but also with relevant processing and visualisation software, thus allowing users to gather and process on a cloud-computing infrastructure large datasets without any need to download them locally.

In-Space Propulsion: Connectivity to In-Space Fabrication and Repair

NASA Technical Reports Server (NTRS)

Johnson, L.; Harris, D.; Trausch, A.; Matloff, G. L.; Taylor, T.; Cutting, K.

2005-01-01

The connectivity between new in-space propulsion technologies and the ultimate development of an in-space fabrication and repair infrastructure are described in this Technical Memorandum. A number of advanced in-space propulsion technologies are being developed by NASA, many of which are directly relevant to the establishment of such an in-space infrastructure. These include aerocapture, advanced solar-electric propulsion, solar-thermal propulsion, advanced chemical propulsion, tethers, and solar photon sails. Other, further-term technologies have also been studied to assess their utility to the development of such an infrastructure.

Telescience workstation

NASA Technical Reports Server (NTRS)

Brown, Robert L.; Doyle, Dee; Haines, Richard F.; Slocum, Michael

1989-01-01

As part of the Telescience Testbed Pilot Program, the Universities Space Research Association/ Research Institute for Advanced Computer Science (USRA/RIACS) proposed to support remote communication by providing a network of human/machine interfaces, computer resources, and experimental equipment which allows: remote science, collaboration, technical exchange, and multimedia communication. The telescience workstation is intended to provide a local computing environment for telescience. The purpose of the program are as follows: (1) to provide a suitable environment to integrate existing and new software for a telescience workstation; (2) to provide a suitable environment to develop new software in support of telescience activities; (3) to provide an interoperable environment so that a wide variety of workstations may be used in the telescience program; (4) to provide a supportive infrastructure and a common software base; and (5) to advance, apply, and evaluate the telescience technolgy base. A prototype telescience computing environment designed to bring practicing scientists in domains other than their computer science into a modern style of doing their computing was created and deployed. This environment, the Telescience Windowing Environment, Phase 1 (TeleWEn-1), met some, but not all of the goals stated above. The TeleWEn-1 provided a window-based workstation environment and a set of tools for text editing, document preparation, electronic mail, multimedia mail, raster manipulation, and system management.

Cloud Computing in Support of Applied Learning: A Baseline Study of Infrastructure Design at Southern Polytechnic State University

ERIC Educational Resources Information Center

Conn, Samuel S.; Reichgelt, Han

2013-01-01

Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…

Biomedical informatics research network: building a national collaboratory to hasten the derivation of new understanding and treatment of disease.

PubMed

Grethe, Jeffrey S; Baru, Chaitan; Gupta, Amarnath; James, Mark; Ludaescher, Bertram; Martone, Maryann E; Papadopoulos, Philip M; Peltier, Steven T; Rajasekar, Arcot; Santini, Simone; Zaslavsky, Ilya N; Ellisman, Mark H

2005-01-01

Through support from the National Institutes of Health's National Center for Research Resources, the Biomedical Informatics Research Network (BIRN) is pioneering the use of advanced cyberinfrastructure for medical research. By synchronizing developments in advanced wide area networking, distributed computing, distributed database federation, and other emerging capabilities of e-science, the BIRN has created a collaborative environment that is paving the way for biomedical research and clinical information management. The BIRN Coordinating Center (BIRN-CC) is orchestrating the development and deployment of key infrastructure components for immediate and long-range support of biomedical and clinical research being pursued by domain scientists in three neuroimaging test beds.

Building Nationally-Focussed, Globally Federated, High Performance Earth Science Platforms to Solve Next Generation Social and Economic Issues.

NASA Astrophysics Data System (ADS)

Wyborn, Lesley; Evans, Ben; Foster, Clinton; Pugh, Timothy; Uhlherr, Alfred

2015-04-01

Digital geoscience data and information are integral to informing decisions on the social, economic and environmental management of natural resources. Traditionally, such decisions were focused on regional or national viewpoints only, but it is increasingly being recognised that global perspectives are required to meet new challenges such as predicting impacts of climate change; sustainably exploiting scarce water, mineral and energy resources; and protecting our communities through better prediction of the behaviour of natural hazards. In recent years, technical advances in scientific instruments have resulted in a surge in data volumes, with data now being collected at unprecedented rates and at ever increasing resolutions. The size of many earth science data sets now exceed the computational capacity of many government and academic organisations to locally store and dynamically access the data sets; to internally process and analyse them to high resolutions; and then to deliver them online to clients, partners and stakeholders. Fortunately, at the same time, computational capacities have commensurately increased (both cloud and HPC): these can now provide the capability to effectively access the ever-growing data assets within realistic time frames. However, to achieve this, data and computing need to be co-located: bandwidth limits the capacity to move the large data sets; the data transfers are too slow; and latencies to access them are too high. These scenarios are driving the move towards more centralised High Performance (HP) Infrastructures. The rapidly increasing scale of data, the growing complexity of software and hardware environments, combined with the energy costs of running such infrastructures is creating a compelling economic argument for just having one or two major national (or continental) HP facilities that can be federated internationally to enable earth and environmental issues to be tackled at global scales. But at the same time, if properly constructed, these infrastructures can also service very small-scale research projects. The National Computational Infrastructure (NCI) at the Australian National University (ANU) has built such an HP infrastructure as part of the Australian Government's National Collaborative Research Infrastructure Strategy. NCI operates as a formal partnership between the ANU and the three major Australian National Government Scientific Agencies: the Commonwealth Scientific and Industrial Research Organisation (CSIRO), the Bureau of Meteorology and Geoscience Australia. The government partners agreed to explore the new opportunities offered within the partnership with NCI, rather than each running their own separate agenda independently. The data from these national agencies, as well as from collaborating overseas organisations (e.g., NASA, NOAA, USGS, CMIP, etc.) are either replicated to, or produced at, NCI. By co-locating and harmonising these vast data collections within the integrated HP computing environments at NCI, new opportunities have arisen for Data-intensive Interdisciplinary Science at scales and resolutions not hitherto possible. The new NCI infrastructure has also enabled the blending of research by the university sector with the more operational business of government science agencies, with the fundamental shift being that researchers from both sectors work and collaborate within a federated data and computational environment that contains both national and international data collections.

Opportunities and challenges of big data for the social sciences: The case of genomic data.

PubMed

Liu, Hexuan; Guo, Guang

2016-09-01

In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research. Copyright © 2016 Elsevier Inc. All rights reserved.

The Advanced Technology Operations System: ATOS

NASA Technical Reports Server (NTRS)

Kaufeler, J.-F.; Laue, H. A.; Poulter, K.; Smith, H.

1993-01-01

Mission control systems supporting new space missions face ever-increasing requirements in terms of functionality, performance, reliability and efficiency. Modern data processing technology is providing the means to meet these requirements in new systems under development. During the past few years the European Space Operations Centre (ESOC) of the European Space Agency (ESA) has carried out a number of projects to demonstrate the feasibility of using advanced software technology, in particular, knowledge based systems, to support mission operations. A number of advances must be achieved before these techniques can be moved towards operational use in future missions, namely, integration of the applications into a single system framework and generalization of the applications so that they are mission independent. In order to achieve this goal, ESA initiated the Advanced Technology Operations System (ATOS) program, which will develop the infrastructure to support advanced software technology in mission operations, and provide applications modules to initially support: Mission Preparation, Mission Planning, Computer Assisted Operations, and Advanced Training. The first phase of the ATOS program is tasked with the goal of designing and prototyping the necessary system infrastructure to support the rest of the program. The major components of the ATOS architecture is presented. This architecture relies on the concept of a Mission Information Base (MIB) as the repository for all information and knowledge which will be used by the advanced application modules in future mission control systems. The MIB is being designed to exploit the latest in database and knowledge representation technology in an open and distributed system. In conclusion the technological and implementation challenges expected to be encountered, as well as the future plans and time scale of the project, are presented.

Water Intelligence and the Cyber-Infrastructure Revolution

NASA Astrophysics Data System (ADS)

Cline, D. W.

2015-12-01

As an intrinsic factor in national security, the global economy, food and energy production, and human and ecological health, fresh water resources are increasingly being considered by an ever-widening array of stakeholders. The U.S. intelligence community has identified water as a key factor in the Nation's security risk profile. Water industries are growing rapidly, and seek to revolutionize the role of water in the global economy, making water an economic value rather than a limitation on operations. Recent increased focus on the complex interrelationships and interdependencies between water, food, and energy signal a renewed effort to move towards integrated water resource management. Throughout all of this, hydrologic extremes continue to wreak havoc on communities and regions around the world, in some cases threatening long-term economic stability. This increased attention on water coincides with the "second IT revolution" of cyber-infrastructure (CI). The CI concept is a convergence of technology, data, applications and human resources, all coalescing into a tightly integrated global grid of computing, information, networking and sensor resources, and ultimately serving as an engine of change for collaboration, education and scientific discovery and innovation. In the water arena, we have unprecedented opportunities to apply the CI concept to help address complex water challenges and shape the future world of water resources - on both science and socio-economic application fronts. Providing actionable local "water intelligence" nationally or globally is now becoming feasible through high-performance computing, data technologies, and advanced hydrologic modeling. Further development on all of these fronts appears likely and will help advance this much-needed capability. Lagging behind are water observation systems, especially in situ networks, which need significant innovation to keep pace with and help fuel rapid advancements in water intelligence.

Intelligent systems technology infrastructure for integrated systems

NASA Technical Reports Server (NTRS)

Lum, Henry

1991-01-01

A system infrastructure must be properly designed and integrated from the conceptual development phase to accommodate evolutionary intelligent technologies. Several technology development activities were identified that may have application to rendezvous and capture systems. Optical correlators in conjunction with fuzzy logic control might be used for the identification, tracking, and capture of either cooperative or non-cooperative targets without the intensive computational requirements associated with vision processing. A hybrid digital/analog system was developed and tested with a robotic arm. An aircraft refueling application demonstration is planned within two years. Initially this demonstration will be ground based with a follow-on air based demonstration. System dependability measurement and modeling techniques are being developed for fault management applications. This involves usage of incremental solution/evaluation techniques and modularized systems to facilitate reuse and to take advantage of natural partitions in system models. Though not yet commercially available and currently subject to accuracy limitations, technology is being developed to perform optical matrix operations to enhance computational speed. Optical terrain recognition using camera image sequencing processed with optical correlators is being developed to determine position and velocity in support of lander guidance. The system is planned for testing in conjunction with Dryden Flight Research Facility. Advanced architecture technology is defining open architecture design constraints, test bed concepts (processors, multiple hardware/software and multi-dimensional user support, knowledge/tool sharing infrastructure), and software engineering interface issues.

The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.

2013-01-01

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276

Earth System Grid II, Turning Climate Datasets into Community Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Middleton, Don

2006-08-01

The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects,more » we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.« less

Sustaining a Community Computing Infrastructure for Online Teacher Professional Development: A Case Study of Designing Tapped In

NASA Astrophysics Data System (ADS)

Farooq, Umer; Schank, Patricia; Harris, Alexandra; Fusco, Judith; Schlager, Mark

Community computing has recently grown to become a major research area in human-computer interaction. One of the objectives of community computing is to support computer-supported cooperative work among distributed collaborators working toward shared professional goals in online communities of practice. A core issue in designing and developing community computing infrastructures — the underlying sociotechnical layer that supports communitarian activities — is sustainability. Many community computing initiatives fail because the underlying infrastructure does not meet end user requirements; the community is unable to maintain a critical mass of users consistently over time; it generates insufficient social capital to support significant contributions by members of the community; or, as typically happens with funded initiatives, financial and human capital resource become unavailable to further maintain the infrastructure. On the basis of more than 9 years of design experience with Tapped In-an online community of practice for education professionals — we present a case study that discusses four design interventions that have sustained the Tapped In infrastructure and its community to date. These interventions represent broader design strategies for developing online environments for professional communities of practice.

A Cloud-based Infrastructure and Architecture for Environmental System Research

NASA Astrophysics Data System (ADS)

Wang, D.; Wei, Y.; Shankar, M.; Quigley, J.; Wilson, B. E.

2016-12-01

The present availability of high-capacity networks, low-cost computers and storage devices, and the widespread adoption of hardware virtualization and service-oriented architecture provide a great opportunity to enable data and computing infrastructure sharing between closely related research activities. By taking advantage of these approaches, along with the world-class high computing and data infrastructure located at Oak Ridge National Laboratory, a cloud-based infrastructure and architecture has been developed to efficiently deliver essential data and informatics service and utilities to the environmental system research community, and will provide unique capabilities that allows terrestrial ecosystem research projects to share their software utilities (tools), data and even data submission workflow in a straightforward fashion. The infrastructure will minimize large disruptions from current project-based data submission workflows for better acceptances from existing projects, since many ecosystem research projects already have their own requirements or preferences for data submission and collection. The infrastructure will eliminate scalability problems with current project silos by provide unified data services and infrastructure. The Infrastructure consists of two key components (1) a collection of configurable virtual computing environments and user management systems that expedite data submission and collection from environmental system research community, and (2) scalable data management services and system, originated and development by ORNL data centers.

CE-ACCE: The Cloud Enabled Advanced sCience Compute Environment

NASA Astrophysics Data System (ADS)

Cinquini, L.; Freeborn, D. J.; Hardman, S. H.; Wong, C.

2017-12-01

Traditionally, Earth Science data from NASA remote sensing instruments has been processed by building custom data processing pipelines (often based on a common workflow engine or framework) which are typically deployed and run on an internal cluster of computing resources. This approach has some intrinsic limitations: it requires each mission to develop and deploy a custom software package on top of the adopted framework; it makes use of dedicated hardware, network and storage resources, which must be specifically purchased, maintained and re-purposed at mission completion; and computing services cannot be scaled on demand beyond the capability of the available servers.More recently, the rise of Cloud computing, coupled with other advances in containerization technology (most prominently, Docker) and micro-services architecture, has enabled a new paradigm, whereby space mission data can be processed through standard system architectures, which can be seamlessly deployed and scaled on demand on either on-premise clusters, or commercial Cloud providers. In this talk, we will present one such architecture named CE-ACCE ("Cloud Enabled Advanced sCience Compute Environment"), which we have been developing at the NASA Jet Propulsion Laboratory over the past year. CE-ACCE is based on the Apache OODT ("Object Oriented Data Technology") suite of services for full data lifecycle management, which are turned into a composable array of Docker images, and complemented by a plug-in model for mission-specific customization. We have applied this infrastructure to both flying and upcoming NASA missions, such as ECOSTRESS and SMAP, and demonstrated deployment on the Amazon Cloud, either using simple EC2 instances, or advanced AWS services such as Amazon Lambda and ECS (EC2 Container Services).

Managing a tier-2 computer centre with a private cloud infrastructure

NASA Astrophysics Data System (ADS)

Bagnasco, Stefano; Berzano, Dario; Brunetti, Riccardo; Lusso, Stefano; Vallero, Sara

2014-06-01

In a typical scientific computing centre, several applications coexist and share a single physical infrastructure. An underlying Private Cloud infrastructure eases the management and maintenance of such heterogeneous applications (such as multipurpose or application-specific batch farms, Grid sites, interactive data analysis facilities and others), allowing dynamic allocation resources to any application. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques. Such infrastructures are being deployed in some large centres (see e.g. the CERN Agile Infrastructure project), but with several open-source tools reaching maturity this is becoming viable also for smaller sites. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 centre, an Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The private cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem and the OpenWRT Linux distribution (used for network virtualization); a future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and OCCI.

High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habib, Salman; Roser, Robert

Computing plays an essential role in all aspects of high energy physics. As computational technology evolves rapidly in new directions, and data throughput and volume continue to follow a steep trend-line, it is important for the HEP community to develop an effective response to a series of expected challenges. In order to help shape the desired response, the HEP Forum for Computational Excellence (HEP-FCE) initiated a roadmap planning activity with two key overlapping drivers -- 1) software effectiveness, and 2) infrastructure and expertise advancement. The HEP-FCE formed three working groups, 1) Applications Software, 2) Software Libraries and Tools, and 3)more » Systems (including systems software), to provide an overview of the current status of HEP computing and to present findings and opportunities for the desired HEP computational roadmap. The final versions of the reports are combined in this document, and are presented along with introductory material.« less

Internet-based computer technology on radiotherapy.

PubMed

Chow, James C L

2017-01-01

Recent rapid development of Internet-based computer technologies has made possible many novel applications in radiation dose delivery. However, translational speed of applying these new technologies in radiotherapy could hardly catch up due to the complex commissioning process and quality assurance protocol. Implementing novel Internet-based technology in radiotherapy requires corresponding design of algorithm and infrastructure of the application, set up of related clinical policies, purchase and development of software and hardware, computer programming and debugging, and national to international collaboration. Although such implementation processes are time consuming, some recent computer advancements in the radiation dose delivery are still noticeable. In this review, we will present the background and concept of some recent Internet-based computer technologies such as cloud computing, big data processing and machine learning, followed by their potential applications in radiotherapy, such as treatment planning and dose delivery. We will also discuss the current progress of these applications and their impacts on radiotherapy. We will explore and evaluate the expected benefits and challenges in implementation as well.

High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habib, Salman; Roser, Robert; LeCompte, Tom

2015-10-29

Computing plays an essential role in all aspects of high energy physics. As computational technology evolves rapidly in new directions, and data throughput and volume continue to follow a steep trend-line, it is important for the HEP community to develop an effective response to a series of expected challenges. In order to help shape the desired response, the HEP Forum for Computational Excellence (HEP-FCE) initiated a roadmap planning activity with two key overlapping drivers -- 1) software effectiveness, and 2) infrastructure and expertise advancement. The HEP-FCE formed three working groups, 1) Applications Software, 2) Software Libraries and Tools, and 3)more » Systems (including systems software), to provide an overview of the current status of HEP computing and to present findings and opportunities for the desired HEP computational roadmap. The final versions of the reports are combined in this document, and are presented along with introductory material.« less

GreenView and GreenLand Applications Development on SEE-GRID Infrastructure

NASA Astrophysics Data System (ADS)

Mihon, Danut; Bacu, Victor; Gorgan, Dorian; Mészáros, Róbert; Gelybó, Györgyi; Stefanut, Teodor

2010-05-01

The GreenView and GreenLand applications [1] have been developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) FP7 project co-funded by the European Commission [2]. The development of environment applications is a challenge for Grid technologies and software development methodologies. This presentation exemplifies the development of the GreenView and GreenLand applications over the SEE-GRID infrastructure by the Grid Application Development Methodology [3]. Today's environmental applications are used in vary domains of Earth Science such as meteorology, ground and atmospheric pollution, ground metal detection or weather prediction. These applications run on satellite images (e.g. Landsat, MERIS, MODIS, etc.) and the accuracy of output results depends mostly of the quality of these images. The main drawback of such environmental applications regards the need of computation power and storage power (some images are almost 1GB in size), in order to process such a large data volume. Actually, almost applications requiring high computation resources have approached the migration onto the Grid infrastructure. This infrastructure offers the computing power by running the atomic application components on different Grid nodes in sequential or parallel mode. The middleware used between the Grid infrastructure and client applications is ESIP (Environment Oriented Satellite Image Processing Platform), which is based on gProcess platform [4]. In its current format, gProcess is used for launching new processes on the Grid nodes, but also for monitoring the execution status of these processes. This presentation highlights two case studies of Grid based environmental applications, GreenView and GreenLand [5]. GreenView is used in correlation with MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images and meteorological datasets, in order to produce pseudo colored temperature and vegetation maps for different geographical CEE (Central Eastern Europe) regions. On the other hand, GreenLand is used for generating maps for different vegetation indexes (e.g. NDVI, EVI, SAVI, GEMI) based on Landsat satellite images. Both applications are using interpolation and random value generation algorithms, but also specific formulas for computing vegetation index values. The GreenView and GreenLand applications have been experimented over the SEE-GRID infrastructure and the performance evaluation is reported in [6]. The improvement of the execution time (obtained through a better parallelization of jobs), the extension of geographical areas to other parts of the Earth, and new user interaction techniques on spatial data and large set of satellite images are the goals of the future work. References [1] GreenView application on Wiki, http://wiki.egee-see.org/index.php/GreenView [2] SEE-GRID-SCI Project, http://www.see-grid-sci.eu/ [3] Gorgan D., Stefanut T., Bâcu V., Mihon D., Grid based Environment Application Development Methodology, SCICOM, 7th International Conference on "Large-Scale Scientific Computations", 4-8 June, 2009, Sozopol, Bulgaria, (To be published by Springer), (2009). [4] Gorgan D., Bacu V., Stefanut T., Rodila D., Mihon D., Grid based Satellite Image Processing Platform for Earth Observation Applications Development. IDAACS'2009 - IEEE Fifth International Workshop on "Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications", 21-23 September, Cosenza, Italy, IEEE Published in Computer Press, 247-252 (2009). [5] Mihon D., Bacu V., Stefanut T., Gorgan D., "Grid Based Environment Application Development - GreenView Application". ICCP2009 - IEEE 5th International Conference on Intelligent Computer Communication and Processing, 27 Aug, 2009 Cluj-Napoca. Published by IEEE Computer Press, pp. 275-282 (2009). [6] Danut Mihon, Victor Bacu, Dorian Gorgan, Róbert Mészáros, Györgyi Gelybó, Teodor Stefanut, Practical Considerations on the GreenView Application Development and Execution over SEE-GRID. SEE-GRID-SCI User Forum, 9-10 Dec 2009, Bogazici University, Istanbul, Turkey, ISBN: 978-975-403-510-0, pp. 167-175 (2009).

Flexible services for the support of research.

PubMed

Turilli, Matteo; Wallom, David; Williams, Chris; Gough, Steve; Curran, Neal; Tarrant, Richard; Bretherton, Dan; Powell, Andy; Johnson, Matt; Harmer, Terry; Wright, Peter; Gordon, John

2013-01-28

Cloud computing has been increasingly adopted by users and providers to promote a flexible, scalable and tailored access to computing resources. Nonetheless, the consolidation of this paradigm has uncovered some of its limitations. Initially devised by corporations with direct control over large amounts of computational resources, cloud computing is now being endorsed by organizations with limited resources or with a more articulated, less direct control over these resources. The challenge for these organizations is to leverage the benefits of cloud computing while dealing with limited and often widely distributed computing resources. This study focuses on the adoption of cloud computing by higher education institutions and addresses two main issues: flexible and on-demand access to a large amount of storage resources, and scalability across a heterogeneous set of cloud infrastructures. The proposed solutions leverage a federated approach to cloud resources in which users access multiple and largely independent cloud infrastructures through a highly customizable broker layer. This approach allows for a uniform authentication and authorization infrastructure, a fine-grained policy specification and the aggregation of accounting and monitoring. Within a loosely coupled federation of cloud infrastructures, users can access vast amount of data without copying them across cloud infrastructures and can scale their resource provisions when the local cloud resources become insufficient.

Vision for a 21st Century Information Infrastructure.

ERIC Educational Resources Information Center

Council on Competitiveness, Washington, DC.

In order to ensure that the United States maintains an advanced information infrastructure, the Council on Competitiveness has started a project on the 21st century infrastructure. Participating in this project are the many different parties who are providing and using the infrastructure, including cable companies, regional Bell companies, long…

Working Group on Virtual Data Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, D. N.; Palanisamy, G.; van Dam, K. K.

2016-02-04

This report is the outcome of a workshop commissioned by the U.S. Department of Energy’s (DOE) Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements foundational for achieving CESD scientific mission goals in advancing a robust, predictive understanding of Earth’s climate and environmental systems. Over the past several years, data volumes in CESD disciplines have risen sharply to unprecedented levels (tens of petabytes). Moreover, the complexity and diversity of this research data— including simulations, observations, and reanalysis— have grown significantly, posing new challenges for data capture, storage, verification, analysis, and integration. With the trends ofmore » increased data volume (in the hundreds of petabytes), more complex analysis processes, and growing cross-disciplinary collaborations, it is timely to investigate whether the CESD community has the computational and data support needed to fully realize the scientific potential of its data collections. In recognition of the challenges, a partnership is forming across CESD and among national and international agencies to examine the viability of creating an integrated, collaborative data infrastructure: a Virtual Laboratory. The overarching goal of this report is to identify the community’s key data technology requirements and high-priority development needs for sustaining and growing its scientific discovery potential. The report also aims to map these requirements to existing solutions and to identify gaps in current services, tools, and infrastructure that will need to be addressed in the short, medium, and long term to advance scientific progress.« less

Implementing Computer-Aided Instruction in Distance Education: An Infrastructure. RR/89-06.

ERIC Educational Resources Information Center

Kotze, Paula

The infrastructure required for the implementation of computer aided instruction is described with particular reference to the distance education environment at the University of South Africa. A review of the state of the art of online distance education in the United States and Europe is followed by an outline of the proposed infrastructure for…

A Primer on High-Throughput Computing for Genomic Selection

PubMed Central

Wu, Xiao-Lin; Beissinger, Timothy M.; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J. M.; Weigel, Kent A.; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized genetic gain). Eventually, HTC may change our view of data analysis as well as decision-making in the post-genomic era of selection programs in animals and plants, or in the study of complex diseases in humans. PMID:22303303

Enabling campus grids with open science grid technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weitzel, Derek; Bockelman, Brian; Swanson, David

2011-01-01

The Open Science Grid is a recognized key component of the US national cyber-infrastructure enabling scientific discovery through advanced high throughput computing. The principles and techniques that underlie the Open Science Grid can also be applied to Campus Grids since many of the requirements are the same, even if the implementation technologies differ. We find five requirements for a campus grid: trust relationships, job submission, resource independence, accounting, and data management. The Holland Computing Center's campus grid at the University of Nebraska-Lincoln was designed to fulfill the requirements of a campus grid. A bridging daemon was designed to bring non-Condormore » clusters into a grid managed by Condor. Condor features which make it possible to bridge Condor sites into a multi-campus grid have been exploited at the Holland Computing Center as well.« less

Forecasting techno-social systems: how physics and computing help to fight off global pandemics

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

2010-03-01

The crucial issue when planning for adequate public health interventions to mitigate the spread and impact of epidemics is risk evaluation and forecast. This amount to the anticipation of where, when and how strong the epidemic will strike. In the last decade advances in performance in computer technology, data acquisition, statistical physics and complex networks theory allow the generation of sophisticated simulations on supercomputer infrastructures to anticipate the spreading pattern of a pandemic. For the first time we are in the position of generating real time forecast of epidemic spreading. I will review the history of the current H1N1 pandemic, the major road-blocks the community has faced in its containment and mitigation and how physics and computing provide predictive tools that help us to battle epidemics.

Data Center Consolidation: A Step towards Infrastructure Clouds

NASA Astrophysics Data System (ADS)

Winter, Markus

Application service providers face enormous challenges and rising costs in managing and operating a growing number of heterogeneous system and computing landscapes. Limitations of traditional computing environments force IT decision-makers to reorganize computing resources within the data center, as continuous growth leads to an inefficient utilization of the underlying hardware infrastructure. This paper discusses a way for infrastructure providers to improve data center operations based on the findings of a case study on resource utilization of very large business applications and presents an outlook beyond server consolidation endeavors, transforming corporate data centers into compute clouds.

Elastic Cloud Computing Infrastructures in the Open Cirrus Testbed Implemented via Eucalyptus

NASA Astrophysics Data System (ADS)

Baun, Christian; Kunze, Marcel

Cloud computing realizes the advantages and overcomes some restrictionsof the grid computing paradigm. Elastic infrastructures can easily be createdand managed by cloud users. In order to accelerate the research ondata center management and cloud services the OpenCirrusTM researchtestbed has been started by HP, Intel and Yahoo!. Although commercialcloud offerings are proprietary, Open Source solutions exist in the field ofIaaS with Eucalyptus, PaaS with AppScale and at the applications layerwith Hadoop MapReduce. This paper examines the I/O performance ofcloud computing infrastructures implemented with Eucalyptus in contrastto Amazon S3.

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine.

PubMed

Kawamoto, Kensaku; Lobach, David F; Willard, Huntington F; Ginsburg, Geoffrey S

2009-03-23

In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.

Network and computing infrastructure for scientific applications in Georgia

NASA Astrophysics Data System (ADS)

Kvatadze, R.; Modebadze, Z.

2016-09-01

Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

Open Source Dataturbine (OSDT) Android Sensorpod in Environmental Observing Systems

NASA Astrophysics Data System (ADS)

Fountain, T. R.; Shin, P.; Tilak, S.; Trinh, T.; Smith, J.; Kram, S.

2014-12-01

The OSDT Android SensorPod is a custom-designed mobile computing platform for assembling wireless sensor networks for environmental monitoring applications. Funded by an award from the Gordon and Betty Moore Foundation, the OSDT SensorPod represents a significant technological advance in the application of mobile and cloud computing technologies to near-real-time applications in environmental science, natural resources management, and disaster response and recovery. It provides a modular architecture based on open standards and open-source software that allows system developers to align their projects with industry best practices and technology trends, while avoiding commercial vendor lock-in to expensive proprietary software and hardware systems. The integration of mobile and cloud-computing infrastructure represents a disruptive technology in the field of environmental science, since basic assumptions about technology requirements are now open to revision, e.g., the roles of special purpose data loggers and dedicated site infrastructure. The OSDT Android SensorPod was designed with these considerations in mind, and the resulting system exhibits the following characteristics - it is flexible, efficient and robust. The system was developed and tested in the three science applications: 1) a fresh water limnology deployment in Wisconsin, 2) a near coastal marine science deployment at the UCSD Scripps Pier, and 3) a terrestrial ecological deployment in the mountains of Taiwan. As part of a public education and outreach effort, a Facebook page with daily ocean pH measurements from the UCSD Scripps pier was developed. Wireless sensor networks and the virtualization of data and network services is the future of environmental science infrastructure. The OSDT Android SensorPod was designed and developed to harness these new technology developments for environmental monitoring applications.

Digital Rocks Portal: a Sustainable Platform for Data Management, Analysis and Remote Visualization of Volumetric Images of Porous Media

NASA Astrophysics Data System (ADS)

Prodanovic, M.; Esteva, M.; Ketcham, R. A.

2017-12-01

Nanometer to centimeter-scale imaging such as (focused ion beam) scattered electron microscopy, magnetic resonance imaging and X-ray (micro)tomography has since 1990s introduced 2D and 3D datasets of rock microstructure that allow investigation of nonlinear flow and mechanical phenomena on the length scales that are otherwise impervious to laboratory measurements. The numerical approaches that use such images produce various upscaled parameters required by subsurface flow and deformation simulators. All of this has revolutionized our knowledge about grain scale phenomena. However, a lack of data-sharing infrastructure among research groups makes it difficult to integrate different length scales. We have developed a sustainable, open and easy-to-use repository called the Digital Rocks Portal (https://www.digitalrocksportal.org), that (1) organizes images and related experimental measurements of different porous materials, (2) improves access to them for a wider community of engineering or geosciences researchers not necessarily trained in computer science or data analysis. Digital Rocks Portal (NSF EarthCube Grant 1541008) is the first repository for imaged porous microstructure data. It is implemented within the reliable, 24/7 maintained High Performance Computing Infrastructure supported by the Texas Advanced Computing Center (University of Texas at Austin). Long-term storage is provided through the University of Texas System Research Cyber-infrastructure initiative. We show how the data can be documented, referenced in publications via digital object identifiers (see Figure below for examples), visualized, searched for and linked to other repositories. We show recently implemented integration of the remote parallel visualization, bulk upload for large datasets as well as preliminary flow simulation workflow with the pore structures currently stored in the repository. We discuss the issues of collecting correct metadata, data discoverability and repository sustainability.

Evaluating Commercial and Private Cloud Services for Facility-Scale Geodetic Data Access, Analysis, and Services

NASA Astrophysics Data System (ADS)

Meertens, C. M.; Boler, F. M.; Ertz, D. J.; Mencin, D.; Phillips, D.; Baker, S.

2017-12-01

UNAVCO, in its role as a NSF facility for geodetic infrastructure and data, has succeeded for over two decades using on-premises infrastructure, and while the promise of cloud-based infrastructure is well-established, significant questions about suitability of such infrastructure for facility-scale services remain. Primarily through the GeoSciCloud award from NSF EarthCube, UNAVCO is investigating the costs, advantages, and disadvantages of providing its geodetic data and services in the cloud versus using UNAVCO's on-premises infrastructure. (IRIS is a collaborator on the project and is performing its own suite of investigations). In contrast to the 2-3 year time scale for the research cycle, the time scale of operation and planning for NSF facilities is for a minimum of five years and for some services extends to a decade or more. Planning for on-premises infrastructure is deliberate, and migrations typically take months to years to fully implement. Migrations to a cloud environment can only go forward with similar deliberate planning and understanding of all costs and benefits. The EarthCube GeoSciCloud project is intended to address the uncertainties of facility-level operations in the cloud. Investigations are being performed in a commercial cloud environment (Amazon AWS) during the first year of the project and in a private cloud environment (NSF XSEDE resource at the Texas Advanced Computing Center) during the second year. These investigations are expected to illuminate the potential as well as the limitations of running facility scale production services in the cloud. The work includes running parallel equivalent cloud-based services to on premises services and includes: data serving via ftp from a large data store, operation of a metadata database, production scale processing of multiple months of geodetic data, web services delivery of quality checked data and products, large-scale compute services for event post-processing, and serving real time data from a network of 700-plus GPS stations. The evaluation is based on a suite of metrics that we have developed to elucidate the effectiveness of cloud-based services in price, performance, and management. Services are currently running in AWS and evaluation is underway.

Design and deployment of hybrid-telemedicine applications

NASA Astrophysics Data System (ADS)

Ikhu-Omoregbe, N. A.; Atayero, A. A.; Ayo, C. K.; Olugbara, O. O.

2005-01-01

With advances and availability of information and communication technology infrastructures in some nations and institutions, patients are now able to receive healthcare services from doctors and healthcare centers even when they are physically separated. The availability and transfer of patient data which often include medical images for specialist opinion is invaluable both to the patient and the medical practitioner in a telemedicine session. Two existing approaches to telemedicine are real-time and stored-and-forward. The real-time requires the availability or development of video-conferencing infrastructures which are expensive especially for most developing nations of the world while stored-and-forward could allow data transmission between any hospital with computer and telephone by landline link which is less expensive but with delays. We therefore propose a hybrid design of applications using hypermedia database capable of harnessing the features of real-time and stored-and-forward deployed over a wireless Virtual Private Network for the participating centers and healthcare providers.

Towards a Multi-Mission, Airborne Science Data System Environment

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Hardman, S.; Law, E.; Freeborn, D.; Kay-Im, E.; Lau, G.; Oswald, J.

2011-12-01

NASA earth science instruments are increasingly relying on airborne missions. However, traditionally, there has been limited common infrastructure support available to principal investigators in the area of science data systems. As a result, each investigator has been required to develop their own computing infrastructures for the science data system. Typically there is little software reuse and many projects lack sufficient resources to provide a robust infrastructure to capture, process, distribute and archive the observations acquired from airborne flights. At NASA's Jet Propulsion Laboratory (JPL), we have been developing a multi-mission data system infrastructure for airborne instruments called the Airborne Cloud Computing Environment (ACCE). ACCE encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation. This includes improving data system interoperability across each instrument. A principal characteristic is being able to provide an agile infrastructure that is architected to allow for a variety of configurations of the infrastructure from locally installed compute and storage services to provisioning those services via the "cloud" from cloud computer vendors such as Amazon.com. Investigators often have different needs that require a flexible configuration. The data system infrastructure is built on the Apache's Object Oriented Data Technology (OODT) suite of components which has been used for a number of spaceborne missions and provides a rich set of open source software components and services for constructing science processing and data management systems. In 2010, a partnership was formed between the ACCE team and the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to support the data processing and data management needs. A principal goal is to provide support for the Fourier Transform Spectrometer (FTS) instrument which will produce over 700,000 soundings over the life of their three-year mission. The cost to purchase and operate a cluster-based system in order to generate Level 2 Full Physics products from this data was prohibitive. Through an evaluation of cloud computing solutions, Amazon's Elastic Compute Cloud (EC2) was selected for the CARVE deployment. As the ACCE infrastructure is developed and extended to form an infrastructure for airborne missions, the experience of working with CARVE has provided a number of lessons learned and has proven to be important in reinforcing the unique aspects of airborne missions and the importance of the ACCE infrastructure in developing a cost effective, flexible multi-mission capability that leverages emerging capabilities in cloud computing, workflow management, and distributed computing.

EMHP: an accurate automated hole masking algorithm for single-particle cryo-EM image processing.

PubMed

Berndsen, Zachary; Bowman, Charles; Jang, Haerin; Ward, Andrew B

2017-12-01

The Electron Microscopy Hole Punch (EMHP) is a streamlined suite of tools for quick assessment, sorting and hole masking of electron micrographs. With recent advances in single-particle electron cryo-microscopy (cryo-EM) data processing allowing for the rapid determination of protein structures using a smaller computational footprint, we saw the need for a fast and simple tool for data pre-processing that could run independent of existing high-performance computing (HPC) infrastructures. EMHP provides a data preprocessing platform in a small package that requires minimal python dependencies to function. https://www.bitbucket.org/chazbot/emhp Apache 2.0 License. bowman@scripps.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research.

PubMed

Eppig, Janan T; Smith, Cynthia L; Blake, Judith A; Ringwald, Martin; Kadin, James A; Richardson, Joel E; Bult, Carol J

2017-01-01

The Mouse Genome Informatics (MGI), resource ( www.informatics.jax.org ) has existed for over 25 years, and over this time its data content, informatics infrastructure, and user interfaces and tools have undergone dramatic changes (Eppig et al., Mamm Genome 26:272-284, 2015). Change has been driven by scientific methodological advances, rapid improvements in computational software, growth in computer hardware capacity, and the ongoing collaborative nature of the mouse genomics community in building resources and sharing data. Here we present an overview of the current data content of MGI, describe its general organization, and provide examples using simple and complex searches, and tools for mining and retrieving sets of data.

Machine learning for Big Data analytics in plants.

PubMed

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

Atlas2 Cloud: a framework for personal genome analysis in the cloud

PubMed Central

2012-01-01

Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663

Atlas2 Cloud: a framework for personal genome analysis in the cloud.

PubMed

Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli

2012-01-01

Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

Modeling the Cloud to Enhance Capabilities for Crises and Catastrophe Management

DTIC Science & Technology

2016-11-16

order for cloud computing infrastructures to be successfully deployed in real world scenarios as tools for crisis and catastrophe management, where...Statement of the Problem Studied As cloud computing becomes the dominant computational infrastructure[1] and cloud technologies make a transition to hosting...1. Formulate rigorous mathematical models representing technological capabilities and resources in cloud computing for performance modeling and

SCinet Architecture: Featured at the International Conference for High Performance Computing,Networking, Storage and Analysis 2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyonnais, Marc; Smith, Matt; Mace, Kate P.

SCinet is the purpose-built network that operates during the International Conference for High Performance Computing,Networking, Storage and Analysis (Super Computing or SC). Created each year for the conference, SCinet brings to life a high-capacity network that supports applications and experiments that are a hallmark of the SC conference. The network links the convention center to research and commercial networks around the world. This resource serves as a platform for exhibitors to demonstrate the advanced computing resources of their home institutions and elsewhere by supporting a wide variety of applications. Volunteers from academia, government and industry work together to design andmore » deliver the SCinet infrastructure. Industry vendors and carriers donate millions of dollars in equipment and services needed to build and support the local and wide area networks. Planning begins more than a year in advance of each SC conference and culminates in a high intensity installation in the days leading up to the conference. The SCinet architecture for SC16 illustrates a dramatic increase in participation from the vendor community, particularly those that focus on network equipment. Software-Defined Networking (SDN) and Data Center Networking (DCN) are present in nearly all aspects of the design.« less

A smarter way to search, share and utilize open-spatial online data for energy R&D - Custom machine learning and GIS tools in U.S. DOE's virtual data library & laboratory, EDX

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J.; Baker, D.; Barkhurst, A.; Bean, A.; DiGiulio, J.; Jones, K.; Jones, T.; Justman, D.; Miller, R., III; Romeo, L.; Sabbatino, M.; Tong, A.

2017-12-01

As spatial datasets are increasingly accessible through open, online systems, the opportunity to use these resources to address a range of Earth system questions grows. Simultaneously, there is a need for better infrastructure and tools to find and utilize these resources. We will present examples of advanced online computing capabilities, hosted in the U.S. DOE's Energy Data eXchange (EDX), that address these needs for earth-energy research and development. In one study the computing team developed a custom, machine learning, big data computing tool designed to parse the web and return priority datasets to appropriate servers to develop an open-source global oil and gas infrastructure database. The results of this spatial smart search approach were validated against expert-driven, manual search results which required a team of seven spatial scientists three months to produce. The custom machine learning tool parsed online, open systems, including zip files, ftp sites and other web-hosted resources, in a matter of days. The resulting resources were integrated into a geodatabase now hosted for open access via EDX. Beyond identifying and accessing authoritative, open spatial data resources, there is also a need for more efficient tools to ingest, perform, and visualize multi-variate, spatial data analyses. Within the EDX framework, there is a growing suite of processing, analytical and visualization capabilities that allow multi-user teams to work more efficiently in private, virtual workspaces. An example of these capabilities are a set of 5 custom spatio-temporal models and data tools that form NETL's Offshore Risk Modeling suite that can be used to quantify oil spill risks and impacts. Coupling the data and advanced functions from EDX with these advanced spatio-temporal models has culminated with an integrated web-based decision-support tool. This platform has capabilities to identify and combine data across scales and disciplines, evaluate potential environmental, social, and economic impacts, highlight knowledge or technology gaps, and reduce uncertainty for a range of `what if' scenarios relevant to oil spill prevention efforts. These examples illustrate EDX's growing capabilities for advanced spatial data search and analysis to support geo-data science needs.

Cloud Infrastructure & Applications - CloudIA

NASA Astrophysics Data System (ADS)

Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

Advanced operations focused on connected vehicles/infrastructure (CVI-UTC).

DOT National Transportation Integrated Search

2015-12-01

The goal of the Infrastructure Safety Assessment in a Connected Vehicle (CV) Environment : project was to develop a method to identify infrastructure safety hot spots using CV data. : Using these basic safety messages to detect hot spots may al...

SpaceWire- Based Control System Architecture for the Lightweight Advanced Robotic Arm Demonstrator [LARAD

NASA Astrophysics Data System (ADS)

Rucinski, Marek; Coates, Adam; Montano, Giuseppe; Allouis, Elie; Jameux, David

2015-09-01

The Lightweight Advanced Robotic Arm Demonstrator (LARAD) is a state-of-the-art, two-meter long robotic arm for planetary surface exploration currently being developed by a UK consortium led by Airbus Defence and Space Ltd under contract to the UK Space Agency (CREST-2 programme). LARAD has a modular design, which allows for experimentation with different electronics and control software. The control system architecture includes the on-board computer, control software and firmware, and the communication infrastructure (e.g. data links, switches) connecting on-board computer(s), sensors, actuators and the end-effector. The purpose of the control system is to operate the arm according to pre-defined performance requirements, monitoring its behaviour in real-time and performing safing/recovery actions in case of faults. This paper reports on the results of a recent study about the feasibility of the development and integration of a novel control system architecture for LARAD fully based on the SpaceWire protocol. The current control system architecture is based on the combination of two communication protocols, Ethernet and CAN. The new SpaceWire-based control system will allow for improved monitoring and telecommanding performance thanks to higher communication data rate, allowing for the adoption of advanced control schemes, potentially based on multiple vision sensors, and for the handling of sophisticated end-effectors that require fine control, such as science payloads or robotic hands.

A cyber infrastructure for the SKA Telescope Manager

NASA Astrophysics Data System (ADS)

Barbosa, Domingos; Barraca, João. P.; Carvalho, Bruno; Maia, Dalmiro; Gupta, Yashwant; Natarajan, Swaminathan; Le Roux, Gerhard; Swart, Paul

2016-07-01

The Square Kilometre Array Telescope Manager (SKA TM) will be responsible for assisting the SKA Operations and Observation Management, carrying out System diagnosis and collecting Monitoring and Control data from the SKA subsystems and components. To provide adequate compute resources, scalability, operation continuity and high availability, as well as strict Quality of Service, the TM cyber-infrastructure (embodied in the Local Infrastructure - LINFRA) consists of COTS hardware and infrastructural software (for example: server monitoring software, host operating system, virtualization software, device firmware), providing a specially tailored Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) solution. The TM infrastructure provides services in the form of computational power, software defined networking, power, storage abstractions, and high level, state of the art IaaS and PaaS management interfaces. This cyber platform will be tailored to each of the two SKA Phase 1 telescopes (SKA_MID in South Africa and SKA_LOW in Australia) instances, each presenting different computational and storage infrastructures and conditioned by location. This cyber platform will provide a compute model enabling TM to manage the deployment and execution of its multiple components (observation scheduler, proposal submission tools, MandC components, Forensic tools and several Databases, etc). In this sense, the TM LINFRA is primarily focused towards the provision of isolated instances, mostly resorting to virtualization technologies, while defaulting to bare hardware if specifically required due to performance, security, availability, or other requirement.

Advanced European Network of E-Infrastructures for Astronomy with the SKA

NASA Astrophysics Data System (ADS)

Massardi, Marcella

2017-11-01

Here, I present the AENEAS (Advanced European Network of E-infrastructures for Astronomy with the SKA) project has been funded in the Horizon 2020 Work Programme call "Research and Innovation Actions for International Co-operation on high-end e-infrastructure requirements" supporting the Square Kilometre Array (SKA). INAF is contributing to all the AENEAS working packages and leading the WP5 - Access and Knowledge Creation (WP leader M. Massardi IRA-ARC), participants from IRA (Brand, Nanni, Venturi) ,OACT(Becciani, Costa, Umana), OATS (Smareglia, Knapic, Taffoni)

Operational flood control of a low-lying delta system using large time step Model Predictive Control

NASA Astrophysics Data System (ADS)

Tian, Xin; van Overloop, Peter-Jules; Negenborn, Rudy R.; van de Giesen, Nick

2015-01-01

The safety of low-lying deltas is threatened not only by riverine flooding but by storm-induced coastal flooding as well. For the purpose of flood control, these deltas are mostly protected in a man-made environment, where dikes, dams and other adjustable infrastructures, such as gates, barriers and pumps are widely constructed. Instead of always reinforcing and heightening these structures, it is worth considering making the most of the existing infrastructure to reduce the damage and manage the delta in an operational and overall way. In this study, an advanced real-time control approach, Model Predictive Control, is proposed to operate these structures in the Dutch delta system (the Rhine-Meuse delta). The application covers non-linearity in the dynamic behavior of the water system and the structures. To deal with the non-linearity, a linearization scheme is applied which directly uses the gate height instead of the structure flow as the control variable. Given the fact that MPC needs to compute control actions in real-time, we address issues regarding computational time. A new large time step scheme is proposed in order to save computation time, in which different control variables can have different control time steps. Simulation experiments demonstrate that Model Predictive Control with the large time step setting is able to control a delta system better and much more efficiently than the conventional operational schemes.

A new vision of the post-NIST civil infrastructure program: the challenges of next-generation construction materials and processes

NASA Astrophysics Data System (ADS)

Wu, H. Felix; Wan, Yan

2014-03-01

Our nation's infrastructural systems are crumbling. The deteriorating process grows over time. The physical aging of these vital facilities and the remediation of their current critical state pose a key societal challenge to the United States. Current sensing technologies, while well developed in controlled laboratory environments, have not yet yielded tools for producing real-time, in-situ data that are adequately comprehensible for infrastructure decision-makers. The need for advanced sensing technologies is national because every municipality and state in the nation faces infrastructure management challenges. The need is critical because portions of infrastructure are reaching the end of their life-spans and there are few cost-effective means to monitor infrastructure integrity and to prioritize the renovation and replacement of infrastructure elements. New advanced sensing technologies that produce cost-effective inspection and real-time monitoring data, and that can also help or aid in meaningful interpretation of the acquired data, therefore will enhance the safety in regard to the public on structural integrity by issuing timely and accurate alert data for effective maintenance to avoid disasters happening. New advanced sensing technologies also allow more informed management of infrastructural investments by avoiding premature replacement of infrastructure and identifying those structures in need of immediate action to prevent from catastrophic failure. Infrastructure management requires that once a structural defect is detected, an economical and efficient repair be made. Advancing the technologies of repairing infrastructure elements in contact with water, road salt, and subjected to thermal changes requires innovative research to significantly extend the service life of repairs, lower the costs of repairs, and provide repair technologies that are suitable for a wide range of conditions. All these new technologies will provide increased lifetimes, security, and safety of elements of critical infrastructure for the Nation's already deteriorating civil infrastructure. It is envisioned that the Nation should look far beyond: not only should we efficiently and effectively address current problems of the aging infrastructure, but we must also further develop next-generation construction materials and processes for new construction. To accomplish this ambitious goal, we must include process efficiency that will help select the most reliable and cost-effective materials in construction processes; performance and cost will be the prime consideration for selections construction materials based on life-cycle cost and materials performance; energy efficiency will drive reduced energy consumption from current levels by 50 % per unit of output; and environmental responsiveness will achieve net-zero waste from construction materials and its constituents. Should it be successfully implemented, we will transform the current 21st century infrastructure systems to enable the vital functioning of society and improve competitiveness of the economy to ensure that our quality of life remains high.

Future Naval Use of COTS Networking Infrastructure

DTIC Science & Technology

2009-07-01

user to benefit from Google’s vast databases and computational resources. Obviously, the ability to harness the full power of the Cloud could be... Computing Impact Findings Action Items Take-Aways Appendices: Pages 54-68 A. Terms of Reference Document B. Sample Definitions of Cloud ...and definition of Cloud Computing . While Cloud Computing is developing in many variations – including Infrastructure as a Service (IaaS), Platform as

A Taxonomy on Accountability and Privacy Issues in Smart Grids

NASA Astrophysics Data System (ADS)

Naik, Ameya; Shahnasser, Hamid

2017-07-01

Cyber-Physical Systems (CPS) are combinations of computation, networking, and physical processes. Embedded computers and networks monitor control the physical processes, which affect computations and vice versa. Two applications of cyber physical systems include health-care and smart grid. In this paper, we have considered privacy aspects of cyber-physical system applicable to smart grid. Smart grid in collaboration with different stockholders can help in the improvement of power generation, communication, circulation and consumption. The proper management with monitoring feature by customers and utility of energy usage can be done through proper transmission and electricity flow; however cyber vulnerability could be increased due to an increased assimilation and linkage. This paper discusses various frameworks and architectures proposed for achieving accountability in smart grids by addressing privacy issues in Advance Metering Infrastructure (AMI). This paper also highlights additional work needed for accountability in more precise specifications such as uncertainty or ambiguity, indistinct, unmanageability, and undetectably.

The QUANTGRID Project (RO)—Quantum Security in GRID Computing Applications

NASA Astrophysics Data System (ADS)

Dima, M.; Dulea, M.; Petre, M.; Petre, C.; Mitrica, B.; Stoica, M.; Udrea, M.; Sterian, R.; Sterian, P.

2010-01-01

The QUANTGRID Project, financed through the National Center for Programme Management (CNMP-Romania), is the first attempt at using Quantum Crypted Communications (QCC) in large scale operations, such as GRID Computing, and conceivably in the years ahead in the banking sector and other security tight communications. In relation with the GRID activities of the Center for Computing & Communications (Nat.'l Inst. Nucl. Phys.—IFIN-HH), the Quantum Optics Lab. (Nat.'l Inst. Plasma and Lasers—INFLPR) and the Physics Dept. (University Polytechnica—UPB) the project will build a demonstrator infrastructure for this technology. The status of the project in its incipient phase is reported, featuring tests for communications in classical security mode: socket level communications under AES (Advanced Encryption Std.), both proprietary code in C++ technology. An outline of the planned undertaking of the project is communicated, highlighting its impact in quantum physics, coherent optics and information technology.

Personal Computer-less (PC-less) Microcontroller Training Kit

NASA Astrophysics Data System (ADS)

Somantri, Y.; Wahyudin, D.; Fushilat, I.

2018-02-01

The need of microcontroller training kit is necessary for practical work of students of electrical engineering education. However, to use available training kit not only costly but also does not meet the need of laboratory requirements. An affordable and portable microcontroller kit could answer such problem. This paper explains the design and development of Personal Computer Less (PC-Less) Microcontroller Training Kit. It was developed based on Lattepanda processor and Arduino microcontroller as target. The training kit equipped with advanced input-output interfaces that adopted the concept of low cost and low power system. The preliminary usability testing proved this device can be used as a tool for microcontroller programming and industrial automation training. By adopting the concept of portability, the device could be operated in the rural area which electricity and computer infrastructure are limited. Furthermore, the training kit is suitable for student of electrical engineering student from university and vocational high school.

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

The inhabited environment, infrastructure development and advanced urbanization in China’s Yangtze River Delta Region

NASA Astrophysics Data System (ADS)

Zhu, Xiaoqing; Gao, Weijun; Zhou, Nan; Kammen, Daniel M.; Wu, Yiqun; Zhang, Yao; Chen, Wei

2016-12-01

This paper analyzes the relationship among the inhabited environment, infrastructure development and environmental impacts in China’s heavily urbanized Yangtze River Delta region. Using primary human environment data for the period 2006-2014, we examine factors affecting the inhabited environment and infrastructure development: urban population, GDP, built-up area, energy consumption, waste emission, transportation, real estate and urban greenery. Then we empirically investigate the impact of advanced urbanization with consideration of cities’ differences. Results from this study show that the growth rate of the inhabited environment and infrastructure development is strongly influenced by regional development structure, functional orientations, traffic network and urban size and form. The effect of advanced urbanization is more significant in large and mid-size cities than huge and mega cities. Energy consumption, waste emission and real estate in large and mid-size cities developed at an unprecedented rate with the rapid increase of economy. However, urban development of huge and mega cities gradually tended to be saturated. The transition development in these cities improved the inhabited environment and ecological protection instead of the urban construction simply. To maintain a sustainable advanced urbanization process, policy implications included urban sprawl control polices, ecological development mechanisms and reforming the economic structure for huge and mega cities, and construct major cross-regional infrastructure, enhance the carrying capacity and improvement of energy efficiency and structure for large and mid-size cities.

Advances in engineering nanometrology at the National Physical Laboratory

NASA Astrophysics Data System (ADS)

Leach, Richard K.; Claverley, James; Giusca, Claudiu; Jones, Christopher W.; Nimishakavi, Lakshmi; Sun, Wenjuan; Tedaldi, Matthew; Yacoot, Andrew

2012-07-01

The National Physical Laboratory, UK, has been active in the field of engineering nanometrology for a number of years. A summary of progress over the last five years is presented in this paper and the following research projects discussed in detail. (1) Development of an infrastructure for the calibration of instruments for measuring areal surface topography, along with the development of areal software measurement standards. This work comprises the use of the optical transfer function and a technique for the simultaneous measurement of topography and the phase change on reflection, allowing composite materials to be measured. (2) Development of a vibrating micro-CMM probe with isotropic probing reaction and the ability to operate in a non-contact mode. (3) A review of x-ray computed tomography and its use in dimensional metrology. (4) The further development of a metrology infrastructure for atomic force microscopy and the development of an instrument for the measurement of the effect of the probe-surface interaction. (5) Traceable measurement of displacement using optical and x-ray interferometry to picometre accuracy. (6) Development of an infrastructure for low-force metrology, including the development of appropriate transfer artefacts.

Validation of Storm Water Management Model Storm Control Measures Modules

NASA Astrophysics Data System (ADS)

Simon, M. A.; Platz, M. C.

2017-12-01

EPA's Storm Water Management Model (SWMM) is a computational code heavily relied upon by industry for the simulation of wastewater and stormwater infrastructure performance. Many municipalities are relying on SWMM results to design multi-billion-dollar, multi-decade infrastructure upgrades. Since the 1970's, EPA and others have developed five major releases, the most recent ones containing storm control measures modules for green infrastructure. The main objective of this study was to quantify the accuracy with which SWMM v5.1.10 simulates the hydrologic activity of previously monitored low impact developments. Model performance was evaluated with a mathematical comparison of outflow hydrographs and total outflow volumes, using empirical data and a multi-event, multi-objective calibration method. The calibration methodology utilized PEST++ Version 3, a parameter estimation tool, which aided in the selection of unmeasured hydrologic parameters. From the validation study and sensitivity analysis, several model improvements were identified to advance SWMM LID Module performance for permeable pavements, infiltration units and green roofs, and these were performed and reported herein. Overall, it was determined that SWMM can successfully simulate low impact development controls given accurate model confirmation, parameter measurement, and model calibration.

The GMOS cyber(e)-infrastructure: advanced services for supporting science and policy.

PubMed

Cinnirella, S; D'Amore, F; Bencardino, M; Sprovieri, F; Pirrone, N

2014-03-01

The need for coordinated, systematized and catalogued databases on mercury in the environment is of paramount importance as improved information can help the assessment of the effectiveness of measures established to phase out and ban mercury. Long-term monitoring sites have been established in a number of regions and countries for the measurement of mercury in ambient air and wet deposition. Long term measurements of mercury concentration in biota also produced a huge amount of information, but such initiatives are far from being within a global, systematic and interoperable approach. To address these weaknesses the on-going Global Mercury Observation System (GMOS) project ( www.gmos.eu ) established a coordinated global observation system for mercury as well it retrieved historical data ( www.gmos.eu/sdi ). To manage such large amount of information a technological infrastructure was planned. This high-performance back-end resource associated with sophisticated client applications enables data storage, computing services, telecommunications networks and all services necessary to support the activity. This paper reports the architecture definition of the GMOS Cyber(e)-Infrastructure and the services developed to support science and policy, including the United Nation Environmental Program. It finally describes new possibilities in data analysis and data management through client applications.

Digital pathology in nephrology clinical trials, research, and pathology practice.

PubMed

Barisoni, Laura; Hodgin, Jeffrey B

2017-11-01

In this review, we will discuss (i) how the recent advancements in digital technology and computational engineering are currently applied to nephropathology in the setting of clinical research, trials, and practice; (ii) the benefits of the new digital environment; (iii) how recognizing its challenges provides opportunities for transformation; and (iv) nephropathology in the upcoming era of kidney precision and predictive medicine. Recent studies highlighted how new standardized protocols facilitate the harmonization of digital pathology database infrastructure and morphologic, morphometric, and computer-aided quantitative analyses. Digital pathology enables robust protocols for clinical trials and research, with the potential to identify previously underused or unrecognized clinically useful parameters. The integration of digital pathology with molecular signatures is leading the way to establishing clinically relevant morpho-omic taxonomies of renal diseases. The introduction of digital pathology in clinical research and trials, and the progressive implementation of the modern software ecosystem, opens opportunities for the development of new predictive diagnostic paradigms and computer-aided algorithms, transforming the practice of renal disease into a modern computational science.

EV Charging Infrastructure Roadmap

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karner, Donald; Garetson, Thomas; Francfort, Jim

2016-08-01

As highlighted in the U.S. Department of Energy’s EV Everywhere Grand Challenge, vehicle technology is advancing toward an objective to “… produce plug-in electric vehicles that are as affordable and convenient for the average American family as today’s gasoline-powered vehicles …” [1] by developing more efficient drivetrains, greater battery energy storage per dollar, and lighter-weight vehicle components and construction. With this technology advancement and improved vehicle performance, the objective for charging infrastructure is to promote vehicle adoption and maximize the number of electric miles driven. The EV Everywhere Charging Infrastructure Roadmap (hereafter referred to as Roadmap) looks forward and assumesmore » that the technical challenges and vehicle performance improvements set forth in the EV Everywhere Grand Challenge will be met. The Roadmap identifies and prioritizes deployment of charging infrastructure in support of this charging infrastructure objective for the EV Everywhere Grand Challenge« less

Consolidation and development roadmap of the EMI middleware

NASA Astrophysics Data System (ADS)

Kónya, B.; Aiftimiei, C.; Cecchi, M.; Field, L.; Fuhrmann, P.; Nilsen, J. K.; White, J.

2012-12-01

Scientific research communities have benefited recently from the increasing availability of computing and data infrastructures with unprecedented capabilities for large scale distributed initiatives. These infrastructures are largely defined and enabled by the middleware they deploy. One of the major issues in the current usage of research infrastructures is the need to use similar but often incompatible middleware solutions. The European Middleware Initiative (EMI) is a collaboration of the major European middleware providers ARC, dCache, gLite and UNICORE. EMI aims to: deliver a consolidated set of middleware components for deployment in EGI, PRACE and other Distributed Computing Infrastructures; extend the interoperability between grids and other computing infrastructures; strengthen the reliability of the services; establish a sustainable model to maintain and evolve the middleware; fulfil the requirements of the user communities. This paper presents the consolidation and development objectives of the EMI software stack covering the last two years. The EMI development roadmap is introduced along the four technical areas of compute, data, security and infrastructure. The compute area plan focuses on consolidation of standards and agreements through a unified interface for job submission and management, a common format for accounting, the wide adoption of GLUE schema version 2.0 and the provision of a common framework for the execution of parallel jobs. The security area is working towards a unified security model and lowering the barriers to Grid usage by allowing users to gain access with their own credentials. The data area is focusing on implementing standards to ensure interoperability with other grids and industry components and to reuse already existing clients in operating systems and open source distributions. One of the highlights of the infrastructure area is the consolidation of the information system services via the creation of a common information backbone.

Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Characterization of attacks on public telephone networks

NASA Astrophysics Data System (ADS)

Lorenz, Gary V.; Manes, Gavin W.; Hale, John C.; Marks, Donald; Davis, Kenneth; Shenoi, Sujeet

2001-02-01

The U.S. Public Telephone Network (PTN) is a massively connected distributed information systems, much like the Internet. PTN signaling, transmission and operations functions must be protected from physical and cyber attacks to ensure the reliable delivery of telecommunications services. The increasing convergence of PTNs with wireless communications systems, computer networks and the Internet itself poses serious threats to our nation's telecommunications infrastructure. Legacy technologies and advanced services encumber well-known and as of yet undiscovered vulnerabilities that render them susceptible to cyber attacks. This paper presents a taxonomy of cyber attacks on PTNs in converged environments that synthesizes exploits in computer and communications network domains. The taxonomy provides an opportunity for the systematic exploration of mitigative and preventive strategies, as well as for the identification and classification of emerging threats.

Minimizing Overhead for Secure Computation and Fully Homomorphic Encryption: Overhead

DTIC Science & Technology

2015-11-01

many inputs. We also improved our compiler infrastructure to handle very large circuits in a more scalable way. In Jan’13, we employed the AESNI and...Amazon’s elastic compute infrastructure , and is running under a Xen hypervisor. Since we do not have direct access to the bare metal, we cannot...creating novel opportunities for compressing au- thentication overhead. It is especially compelling that existing public key infrastructures can be used

Mobility management techniques for the next-generation wireless networks

NASA Astrophysics Data System (ADS)

Sun, Junzhao; Howie, Douglas P.; Sauvola, Jaakko J.

2001-10-01

The tremendous demands from social market are pushing the booming development of mobile communications faster than ever before, leading to plenty of new advanced techniques emerging. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Mobility management is an important issue in the area of mobile communications, which can be best solved at the network layer. One of the key features of the next generation wireless networks is all-IP infrastructure. This paper discusses the mobility management schemes for the next generation mobile networks through extending IP's functions with mobility support. A global hierarchical framework model for the mobility management of wireless networks is presented, in which the mobility management is divided into two complementary tasks: macro mobility and micro mobility. As the macro mobility solution, a basic principle of Mobile IP is introduced, together with the optimal schemes and the advances in IPv6. The disadvantages of the Mobile IP on solving the micro mobility problem are analyzed, on the basis of which three main proposals are discussed as the micro mobility solutions for mobile communications, including Hierarchical Mobile IP (HMIP), Cellular IP, and Handoff-Aware Wireless Access Internet Infrastructure (HAWAII). A unified model is also described in which the different micro mobility solutions can coexist simultaneously in mobile networks.

Primer to Design Safe School Projects in Case of Terrorist Attacks and School Shootings. Buildings and Infrastructure Protection Series. FEMA-428/BIPS-07/January 2012. Edition 2

ERIC Educational Resources Information Center

Chipley, Michael; Lyon, Wesley; Smilowitz, Robert; Williams, Pax; Arnold, Christopher; Blewett, William; Hazen, Lee; Krimgold, Fred

2012-01-01

This publication, part of the new Building and Infrastructure Protection Series (BIPS) published by the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) Infrastructure Protection and Disaster Management Division (IDD), serves to advance high performance and integrated design for buildings and infrastructure. This…

[Design and study of parallel computing environment of Monte Carlo simulation for particle therapy planning using a public cloud-computing infrastructure].

PubMed

Yokohama, Noriya

2013-07-01

This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost.

75 FR 70899 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-19

... submit to the Office of Management and Budget (OMB) for clearance the following proposal for collection... Annual Burden Hours: 2,952. Public Computer Center Reports (Quarterly and Annually) Number of Respondents... specific to Infrastructure and Comprehensive Community Infrastructure, Public Computer Center, and...

From computer-assisted intervention research to clinical impact: The need for a holistic approach.

PubMed

Ourselin, Sébastien; Emberton, Mark; Vercauteren, Tom

2016-10-01

The early days of the field of medical image computing (MIC) and computer-assisted intervention (CAI), when publishing a strong self-contained methodological algorithm was enough to produce impact, are over. As a community, we now have substantial responsibility to translate our scientific progresses into improved patient care. In the field of computer-assisted interventions, the emphasis is also shifting from the mere use of well-known established imaging modalities and position trackers to the design and combination of innovative sensing, elaborate computational models and fine-grained clinical workflow analysis to create devices with unprecedented capabilities. The barriers to translating such devices in the complex and understandably heavily regulated surgical and interventional environment can seem daunting. Whether we leave the translation task mostly to our industrial partners or welcome, as researchers, an important share of it is up to us. We argue that embracing the complexity of surgical and interventional sciences is mandatory to the evolution of the field. Being able to do so requires large-scale infrastructure and a critical mass of expertise that very few research centres have. In this paper, we emphasise the need for a holistic approach to computer-assisted interventions where clinical, scientific, engineering and regulatory expertise are combined as a means of moving towards clinical impact. To ensure that the breadth of infrastructure and expertise required for translational computer-assisted intervention research does not lead to a situation where the field advances only thanks to a handful of exceptionally large research centres, we also advocate that solutions need to be designed to lower the barriers to entry. Inspired by fields such as particle physics and astronomy, we claim that centralised very large innovation centres with state of the art technology and health technology assessment capabilities backed by core support staff and open interoperability standards need to be accessible to the wider computer-assisted intervention research community. Copyright © 2016. Published by Elsevier B.V.

A characterization of workflow management systems for extreme-scale applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

A characterization of workflow management systems for extreme-scale applications

DOE PAGES

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...

2017-02-16

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

A modified eco-efficiency framework and methodology for advancing the state of practice of sustainability analysis as applied to green infrastructure

EPA Science Inventory

We propose a modified eco-efficiency (EE) framework and novel sustainability analysis methodology for green infrastructure (GI) practices used in water resource management. Green infrastructure practices such as rainwater harvesting (RWH), rain gardens, porous pavements, and gree...

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

DOE PAGES

Rao, Nageswara S. V.; Poole, Stephen W.; Ma, Chris Y. T.; ...

2015-04-06

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical sub-infrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein theirmore » components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. In conclusion, the analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures.« less

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S. V.; Poole, Stephen W.; Ma, Chris Y. T.

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical sub-infrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein theirmore » components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. In conclusion, the analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures.« less

SCIENCE BRIEF: ADVANCED CONCEPTS

EPA Science Inventory

Research on advanced concepts will evaluate and demonstrate the application of innovative infrastructure designs, management procedures and operational approaches. Advanced concepts go beyond simple asset management. The infusion of these advanced concepts into established wastew...

Image-Based Predictive Modeling of Heart Mechanics.

PubMed

Wang, V Y; Nielsen, P M F; Nash, M P

2015-01-01

Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation.

New security infrastructure model for distributed computing systems

NASA Astrophysics Data System (ADS)

Dubenskaya, J.; Kryukov, A.; Demichev, A.; Prikhodko, N.

2016-02-01

At the paper we propose a new approach to setting up a user-friendly and yet secure authentication and authorization procedure in a distributed computing system. The security concept of the most heterogeneous distributed computing systems is based on the public key infrastructure along with proxy certificates which are used for rights delegation. In practice a contradiction between the limited lifetime of the proxy certificates and the unpredictable time of the request processing is a big issue for the end users of the system. We propose to use unlimited in time hashes which are individual for each request instead of proxy certificate. Our approach allows to avoid using of the proxy certificates. Thus the security infrastructure of distributed computing system becomes easier for development, support and use.

TerraFERMA: The Transparent Finite Element Rapid Model Assembler for multiphysics problems in Earth sciences

NASA Astrophysics Data System (ADS)

Wilson, Cian R.; Spiegelman, Marc; van Keken, Peter E.

2017-02-01

We introduce and describe a new software infrastructure TerraFERMA, the Transparent Finite Element Rapid Model Assembler, for the rapid and reproducible description and solution of coupled multiphysics problems. The design of TerraFERMA is driven by two computational needs in Earth sciences. The first is the need for increased flexibility in both problem description and solution strategies for coupled problems where small changes in model assumptions can lead to dramatic changes in physical behavior. The second is the need for software and models that are more transparent so that results can be verified, reproduced, and modified in a manner such that the best ideas in computation and Earth science can be more easily shared and reused. TerraFERMA leverages three advanced open-source libraries for scientific computation that provide high-level problem description (FEniCS), composable solvers for coupled multiphysics problems (PETSc), and an options handling system (SPuD) that allows the hierarchical management of all model options. TerraFERMA integrates these libraries into an interface that organizes the scientific and computational choices required in a model into a single options file from which a custom compiled application is generated and run. Because all models share the same infrastructure, models become more reusable and reproducible, while still permitting the individual researcher considerable latitude in model construction. TerraFERMA solves partial differential equations using the finite element method. It is particularly well suited for nonlinear problems with complex coupling between components. TerraFERMA is open-source and available at http://terraferma.github.io, which includes links to documentation and example input files.

A Scalable, Out-of-Band Diagnostics Architecture for International Space Station Systems Support

NASA Technical Reports Server (NTRS)

Fletcher, Daryl P.; Alena, Rick; Clancy, Daniel (Technical Monitor)

2002-01-01

The computational infrastructure of the International Space Station (ISS) is a dynamic system that supports multiple vehicle subsystems such as Caution and Warning, Electrical Power Systems and Command and Data Handling (C&DH), as well as scientific payloads of varying size and complexity. The dynamic nature of the ISS configuration coupled with the increased demand for payload support places a significant burden on the inherently resource constrained computational infrastructure of the ISS. Onboard system diagnostics applications are hosted on computers that are elements of the avionics network while ground-based diagnostic applications receive only a subset of available telemetry, down-linked via S-band communications. In this paper we propose a scalable, out-of-band diagnostics architecture for ISS systems support that uses a read-only connection for C&DH data acquisition, which provides a lower cost of deployment and maintenance (versus a higher criticality readwrite connection). The diagnostics processing burden is off-loaded from the avionics network to elements of the on-board LAN that have a lower overall cost of operation and increased computational capacity. A superset of diagnostic data, richer in content than the configured telemetry, is made available to Advanced Diagnostic System (ADS) clients running on wireless handheld devices, affording the crew greater mobility for troubleshooting and providing improved insight into vehicle state. The superset of diagnostic data is made available to the ground in near real-time via an out-of band downlink, providing a high level of fidelity between vehicle state and test, training and operational facilities on the ground.

Critical infrastructure protection : significant challenges in developing national capabilities

DOT National Transportation Integrated Search

2001-04-01

To address the concerns about protecting the nation's critical computer-dependent infrastructure, this General Accounting Office (GOA) report describes the progress of the National Infrastructure Protection Center (NIPC) in (1) developing national ca...

Distributed Accounting on the Grid

NASA Technical Reports Server (NTRS)

Thigpen, William; Hacker, Thomas J.; McGinnis, Laura F.; Athey, Brian D.

2001-01-01

By the late 1990s, the Internet was adequately equipped to move vast amounts of data between HPC (High Performance Computing) systems, and efforts were initiated to link together the national infrastructure of high performance computational and data storage resources together into a general computational utility 'grid', analogous to the national electrical power grid infrastructure. The purpose of the Computational grid is to provide dependable, consistent, pervasive, and inexpensive access to computational resources for the computing community in the form of a computing utility. This paper presents a fully distributed view of Grid usage accounting and a methodology for allocating Grid computational resources for use on a Grid computing system.

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

PubMed Central

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

2015-01-01

Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

PubMed

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

2015-05-01

The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

Pilots 2.0: DIRAC pilots for all the skies

NASA Astrophysics Data System (ADS)

Stagni, F.; Tsaregorodtsev, A.; McNab, A.; Luzzi, C.

2015-12-01

In the last few years, new types of computing infrastructures, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are opportunistic. Most of these new infrastructures are based on virtualization techniques. Meanwhile, some concepts, such as distributed queues, lost appeal, while still supporting a vast amount of resources. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to hide the diversity of underlying resources has become essential. The DIRAC WMS is based on the concept of pilot jobs that was introduced back in 2004. A pilot is what creates the possibility to run jobs on a worker node. Within DIRAC, we developed a new generation of pilot jobs, that we dubbed Pilots 2.0. Pilots 2.0 are not tied to a specific infrastructure; rather they are generic, fully configurable and extendible pilots. A Pilot 2.0 can be sent, as a script to be run, or it can be fetched from a remote location. A pilot 2.0 can run on every computing resource, e.g.: on CREAM Computing elements, on DIRAC Computing elements, on Virtual Machines as part of the contextualization script, or IAAC resources, provided that these machines are properly configured, hiding all the details of the Worker Nodes (WNs) infrastructure. Pilots 2.0 can be generated server and client side. Pilots 2.0 are the “pilots to fly in all the skies”, aiming at easy use of computing power, in whatever form it is presented. Another aim is the unification and simplification of the monitoring infrastructure for all kinds of computing resources, by using pilots as a network of distributed sensors coordinated by a central resource monitoring system. Pilots 2.0 have been developed using the command pattern. VOs using DIRAC can tune pilots 2.0 as they need, and extend or replace each and every pilot command in an easy way. In this paper we describe how Pilots 2.0 work with distributed and heterogeneous resources providing the necessary abstraction to deal with different kind of computing resources.

Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

NASA Astrophysics Data System (ADS)

Adakin, A.; Anisenkov, A.; Belov, S.; Chubarov, D.; Kalyuzhny, V.; Kaplin, V.; Korol, A.; Kuchin, N.; Lomakin, S.; Nikultsev, V.; Skovpen, K.; Sukharev, A.; Zaytsev, A.

2012-12-01

Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM&MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM&MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

Analysis Report for Exascale Storage Requirements for Scientific Data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruwart, Thomas M.

Over the next 10 years, the Department of Energy will be transitioning from Petascale to Exascale Computing resulting in data storage, networking, and infrastructure requirements to increase by three orders of magnitude. The technologies and best practices used today are the result of a relatively slow evolution of ancestral technologies developed in the 1950s and 1960s. These include magnetic tape, magnetic disk, networking, databases, file systems, and operating systems. These technologies will continue to evolve over the next 10 to 15 years on a reasonably predictable path. Experience with the challenges involved in transitioning these fundamental technologies from Terascale tomore » Petascale computing systems has raised questions about how these will scale another 3 or 4 orders of magnitude to meet the requirements imposed by Exascale computing systems. This report is focused on the most concerning scaling issues with data storage systems as they relate to High Performance Computing- and presents options for a path forward. Given the ability to store exponentially increasing amounts of data, far more advanced concepts and use of metadata will be critical to managing data in Exascale computing systems.« less

Editorial [Special issue on software defined networks and infrastructures, network function virtualisation, autonomous systems and network management

DOE PAGES

Biswas, Amitava; Liu, Chen; Monga, Inder; ...

2016-01-01

For last few years, there has been a tremendous growth in data traffic due to high adoption rate of mobile devices and cloud computing. Internet of things (IoT) will stimulate even further growth. This is increasing scale and complexity of telecom/internet service provider (SP) and enterprise data centre (DC) compute and network infrastructures. As a result, managing these large network-compute converged infrastructures is becoming complex and cumbersome. To cope up, network and DC operators are trying to automate network and system operations, administrations and management (OAM) functions. OAM includes all non-functional mechanisms which keep the network running.

White paper on science operations

NASA Technical Reports Server (NTRS)

Schreier, Ethan J.

1991-01-01

Major changes are taking place in the way astronomy gets done. There are continuing advances in observational capabilities across the frequency spectrum, involving both ground-based and space-based facilities. There is also very rapid evolution of relevant computing and data management technologies. However, although the new technologies are filtering in to the astronomy community, and astronomers are looking at their computing needs in new ways, there is little coordination or coherent policy. Furthermore, although there is great awareness of the evolving technologies in the arena of operations, much of the existing operations infrastructure is ill-suited to take advantage of them. Astronomy, especially space astronomy, has often been at the cutting edge of computer use in data reduction and image analysis, but has been somewhat removed from advanced applications in operations, which have tended to be implemented by industry rather than by the end-user scientists. The purpose of this paper is threefold. First, we briefly review the background and general status of astronomy-related computing. Second, we make recommendations in three areas: data analysis; operations (directed primarily to NASA-related activities); and issues of management and policy, believing that these must be addressed to enable technological progress and to proceed through the next decade. Finally, we recommend specific NASA-related work as part of the Astrotech-21 plans, to enable better science operations in the operations of the Great Observatories and in the lunar outpost era.

From information technology to informatics: the information revolution in dental education.

PubMed

Schleyer, Titus K; Thyvalikakath, Thankam P; Spallek, Heiko; Dziabiak, Michael P; Johnson, Lynn A

2012-01-01

The capabilities of information technology (IT) have advanced precipitously in the last fifty years. Many of these advances have enabled new and beneficial applications of IT in dental education. However, conceptually, IT use in dental schools is only in its infancy. Challenges and opportunities abound for improving how we support clinical care, education, and research with IT. In clinical care, we need to move electronic dental records beyond replicating paper, connect information on oral health to that on systemic health, facilitate collaborative care through teledentistry, and help clinicians apply evidence-based dentistry and preventive management strategies. With respect to education, we should adopt an evidence-based approach to IT use for teaching and learning, share effective educational content and methods, leverage technology-mediated changes in the balance of power between faculty and students, improve technology support for clinical teaching, and build an information infrastructure centered on learners and organizations. In research, opportunities include reusing clinical care data for research studies, helping advance computational methods for research, applying generalizable research tools in dentistry, and reusing research data and scientific workflows. In the process, we transition from a focus on IT-the mere technical aspects of applying computer technology-to one on informatics: the what, how, and why of managing information.

From Information Technology to Informatics: The Information Revolution in Dental Education

PubMed Central

Schleyer, Titus K.; Thyvalikakath, Thankam P.; Spallek, Heiko; Dziabiak, Michael P.; Johnson, Lynn A.

2014-01-01

The capabilities of information technology (IT) have advanced precipitously in the last fifty years. Many of these advances have enabled new and beneficial applications of IT in dental education. However, conceptually, IT use in dental schools is only in its infancy. Challenges and opportunities abound for improving how we support clinical care, education, and research with IT. In clinical care, we need to move electronic dental records beyond replicating paper, connect information on oral health to that on systemic health, facilitate collaborative care through teledentistry, and help clinicians apply evidence-based dentistry and preventive management strategies. With respect to education, we should adopt an evidence-based approach to IT use for teaching and learning, share effective educational content and methods, leverage technology-mediated changes in the balance of power between faculty and students, improve technology support for clinical teaching, and build an information infrastructure centered on learners and organizations. In research, opportunities include reusing clinical care data for research studies, helping advance computational methods for research, applying generalizable research tools in dentistry, and reusing research data and scientific workflows. In the process, we transition from a focus on IT—the mere technical aspects of applying computer technology—to one on informatics: the what, how, and why of managing information. PMID:22262557

Cloud computing can simplify HIT infrastructure management.

PubMed

Glaser, John

2011-08-01

Software as a Service (SaaS), built on cloud computing technology, is emerging as the forerunner in IT infrastructure because it helps healthcare providers reduce capital investments. Cloud computing leads to predictable, monthly, fixed operating expenses for hospital IT staff. Outsourced cloud computing facilities are state-of-the-art data centers boasting some of the most sophisticated networking equipment on the market. The SaaS model helps hospitals safeguard against technology obsolescence, minimizes maintenance requirements, and simplifies management.

Distribution system model calibration with big data from AMI and PV inverters

DOE PAGES

Peppanen, Jouni; Reno, Matthew J.; Broderick, Robert J.; ...

2016-03-03

Efficient management and coordination of distributed energy resources with advanced automation schemes requires accurate distribution system modeling and monitoring. Big data from smart meters and photovoltaic (PV) micro-inverters can be leveraged to calibrate existing utility models. This paper presents computationally efficient distribution system parameter estimation algorithms to improve the accuracy of existing utility feeder radial secondary circuit model parameters. The method is demonstrated using a real utility feeder model with advanced metering infrastructure (AMI) and PV micro-inverters, along with alternative parameter estimation approaches that can be used to improve secondary circuit models when limited measurement data is available. Lastly, themore » parameter estimation accuracy is demonstrated for both a three-phase test circuit with typical secondary circuit topologies and single-phase secondary circuits in a real mixed-phase test system.« less

Distribution system model calibration with big data from AMI and PV inverters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peppanen, Jouni; Reno, Matthew J.; Broderick, Robert J.

Efficient management and coordination of distributed energy resources with advanced automation schemes requires accurate distribution system modeling and monitoring. Big data from smart meters and photovoltaic (PV) micro-inverters can be leveraged to calibrate existing utility models. This paper presents computationally efficient distribution system parameter estimation algorithms to improve the accuracy of existing utility feeder radial secondary circuit model parameters. The method is demonstrated using a real utility feeder model with advanced metering infrastructure (AMI) and PV micro-inverters, along with alternative parameter estimation approaches that can be used to improve secondary circuit models when limited measurement data is available. Lastly, themore » parameter estimation accuracy is demonstrated for both a three-phase test circuit with typical secondary circuit topologies and single-phase secondary circuits in a real mixed-phase test system.« less

Progress in Machine Learning Studies for the CMS Computing Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bonacorsi, Daniele; Kuznetsov, Valentin; Magini, Nicolo

Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.

Progress in Machine Learning Studies for the CMS Computing Infrastructure

DOE PAGES

Bonacorsi, Daniele; Kuznetsov, Valentin; Magini, Nicolo; ...

2017-12-06

Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.

Progress In Developing An In-Pile Acoustically Telemetered Sensor Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, James A.; Garrett, Steven L.; Heibel, Michael D.

2016-09-01

A salient grand challenge for a number of Department of Energy programs such as Fuels Cycle Research and Development ( includes Accident Tolerant Fuel research and the Transient Reactor Test Facility Restart experiments), Light Water Sustainability, and Advanced Reactor Technologies is to enhance our fundamental understanding of fuel and materials behavior under irradiation. Robust and accurate in-pile measurements will be instrumental to develop and validate a computationally predictive multi-scale understanding of nuclear fuel and materials. This sensing technology will enable the linking of fundamental micro-structural evolution mechanisms to the macroscopic degradation of fuels and materials. The in situ sensors andmore » measurement systems will monitor local environmental parameters as well as characterize microstructure evolution during irradiation. One of the major road blocks in developing practical robust, and cost effective in-pile sensor systems, are instrument leads. If a wireless telemetry infrastructure can be developed for in-pile use, in-core measurements would become more attractive and effective. Thus to be successful in accomplishing effective in-pile sensing and microstructure characterization an interdisciplinary measurement infrastructure needs to be developed in parallel with key sensing technology. For the discussion in this research, infrastructure is defined as systems, technology, techniques, and algorithms that may be necessary in the delivery of beneficial and robust data from in-pile devices. The architecture of a system’s infrastructure determines how well it operates and how flexible it is to meet future requirements. The limiting path for the effective deployment of the salient sensing technology will not be the sensors themselves but the infrastructure that is necessary to communicate data from in-pile to the outside world in a non-intrusive and reliable manner. This article gives a high level overview of a promising telemetry infrastructure based on acoustic wireless transmission of data that is being developed and tested by the INL, Penn State and Westinghouse.« less

Convergence, Competition, Cooperation: The Report of the Governor's Blue Ribbon Telecommunications Infrastructure Task Force. Volume One.

ERIC Educational Resources Information Center

Wisconsin Governor's Office, Madison.

This report by the Blue Ribbon Task Force on Wisconsin's Telecommunications Infrastructure considers infrastructure to be the common network that connects individual residences, businesses, and agencies, rather than the individual systems and equipment themselves. The task force recognizes that advances in telecommunications technologies and…

Education as eHealth Infrastructure: Considerations in Advancing a National Agenda for eHealth

ERIC Educational Resources Information Center

Hilberts, Sonya; Gray, Kathleen

2014-01-01

This paper explores the role of education as infrastructure in large-scale ehealth strategies--in theory, in international practice and in one national case study. Education is often invisible in the documentation of ehealth infrastructure. Nevertheless a review of international practice shows that there is significant educational investment made…

Sustainable access to data, products, services and software from the European seismological Research Infrastructures: the EPOS TCS Seismology

NASA Astrophysics Data System (ADS)

Haslinger, Florian; Dupont, Aurelien; Michelini, Alberto; Rietbrock, Andreas; Sleeman, Reinoud; Wiemer, Stefan; Basili, Roberto; Bossu, Rémy; Cakti, Eser; Cotton, Fabrice; Crawford, Wayne; Diaz, Jordi; Garth, Tom; Locati, Mario; Luzi, Lucia; Pinho, Rui; Pitilakis, Kyriazis; Strollo, Angelo

2016-04-01

Easy, efficient and comprehensive access to data, data products, scientific services and scientific software is a key ingredient in enabling research at the frontiers of science. Organizing this access across the European Research Infrastructures in the field of seismology, so that it best serves user needs, takes advantage of state-of-the-art ICT solutions, provides cross-domain interoperability, and is organizationally and financially sustainable in the long term, is the core challenge of the implementation phase of the Thematic Core Service (TCS) Seismology within the EPOS-IP project. Building upon the existing European-level infrastructures ORFEUS for seismological waveforms, EMSC for seismological products, and EFEHR for seismological hazard and risk information, and implementing a pilot Computational Earth Science service starting from the results of the VERCE project, the work within the EPOS-IP project focuses on improving and extending the existing services, aligning them with global developments, to at the end produce a well coordinated framework that is technically, organizationally, and financially integrated with the EPOS architecture. This framework needs to respect the roles and responsibilities of the underlying national research infrastructures that are the data owners and main providers of data and products, and allow for active input and feedback from the (scientific) user community. At the same time, it needs to remain flexible enough to cope with unavoidable challenges in the availability of resources and dynamics of contributors. The technical work during the next years is organized in four areas: - constructing the next generation software architecture for the European Integrated (waveform) Data Archive EIDA, developing advanced metadata and station information services, fully integrate strong motion waveforms and derived parametric engineering-domain data, and advancing the integration of mobile (temporary) networks and OBS deployments in EIDA; - further development and expansion of services to access seismological products of scientific interest as provided by the community by implementing a common collection and development (IT) platform, improvements in the earthquake information services e.g. by introducing more robust quality indicators and diversifying collection and dissemination mechanisms, as well as improving historical earthquake data services; - development of a comprehensive suite of earthquake hazard products, tools, and services harmonized on the European level and available through a common access platform, encompassing information on seismic sources, seismogenic faults, ground-motion prediction equations, geotechnical information, and strong-motion recordings in buildings, together with an interface to earthquake risk; - a portal implementation of computational seismology tools and services, specifically for seismic waveform propagation in complex 3D media following the results of the VERCE project, and initiating the inclusion of further suitable codes on that portal in discussion with the community, forming the basis of EPOS computational earth science infrastructure. This will be accompanied by development and implementation of integrated and interoperable metadata structures, adequate and referencable persistent identifiers, and appropriate user access and authorization mechanisms. Here we present further detail on the work plan with the attempt to foster interaction with the target user community on the spectrum of services as well as on feedback mechanisms and governance.

Near Real-Time Flood Monitoring and Impact Assessment Systems. Chapter 6; [Case Study: 2011 Flooding in Southeast Asia

NASA Technical Reports Server (NTRS)

Ahamed, Aakash; Bolten, John; Doyle, Colin; Fayne, Jessica

2016-01-01

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

VDJServer: A Cloud-Based Analysis Portal and Data Commons for Immune Repertoire Sequences and Rearrangements.

PubMed

Christley, Scott; Scarborough, Walter; Salinas, Eddie; Rounds, William H; Toby, Inimary T; Fonner, John M; Levin, Mikhail K; Kim, Min; Mock, Stephen A; Jordan, Christopher; Ostmeyer, Jared; Buntzman, Adam; Rubelt, Florian; Davila, Marco L; Monson, Nancy L; Scheuermann, Richard H; Cowell, Lindsay G

2018-01-01

Recent technological advances in immune repertoire sequencing have created tremendous potential for advancing our understanding of adaptive immune response dynamics in various states of health and disease. Immune repertoire sequencing produces large, highly complex data sets, however, which require specialized methods and software tools for their effective analysis and interpretation. VDJServer is a cloud-based analysis portal for immune repertoire sequence data that provide access to a suite of tools for a complete analysis workflow, including modules for preprocessing and quality control of sequence reads, V(D)J gene segment assignment, repertoire characterization, and repertoire comparison. VDJServer also provides sophisticated visualizations for exploratory analysis. It is accessible through a standard web browser via a graphical user interface designed for use by immunologists, clinicians, and bioinformatics researchers. VDJServer provides a data commons for public sharing of repertoire sequencing data, as well as private sharing of data between users. We describe the main functionality and architecture of VDJServer and demonstrate its capabilities with use cases from cancer immunology and autoimmunity. VDJServer provides a complete analysis suite for human and mouse T-cell and B-cell receptor repertoire sequencing data. The combination of its user-friendly interface and high-performance computing allows large immune repertoire sequencing projects to be analyzed with no programming or software installation required. VDJServer is a web-accessible cloud platform that provides access through a graphical user interface to a data management infrastructure, a collection of analysis tools covering all steps in an analysis, and an infrastructure for sharing data along with workflows, results, and computational provenance. VDJServer is a free, publicly available, and open-source licensed resource.

e-Infrastructures for e-Sciences 2013 A CHAIN-REDS Workshop organised under the aegis of the European Commission

NASA Astrophysics Data System (ADS)

The CHAIN-REDS Project is organising a workshop on "e-Infrastructures for e-Sciences" focusing on Cloud Computing and Data Repositories under the aegis of the European Commission and in co-location with the International Conference on e-Science 2013 (IEEE2013) that will be held in Beijing, P.R. of China on October 17-22, 2013. The core objective of the CHAIN-REDS project is to promote, coordinate and support the effort of a critical mass of non-European e-Infrastructures for Research and Education to collaborate with Europe addressing interoperability and interoperation of Grids and other Distributed Computing Infrastructures (DCI). From this perspective, CHAIN-REDS will optimise the interoperation of European infrastructures with those present in 6 other regions of the world, both from a development and use point of view, and catering to different communities. Overall, CHAIN-REDS will provide input for future strategies and decision-making regarding collaboration with other regions on e-Infrastructure deployment and availability of related data; it will raise the visibility of e-Infrastructures towards intercontinental audiences, covering most of the world and will provide support to establish globally connected and interoperable infrastructures, in particular between the EU and the developing regions. Organised by IHEP, INFN and Sigma Orionis with the support of all project partners, this workshop will aim at: - Presenting the state of the art of Cloud computing in Europe and in China and discussing the opportunities offered by having interoperable and federated e-Infrastructures; - Exploring the existing initiatives of Data Infrastructures in Europe and China, and highlighting the Data Repositories of interest for the Virtual Research Communities in several domains such as Health, Agriculture, Climate, etc.

Centralized Fabric Management Using Puppet, Git, and GLPI

NASA Astrophysics Data System (ADS)

Smith, Jason A.; De Stefano, John S., Jr.; Fetzko, John; Hollowell, Christopher; Ito, Hironori; Karasawa, Mizuki; Pryor, James; Rao, Tejas; Strecker-Kellogg, William

2012-12-01

Managing the infrastructure of a large and complex data center can be extremely difficult without taking advantage of recent technological advances in administrative automation. Puppet is a seasoned open-source tool that is designed for enterprise class centralized configuration management. At the RHIC and ATLAS Computing Facility (RACF) at Brookhaven National Laboratory, we use Puppet along with Git, GLPI, and some custom scripts as part of our centralized configuration management system. In this paper, we discuss how we use these tools for centralized configuration management of our servers and services, change management requiring authorized approval of production changes, a complete version controlled history of all changes made, separation of production, testing and development systems using puppet environments, semi-automated server inventory using GLPI, and configuration change monitoring and reporting using the Puppet dashboard. We will also discuss scalability and performance results from using these tools on a 2,000+ node cluster and 400+ infrastructure servers with an administrative staff of approximately 25 full-time employees (FTEs).

OpenSoC Fabric

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

Current Capabilities at SNL for the Integration of Small Modular Reactors onto Smart Microgrids Using Sandia's Smart Microgrid Technology High Performance Computing and Advanced Manufacturing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Salvador B.

Smart grids are a crucial component for enabling the nation’s future energy needs, as part of a modernization effort led by the Department of Energy. Smart grids and smart microgrids are being considered in niche applications, and as part of a comprehensive energy strategy to help manage the nation’s growing energy demands, for critical infrastructures, military installations, small rural communities, and large populations with limited water supplies. As part of a far-reaching strategic initiative, Sandia National Laboratories (SNL) presents herein a unique, three-pronged approach to integrate small modular reactors (SMRs) into microgrids, with the goal of providing economically-competitive, reliable, andmore » secure energy to meet the nation’s needs. SNL’s triad methodology involves an innovative blend of smart microgrid technology, high performance computing (HPC), and advanced manufacturing (AM). In this report, Sandia’s current capabilities in those areas are summarized, as well as paths forward that will enable DOE to achieve its energy goals. In the area of smart grid/microgrid technology, Sandia’s current computational capabilities can model the entire grid, including temporal aspects and cyber security issues. Our tools include system development, integration, testing and evaluation, monitoring, and sustainment.« less

Galaxy CloudMan: delivering cloud compute clusters.

PubMed

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Connor, Carolyn Marie; Jacobson, Andree Lars; Bonnie, Amanda Marie

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in evenmore » many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.« less

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

DOE PAGES

Connor, Carolyn Marie; Jacobson, Andree Lars; Bonnie, Amanda Marie; ...

2016-11-01

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in evenmore » many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.« less

Towards a single seismological service infrastructure in Europe

NASA Astrophysics Data System (ADS)

Spinuso, A.; Trani, L.; Frobert, L.; Van Eck, T.

2012-04-01

In the last five year services and data providers, within the seismological community in Europe, focused their efforts in migrating the way of opening their archives towards a Service Oriented Architecture (SOA). This process tries to follow pragmatically the technological trends and available solutions aiming at effectively improving all the data stewardship activities. These advancements are possible thanks to the cooperation and the follow-ups of several EC infrastructural projects that, by looking at general purpose techniques, combine their developments envisioning a multidisciplinary platform for the earth observation as the final common objective (EPOS, Earth Plate Observation System) One of the first results of this effort is the Earthquake Data Portal (http://www.seismicportal.eu), which provides a collection of tools to discover, visualize and access a variety of seismological data sets like seismic waveform, accelerometric data, earthquake catalogs and parameters. The Portal offers a cohesive distributed search environment, linking data search and access across multiple data providers through interactive web-services, map-based tools and diverse command-line clients. Our work continues under other EU FP7 projects. Here we will address initiatives in two of those projects. The NERA, (Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation) project will implement a Common Services Architecture based on OGC services APIs, in order to provide Resource-Oriented common interfaces across the data access and processing services. This will improve interoperability between tools and across projects, enabling the development of higher-level applications that can uniformly access the data and processing services of all participants. This effort will be conducted jointly with the VERCE project (Virtual Earthquake and Seismology Research Community for Europe). VERCE aims to enable seismologists to exploit the wealth of seismic data within a data-intensive computation framework, which will be tailored to the specific needs of the community. It will provide a new interoperable infrastructure, as the computational backbone laying behind the publicly available interfaces. VERCE will have to face the challenges of implementing a service oriented architecture providing an efficient layer between the Data and the Grid infrastructures, coupling HPC data analysis and HPC data modeling applications through the execution of workflows and data sharing mechanism. Online registries of interoperable worklflow components, storage of intermediate results and data provenance are those aspects that are currently under investigations to make the VERCE facilities usable from a large scale of users, data and service providers. For such purposes the adoption of a Digital Object Architecture, to create online catalogs referencing and describing semantically all these distributed resources, such as datasets, computational processes and derivative products, is seen as one of the viable solution to monitor and steer the usage of the infrastructure, increasing its efficiency and the cooperation among the community.

Software Reuse Methods to Improve Technological Infrastructure for e-Science

NASA Technical Reports Server (NTRS)

Marshall, James J.; Downs, Robert R.; Mattmann, Chris A.

2011-01-01

Social computing has the potential to contribute to scientific research. Ongoing developments in information and communications technology improve capabilities for enabling scientific research, including research fostered by social computing capabilities. The recent emergence of e-Science practices has demonstrated the benefits from improvements in the technological infrastructure, or cyber-infrastructure, that has been developed to support science. Cloud computing is one example of this e-Science trend. Our own work in the area of software reuse offers methods that can be used to improve new technological development, including cloud computing capabilities, to support scientific research practices. In this paper, we focus on software reuse and its potential to contribute to the development and evaluation of information systems and related services designed to support new capabilities for conducting scientific research.

Neo-deterministic definition of earthquake hazard scenarios: a multiscale application to India

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Magrin, Andrea; Parvez, Imtiyaz A.; Rastogi, Bal K.; Vaccari, Franco; Cozzini, Stefano; Bisignano, Davide; Romanelli, Fabio; Panza, Giuliano F.; Ashish, Mr; Mir, Ramees R.

2014-05-01

The development of effective mitigation strategies requires scientifically consistent estimates of seismic ground motion; recent analysis, however, showed that the performances of the classical probabilistic approach to seismic hazard assessment (PSHA) are very unsatisfactory in anticipating ground shaking from future large earthquakes. Moreover, due to their basic heuristic limitations, the standard PSHA estimates are by far unsuitable when dealing with the protection of critical structures (e.g. nuclear power plants) and cultural heritage, where it is necessary to consider extremely long time intervals. Nonetheless, the persistence in resorting to PSHA is often explained by the need to deal with uncertainties related with ground shaking and earthquakes recurrence. We show that current computational resources and physical knowledge of the seismic waves generation and propagation processes, along with the improving quantity and quality of geophysical data, allow nowadays for viable numerical and analytical alternatives to the use of PSHA. The advanced approach considered in this study, namely the NDSHA (neo-deterministic seismic hazard assessment), is based on the physically sound definition of a wide set of credible scenario events and accounts for uncertainties and earthquakes recurrence in a substantially different way. The expected ground shaking due to a wide set of potential earthquakes is defined by means of full waveforms modelling, based on the possibility to efficiently compute synthetic seismograms in complex laterally heterogeneous anelastic media. In this way a set of scenarios of ground motion can be defined, either at national and local scale, the latter considering the 2D and 3D heterogeneities of the medium travelled by the seismic waves. The efficiency of the NDSHA computational codes allows for the fast generation of hazard maps at the regional scale even on a modern laptop computer. At the scenario scale, quick parametric studies can be easily performed to understand the influence of the model characteristics on the computed ground shaking scenarios. For massive parametric tests, or for the repeated generation of large scale hazard maps, the methodology can take advantage of more advanced computational platforms, ranging from GRID computing infrastructures to HPC dedicated clusters up to Cloud computing. In such a way, scientists can deal efficiently with the variety and complexity of the potential earthquake sources, and perform parametric studies to characterize the related uncertainties. NDSHA provides realistic time series of expected ground motion readily applicable for seismic engineering analysis and other mitigation actions. The methodology has been successfully applied to strategic buildings, lifelines and cultural heritage sites, and for the purpose of seismic microzoning in several urban areas worldwide. A web application is currently being developed that facilitates the access to the NDSHA methodology and the related outputs by end-users, who are interested in reliable territorial planning and in the design and construction of buildings and infrastructures in seismic areas. At the same, the web application is also shaping up as an advanced educational tool to explore interactively how seismic waves are generated at the source, propagate inside structural models, and build up ground shaking scenarios. We illustrate the preliminary results obtained from a multiscale application of NDSHA approach to the territory of India, zooming from large scale hazard maps of ground shaking at bedrock, to the definition of local scale earthquake scenarios for selected sites in the Gujarat state (NW India). The study aims to provide the community (e.g. authorities and engineers) with advanced information for earthquake risk mitigation, which is particularly relevant to Gujarat in view of the rapid development and urbanization of the region.

RAPPORT: running scientific high-performance computing applications on the cloud.

PubMed

Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

2013-01-28

Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

Some recent advances of intelligent health monitoring systems for civil infrastructures in HIT

NASA Astrophysics Data System (ADS)

Ou, Jinping

2005-06-01

The intelligent health monitoring systems more and more become a technique for ensuring the health and safety of civil infrastructures and also an important approach for research of the damage accumulation or even disaster evolving characteristics of civil infrastructures, and attracts prodigious research interests and active development interests of scientists and engineers since a great number of civil infrastructures are planning and building each year in mainland China. In this paper, some recent advances on research, development nad implementation of intelligent health monitoring systems for civil infrastructuresin mainland China, especially in Harbin Institute of Technology (HIT), P.R.China. The main contents include smart sensors such as optical fiber Bragg grating (OFBG) and polivinyllidene fluoride (PVDF) sensors, fatigue life gauges, self-sensing mortar and carbon fiber reinforced polymer (CFRP), wireless sensor networks and their implementation in practical infrastructures such as offshore platform structures, hydraulic engineering structures, large span bridges and large space structures. Finally, the relative research projects supported by the national foundation agencies of China are briefly introduced.

Alternative vehicles and infrastructure requirements conference.

DOT National Transportation Integrated Search

2011-11-01

"A conference entitled Alternative Fuel / Advanced Vehicles Technologies & Infrastructure Requirements: Bringing Innovation to Our Streets was held in New York, NY at New York University on June 14, 2011. The conference addressed several of the...

Space-based communications infrastructure for developing countries

NASA Astrophysics Data System (ADS)

Barker, Keith; Barnes, Carl; Price, K. M.

1995-08-01

This study examines the potential use of satellites to augment the telecommunications infrastructure of developing countries with advanced satellites. The study investigated the potential market for using satellites in developing countries, the role of satellites in national information infrastructures (NII), the technical feasibility of augmenting NIIs with satellites, and a nation's financial conditions necessary for procuring satellite systems. In addition, the study examined several technical areas including onboard processing, intersatellite links, frequency of operation, multibeam and active antennas, and advanced satellite technologies. The marketing portion of this study focused on three case studies: China, Brazil, and Mexico. These cases represent countries in various stages of telecommunication infrastructure development. The study concludes by defining the needs of developing countries for satellites, and recommends steps that both industry and NASA can take to improve the competitiveness of U.S. satellite manufacturing.

Integrating Urban Infrastructure and Health System Impact Modeling for Disasters and Mass-Casualty Events

NASA Astrophysics Data System (ADS)

Balbus, J. M.; Kirsch, T.; Mitrani-Reiser, J.

2017-12-01

Over recent decades, natural disasters and mass-casualty events in United States have repeatedly revealed the serious consequences of health care facility vulnerability and the subsequent ability to deliver care for the affected people. Advances in predictive modeling and vulnerability assessment for health care facility failure, integrated infrastructure, and extreme weather events have now enabled a more rigorous scientific approach to evaluating health care system vulnerability and assessing impacts of natural and human disasters as well as the value of specific interventions. Concurrent advances in computing capacity also allow, for the first time, full integration of these multiple individual models, along with the modeling of population behaviors and mass casualty responses during a disaster. A team of federal and academic investigators led by the National Center for Disaster Medicine and Public Health (NCDMPH) is develoing a platform for integrating extreme event forecasts, health risk/impact assessment and population simulations, critical infrastructure (electrical, water, transportation, communication) impact and response models, health care facility-specific vulnerability and failure assessments, and health system/patient flow responses. The integration of these models is intended to develop much greater understanding of critical tipping points in the vulnerability of health systems during natural and human disasters and build an evidence base for specific interventions. Development of such a modeling platform will greatly facilitate the assessment of potential concurrent or sequential catastrophic events, such as a terrorism act following a severe heat wave or hurricane. This presentation will highlight the development of this modeling platform as well as applications not just for the US health system, but also for international science-based disaster risk reduction efforts, such as the Sendai Framework and the WHO SMART hospital project.

International Symposium on Grids and Clouds (ISGC) 2016

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2016 will be held at Academia Sinica in Taipei, Taiwan from 13-18 March 2016, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). The theme of ISGC 2016 focuses on“Ubiquitous e-infrastructures and Applications”. Contemporary research is impossible without a strong IT component - researchers rely on the existence of stable and widely available e-infrastructures and their higher level functions and properties. As a result of these expectations, e-Infrastructures are becoming ubiquitous, providing an environment that supports large scale collaborations that deal with global challenges as well as smaller and temporal research communities focusing on particular scientific problems. To support those diversified communities and their needs, the e-Infrastructures themselves are becoming more layered and multifaceted, supporting larger groups of applications. Following the call for the last year conference, ISGC 2016 continues its aim to bring together users and application developers with those responsible for the development and operation of multi-purpose ubiquitous e-Infrastructures. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities, Arts, and Social Sciences (HASS) Applications, Virtual Research Environment (including Middleware, tools, services, workflow, etc.), Data Management, Big Data, Networking & Security, Infrastructure & Operations, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC), etc.

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models.

PubMed

Rao, Nageswara S V; Poole, Stephen W; Ma, Chris Y T; He, Fei; Zhuang, Jun; Yau, David K Y

2016-04-01

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities, expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical subinfrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein their components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures, are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. The analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures. © 2015 Society for Risk Analysis.

S3DB core: a framework for RDF generation and management in bioinformatics infrastructures

PubMed Central

2010-01-01

Background Biomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine. Results A computational framework for bioinformatic infrastructure was designed to deal with the heterogeneous data sources and the sensitive mixture of public and private data that characterizes the biomedical domain. This framework consists of a logical model build with semantic web tools, coupled with a Markov process that propagates user operator states. An accompanying open source prototype was developed to meet a series of applications that range from collaborative multi-institution data acquisition efforts to data analysis applications that need to quickly traverse complex data structures. This report describes the two abstractions underlying the S3DB-based infrastructure, logical and numerical, and discusses its generality beyond the immediate confines of existing implementations. Conclusions The emergence of the "web as a computer" requires a formal model for the different functionalities involved in reading and writing to it. The S3DB core model proposed was found to address the design criteria of biomedical computational infrastructure, such as those supporting large scale multi-investigator research, clinical trials, and molecular epidemiology. PMID:20646315

Resilient Military Systems and the Advanced Cyber Threat

DTIC Science & Technology

2013-01-01

systems; intelligence, surveillance, and reconnaissance systems; logistics and human resource systems; and mobile as well as fixed- infrastructure ...significant portions of military and critical infrastructure : power generation, communications, fuel and transportation, emergency services, financial...vulnerabilities in the domestic power grid and critical infrastructure systems.4,5 DoD, and the United States, is extremely reliant on the

The Czech National Grid Infrastructure

NASA Astrophysics Data System (ADS)

Chudoba, J.; Křenková, I.; Mulač, M.; Ruda, M.; Sitera, J.

2017-10-01

The Czech National Grid Infrastructure is operated by MetaCentrum, a CESNET department responsible for coordinating and managing activities related to distributed computing. CESNET as the Czech National Research and Education Network (NREN) provides many e-infrastructure services, which are used by 94% of the scientific and research community in the Czech Republic. Computing and storage resources owned by different organizations are connected by fast enough network to provide transparent access to all resources. We describe in more detail the computing infrastructure, which is based on several different technologies and covers grid, cloud and map-reduce environment. While the largest part of CPUs is still accessible via distributed torque servers, providing environment for long batch jobs, part of infrastructure is available via standard EGI tools in EGI, subset of NGI resources is provided into EGI FedCloud environment with cloud interface and there is also Hadoop cluster provided by the same e-infrastructure.A broad spectrum of computing servers is offered; users can choose from standard 2 CPU servers to large SMP machines with up to 6 TB of RAM or servers with GPU cards. Different groups have different priorities on various resources, resource owners can even have an exclusive access. The software is distributed via AFS. Storage servers offering up to tens of terabytes of disk space to individual users are connected via NFS4 on top of GPFS and access to long term HSM storage with peta-byte capacity is also provided. Overview of available resources and recent statistics of usage will be given.

An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

NASA Astrophysics Data System (ADS)

Yang, Wei; Hall, Trevor

2012-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

Enabling Grid Computing resources within the KM3NeT computing model

NASA Astrophysics Data System (ADS)

Filippidis, Christos

2016-04-01

KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that - located at the bottom of the Mediterranean Sea - will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.

The Magellan Final Report on Cloud Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

,; Coghlan, Susan; Yelick, Katherine

The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computingmore » Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.« less

OCCAM: a flexible, multi-purpose and extendable HPC cluster

NASA Astrophysics Data System (ADS)

Aldinucci, M.; Bagnasco, S.; Lusso, S.; Pasteris, P.; Rabellino, S.; Vallero, S.

2017-10-01

The Open Computing Cluster for Advanced data Manipulation (OCCAM) is a multipurpose flexible HPC cluster designed and operated by a collaboration between the University of Torino and the Sezione di Torino of the Istituto Nazionale di Fisica Nucleare. It is aimed at providing a flexible, reconfigurable and extendable infrastructure to cater to a wide range of different scientific computing use cases, including ones from solid-state chemistry, high-energy physics, computer science, big data analytics, computational biology, genomics and many others. Furthermore, it will serve as a platform for R&D activities on computational technologies themselves, with topics ranging from GPU acceleration to Cloud Computing technologies. A heterogeneous and reconfigurable system like this poses a number of challenges related to the frequency at which heterogeneous hardware resources might change their availability and shareability status, which in turn affect methods and means to allocate, manage, optimize, bill, monitor VMs, containers, virtual farms, jobs, interactive bare-metal sessions, etc. This work describes some of the use cases that prompted the design and construction of the HPC cluster, its architecture and resource provisioning model, along with a first characterization of its performance by some synthetic benchmark tools and a few realistic use-case tests.

Galaxy CloudMan: delivering cloud compute clusters

PubMed Central

2010-01-01

Background Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge. PMID:21210983

Conditions for Ubiquitous Computing: What Can Be Learned from a Longitudinal Study

ERIC Educational Resources Information Center

Lei, Jing

2010-01-01

Based on survey data and interview data collected over four academic years, this longitudinal study examined how a ubiquitous computing project evolved along with the changes in teachers, students, the human infrastructure, and technology infrastructure in the school. This study also investigated what conditions were necessary for successful…

Modernization of the NASA scientific and technical information program

NASA Technical Reports Server (NTRS)

Cotter, Gladys A.; Hunter, Judy F.; Ostergaard, K.

1993-01-01

The NASA Scientific and Technical Information Program utilizes a technology infrastructure assembled in the mid 1960s to late 1970s to process and disseminate its information products. When this infrastructure was developed it placed NASA as a leader in processing STI. The retrieval engine for the STI database was the first of its kind and was used as the basis for developing commercial, other U.S., and foreign government agency retrieval systems. Due to the combination of changes in user requirements and the tremendous increase in technological capabilities readily available in the marketplace, this infrastructure is no longer the most cost-effective or efficient methodology available. Consequently, the NASA STI Program is pursuing a modernization effort that applies new technology to current processes to provide near-term benefits to the user. In conjunction with this activity, we are developing a long-term modernization strategy designed to transition the Program to a multimedia, global 'library without walls.' Critical pieces of the long-term strategy include streamlining access to sources of STI by using advances in computer networking and graphical user interfaces; creating and disseminating technical information in various electronic media including optical disks, video, and full text; and establishing a Technology Focus Group to maintain a current awareness of emerging technology and to plan for the future.

Towards computer-assisted surgery in shoulder joint replacement

NASA Astrophysics Data System (ADS)

Valstar, Edward R.; Botha, Charl P.; van der Glas, Marjolein; Rozing, Piet M.; van der Helm, Frans C. T.; Post, Frits H.; Vossepoel, Albert M.

A research programme that aims to improve the state of the art in shoulder joint replacement surgery has been initiated at the Delft University of Technology. Development of improved endoprostheses for the upper extremities (DIPEX), as this effort is called, is a clinically driven multidisciplinary programme consisting of many contributory aspects. A part of this research programme focuses on the pre-operative planning and per-operative guidance issues. The ultimate goal of this part of the DIPEX project is to create a surgical support infrastructure that can be used to predict the optimal surgical protocol and can assist with the selection of the most suitable endoprosthesis for a particular patient. In the pre-operative planning phase, advanced biomechanical models of the endoprosthesis fixation and the musculo-skeletal system of the shoulder will be incorporated, which are adjusted to the individual's morphology. Subsequently, the support infrastructure must assist the surgeon during the operation in executing his surgical plan. In the per-operative phase, the chosen optimal position of the endoprosthesis can be realised using camera-assisted tools or mechanical guidance tools. In this article, the pathway towards the desired surgical support infrastructure is described. Furthermore, we discuss the pre-operative planning phase and the per-operative guidance phase, the initial work performed, and finally, possible approaches for improving prosthesis placement.

Intelligent systems technology infrastructure for integrated systems

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1991-01-01

Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.

High Resolution Sensing and Control of Urban Water Networks

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Wong, B. P.; Kerkez, B.

2016-12-01

We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

Networking Technologies Enable Advances in Earth Science

NASA Technical Reports Server (NTRS)

Johnson, Marjory; Freeman, Kenneth; Gilstrap, Raymond; Beck, Richard

2004-01-01

This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.

Telemedicine: an emerging health care technology.

PubMed

Myers, Mary R

2003-01-01

Telemedicine uses advanced telecommunication technologies to exchange health information and provide health care services across geographic, time, social, and cultural barriers. All telemedicine applications require the use of the electronic transfer of information. Telemedicine encompasses computer technologies using narrow and high bandwidths for specific types of information transmission, broadcast video, compressed video, full motion video, and even virtual reality. There are many types of common medical devices that have been adapted for use with telemedicine technology, and many clinical services can be provided via telemedicine to patients who live in physician shortage areas. The greatest challenges for telemedicine in the twenty-first century are financing, safety standards, security, and infrastructure.

Tempest: Tools for Addressing the Needs of Next-Generation Climate Models

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.; Pinheiro, M. C.; Fong, J.

2015-12-01

Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for identifying weather extremes in large climate datasets. In this presentation, the latest advances with the implementation of this framework will be discussed, and a number of projects now utilizing these tools will be featured.

Sandia National Laboratories Institutional Plan FY1994--1999

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1993-10-01

This report presents a five year plan for the laboratory. This plan takes advantage of the technical strengths of the lab and its staff to address issues of concern to the nation on a scope much broader than Sandia`s original mission, while maintaining the general integrity of the laboratory. The plan proposes initiatives in a number of technologies which overlap the needs of its customers and the strengths of its staff. They include: advanced manufacturing technology; electronics; information and computational technology; transportation energy technology and infrastructure; environmental technology; energy research and technology development; biomedical systems engineering; and post-cold war defensemore » imperatives.« less

The clinical value of large neuroimaging data sets in Alzheimer's disease.

PubMed

Toga, Arthur W

2012-02-01

Rapid advances in neuroimaging and cyberinfrastructure technologies have brought explosive growth in the Web-based warehousing, availability, and accessibility of imaging data on a variety of neurodegenerative and neuropsychiatric disorders and conditions. There has been a prolific development and emergence of complex computational infrastructures that serve as repositories of databases and provide critical functionalities such as sophisticated image analysis algorithm pipelines and powerful three-dimensional visualization and statistical tools. The statistical and operational advantages of collaborative, distributed team science in the form of multisite consortia push this approach in a diverse range of population-based investigations. Copyright © 2012 Elsevier Inc. All rights reserved.

Geocomputation over Hybrid Computer Architecture and Systems: Prior Works and On-going Initiatives at UARK

NASA Astrophysics Data System (ADS)

Shi, X.

2015-12-01

As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced infrastructure remains unexplored in this domain. Within this presentation, our prior and on-going initiatives will be summarized to exemplify how we exploit multicore CPUs, GPUs, and MICs, and clusters of CPUs, GPUs and MICs, to accelerate geocomputation in different applications.

Cloud based intelligent system for delivering health care as a service.

PubMed

Kaur, Pankaj Deep; Chana, Inderveer

2014-01-01

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A network-based distributed, media-rich computing and information environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, R.L.

1995-12-31

Sunrise is a Los Alamos National Laboratory (LANL) project started in October 1993. It is intended to be a prototype National Information Infrastructure development project. A main focus of Sunrise is to tie together enabling technologies (networking, object-oriented distributed computing, graphical interfaces, security, multi-media technologies, and data-mining technologies) with several specific applications. A diverse set of application areas was chosen to ensure that the solutions developed in the project are as generic as possible. Some of the application areas are materials modeling, medical records and image analysis, transportation simulations, and K-12 education. This paper provides a description of Sunrise andmore » a view of the architecture and objectives of this evolving project. The primary objectives of Sunrise are three-fold: (1) To develop common information-enabling tools for advanced scientific research and its applications to industry; (2) To enhance the capabilities of important research programs at the Laboratory; (3) To define a new way of collaboration between computer science and industrially-relevant research.« less

Development Model for Research Infrastructures

NASA Astrophysics Data System (ADS)

Wächter, Joachim; Hammitzsch, Martin; Kerschke, Dorit; Lauterjung, Jörn

2015-04-01

Research infrastructures (RIs) are platforms integrating facilities, resources and services used by the research communities to conduct research and foster innovation. RIs include scientific equipment, e.g., sensor platforms, satellites or other instruments, but also scientific data, sample repositories or archives. E-infrastructures on the other hand provide the technological substratum and middleware to interlink distributed RI components with computing systems and communication networks. The resulting platforms provide the foundation for the design and implementation of RIs and play an increasing role in the advancement and exploitation of knowledge and technology. RIs are regarded as essential to achieve and maintain excellence in research and innovation crucial for the European Research Area (ERA). The implementation of RIs has to be considered as a long-term, complex development process often over a period of 10 or more years. The ongoing construction of Spatial Data Infrastructures (SDIs) provides a good example for the general complexity of infrastructure development processes especially in system-of-systems environments. A set of directives issued by the European Commission provided a framework of guidelines for the implementation processes addressing the relevant content and the encoding of data as well as the standards for service interfaces and the integration of these services into networks. Additionally, a time schedule for the overall construction process has been specified. As a result this process advances with a strong participation of member states and responsible organisations. Today, SDIs provide the operational basis for new digital business processes in both national and local authorities. Currently, the development of integrated RIs in Earth and Environmental Sciences is characterised by the following properties: • A high number of parallel activities on European and national levels with numerous institutes and organisations participating. The maturity of individual scientific domains differs considerably. • Technologically and organisationally many different RI components have to be integrated. Individual systems are often complex and have a long-term history. Existing approaches are on different maturity levels, e.g. in relation to the standardisation of interfaces. • The concrete implementation process consists of independent and often parallel development activities. In many cases no detailed architectural blue-print for the envisioned system exists. • Most of the funding currently available for RI implementation is provided on a project basis. To increase the synergies in infrastructure development the authors propose a specific RI Maturity Model (RIMM) that is specifically qualified for open system-of-system environments. RIMM is based on the concepts of Capability Maturity Models for organisational development, concretely the Levels of Conceptual Interoperability Model (LCIM) specifying the technical, syntactical, semantic, pragmatic, dynamic, and conceptual layers of interoperation [1]. The model is complemented by the identification and integration of growth factors (according to the Nolan Stages Theory [2]). These factors include supply and demand factors. Supply factors comprise available resources, e.g., data, services and IT-management capabilities including organisations and IT-personal. Demand factors are the overall application portfolio for RIs but also the skills and requirements of scientists and communities using the infrastructure. RIMM thus enables a balanced development process of RI and RI components by evaluating the status of the supply and demand factors in relation to specific levels of interoperability. [1] Tolk, A., Diallo, A., Turnitsa, C. (2007): Applying the Levels of Conceptual Interoperability Model in Support of Integratability, Interoperability, and Composability for System-of-Systems Engineering. Systemics, Cybernetics and Informatics, Volume 5 - Number 5. [2] Mutsaers, E.-J., van der Zee, H., and Giertz, H. (1998): The evolution of information technology. Information Management & Computer Security, Volume 6 - Issue 3.

UNH Data Cooperative: A Cyber Infrastructure for Earth System Studies

NASA Astrophysics Data System (ADS)

Braswell, B. H.; Fekete, B. M.; Prusevich, A.; Gliden, S.; Magill, A.; Vorosmarty, C. J.

2007-12-01

Earth system scientists and managers have a continuously growing demand for a wide array of earth observations derived from various data sources including (a) modern satellite retrievals, (b) "in-situ" records, (c) various simulation outputs, and (d) assimilated data products combining model results with observational records. The sheer quantity of data, and formatting inconsistencies make it difficult for users to take full advantage of this important information resource. Thus the system could benefit from a thorough retooling of our current data processing procedures and infrastructure. Emerging technologies, like OPeNDAP and OGC map services, open standard data formats (NetCDF, HDF) data cataloging systems (NASA-Echo, Global Change Master Directory, etc.) are providing the basis for a new approach in data management and processing, where web- services are increasingly designed to serve computer-to-computer communications without human interactions and complex analysis can be carried out over distributed computer resources interconnected via cyber infrastructure. The UNH Earth System Data Collaborative is designed to utilize the aforementioned emerging web technologies to offer new means of access to earth system data. While the UNH Data Collaborative serves a wide array of data ranging from weather station data (Climate Portal) to ocean buoy records and ship tracks (Portsmouth Harbor Initiative) to land cover characteristics, etc. the underlaying data architecture shares common components for data mining and data dissemination via web-services. Perhaps the most unique element of the UNH Data Cooperative's IT infrastructure is its prototype modeling environment for regional ecosystem surveillance over the Northeast corridor, which allows the integration of complex earth system model components with the Cooperative's data services. While the complexity of the IT infrastructure to perform complex computations is continuously increasing, scientists are often forced to spend considerable amount of time to solve basic data management and preprocessing tasks and deal with low level computational design problems like parallelization of model codes. Our modeling infrastructure is designed to take care the bulk of the common tasks found in complex earth system models like I/O handling, computational domain and time management, parallel execution of the modeling tasks, etc. The modeling infrastructure allows scientists to focus on the numerical implementation of the physical processes on a single computational objects(typically grid cells) while the framework takes care of the preprocessing of input data, establishing of the data exchange between computation objects and the execution of the science code. In our presentation, we will discuss the key concepts of our modeling infrastructure. We will demonstrate integration of our modeling framework with data services offered by the UNH Earth System Data Collaborative via web interfaces. We will layout the road map to turn our prototype modeling environment into a truly community framework for wide range of earth system scientists and environmental managers.

Knowledge-based decision support for Space Station assembly sequence planning

NASA Astrophysics Data System (ADS)

1991-04-01

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

The Earth System Grid Federation (ESGF) Project

NASA Astrophysics Data System (ADS)

Carenton-Madiec, Nicolas; Denvil, Sébastien; Greenslade, Mark

2015-04-01

The Earth System Grid Federation (ESGF) Peer-to-Peer (P2P) enterprise system is a collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of model output and observational data. ESGF's primary goal is to facilitate advancements in Earth System Science. It is an interagency and international effort led by the US Department of Energy (DOE), and co-funded by National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), National Science Foundation (NSF), Infrastructure for the European Network of Earth System Modelling (IS-ENES) and international laboratories such as the Max Planck Institute for Meteorology (MPI-M) german Climate Computing Centre (DKRZ), the Australian National University (ANU) National Computational Infrastructure (NCI), Institut Pierre-Simon Laplace (IPSL), and the British Atmospheric Data Center (BADC). Its main mission is to support current CMIP5 activities and prepare for future assesments. The ESGF architecture is based on a system of autonomous and distributed nodes, which interoperate through common acceptance of federation protocols and trust agreements. Data is stored at multiple nodes around the world, and served through local data and metadata services. Nodes exchange information about their data holdings and services, trust each other for registering users and establishing access control decisions. The net result is that a user can use a web browser, connect to any node, and seamlessly find and access data throughout the federation. This type of collaborative working organization and distributed architecture context en-lighted the need of integration and testing processes definition to ensure the quality of software releases and interoperability. This presentation will introduce the ESGF project and demonstrate the range of tools and processes that have been set up to support release management activities.

Knowledge-based decision support for Space Station assembly sequence planning

NASA Technical Reports Server (NTRS)

1991-01-01

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

Implementation Issues of Virtual Desktop Infrastructure and Its Case Study for a Physician's Round at Seoul National University Bundang Hospital.

PubMed

Yoo, Sooyoung; Kim, Seok; Kim, Taegi; Kim, Jon Soo; Baek, Rong-Min; Suh, Chang Suk; Chung, Chin Youb; Hwang, Hee

2012-12-01

The cloud computing-based virtual desktop infrastructure (VDI) allows access to computing environments with no limitations in terms of time or place such that it can permit the rapid establishment of a mobile hospital environment. The objective of this study was to investigate the empirical issues to be considered when establishing a virtual mobile environment using VDI technology in a hospital setting and to examine the utility of the technology with an Apple iPad during a physician's rounds as a case study. Empirical implementation issues were derived from a 910-bed tertiary national university hospital that recently launched a VDI system. During the physicians' rounds, we surveyed patient satisfaction levels with the VDI-based mobile consultation service with the iPad and the relationship between these levels of satisfaction and hospital revisits, hospital recommendations, and the hospital brand image. Thirty-five inpatients (including their next-of-kin) and seven physicians participated in the survey. Implementation issues pertaining to the VDI system arose with regard to the highly availability system architecture, wireless network infrastructure, and screen resolution of the system. Other issues were related to privacy and security, mobile device management, and user education. When the system was used in rounds, patients and their next-of-kin expressed high satisfaction levels, and a positive relationship was noted as regards patients' decisions to revisit the hospital and whether the use of the VDI system improved the brand image of the hospital. Mobile hospital environments have the potential to benefit both physicians and patients. The issues related to the implementation of VDI system discussed here should be examined in advance for its successful adoption and implementation.

Implementation Issues of Virtual Desktop Infrastructure and Its Case Study for a Physician's Round at Seoul National University Bundang Hospital

PubMed Central

Yoo, Sooyoung; Kim, Seok; Kim, Taegi; Kim, Jon Soo; Baek, Rong-Min; Suh, Chang Suk; Chung, Chin Youb

2012-01-01

Objectives The cloud computing-based virtual desktop infrastructure (VDI) allows access to computing environments with no limitations in terms of time or place such that it can permit the rapid establishment of a mobile hospital environment. The objective of this study was to investigate the empirical issues to be considered when establishing a virtual mobile environment using VDI technology in a hospital setting and to examine the utility of the technology with an Apple iPad during a physician's rounds as a case study. Methods Empirical implementation issues were derived from a 910-bed tertiary national university hospital that recently launched a VDI system. During the physicians' rounds, we surveyed patient satisfaction levels with the VDI-based mobile consultation service with the iPad and the relationship between these levels of satisfaction and hospital revisits, hospital recommendations, and the hospital brand image. Thirty-five inpatients (including their next-of-kin) and seven physicians participated in the survey. Results Implementation issues pertaining to the VDI system arose with regard to the highly availability system architecture, wireless network infrastructure, and screen resolution of the system. Other issues were related to privacy and security, mobile device management, and user education. When the system was used in rounds, patients and their next-of-kin expressed high satisfaction levels, and a positive relationship was noted as regards patients' decisions to revisit the hospital and whether the use of the VDI system improved the brand image of the hospital. Conclusions Mobile hospital environments have the potential to benefit both physicians and patients. The issues related to the implementation of VDI system discussed here should be examined in advance for its successful adoption and implementation. PMID:23346476

Climate Science's Globally Distributed Infrastructure

NASA Astrophysics Data System (ADS)

Williams, D. N.

2016-12-01

The Earth System Grid Federation (ESGF) is primarily funded by the Department of Energy's (DOE's) Office of Science (the Office of Biological and Environmental Research [BER] Climate Data Informatics Program and the Office of Advanced Scientific Computing Research Next Generation Network for Science Program), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF), the European Infrastructure for the European Network for Earth System Modeling (IS-ENES), and the Australian National University (ANU). Support also comes from other U.S. federal and international agencies. The federation works across multiple worldwide data centers and spans seven international network organizations to provide users with the ability to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a series of geographically distributed peer nodes that are independently administered and united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP; output used by the Intergovernmental Panel on Climate Change assessment reports), multiple model intercomparison projects (MIPs; endorsed by the World Climate Research Programme [WCRP]), and the Accelerated Climate Modeling for Energy (ACME; ESGF is included in the overarching ACME workflow process to store model output). ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs the global climate science community. Data served by ESGF includes not only model output but also observational data from satellites and instruments, reanalysis, and generated images.

Accelerating epistasis analysis in human genetics with consumer graphics hardware.

PubMed

Sinnott-Armstrong, Nicholas A; Greene, Casey S; Cancare, Fabio; Moore, Jason H

2009-07-24

Human geneticists are now capable of measuring more than one million DNA sequence variations from across the human genome. The new challenge is to develop computationally feasible methods capable of analyzing these data for associations with common human disease, particularly in the context of epistasis. Epistasis describes the situation where multiple genes interact in a complex non-linear manner to determine an individual's disease risk and is thought to be ubiquitous for common diseases. Multifactor Dimensionality Reduction (MDR) is an algorithm capable of detecting epistasis. An exhaustive analysis with MDR is often computationally expensive, particularly for high order interactions. This challenge has previously been met with parallel computation and expensive hardware. The option we examine here exploits commodity hardware designed for computer graphics. In modern computers Graphics Processing Units (GPUs) have more memory bandwidth and computational capability than Central Processing Units (CPUs) and are well suited to this problem. Advances in the video game industry have led to an economy of scale creating a situation where these powerful components are readily available at very low cost. Here we implement and evaluate the performance of the MDR algorithm on GPUs. Of primary interest are the time required for an epistasis analysis and the price to performance ratio of available solutions. We found that using MDR on GPUs consistently increased performance per machine over both a feature rich Java software package and a C++ cluster implementation. The performance of a GPU workstation running a GPU implementation reduces computation time by a factor of 160 compared to an 8-core workstation running the Java implementation on CPUs. This GPU workstation performs similarly to 150 cores running an optimized C++ implementation on a Beowulf cluster. Furthermore this GPU system provides extremely cost effective performance while leaving the CPU available for other tasks. The GPU workstation containing three GPUs costs $2000 while obtaining similar performance on a Beowulf cluster requires 150 CPU cores which, including the added infrastructure and support cost of the cluster system, cost approximately $82,500. Graphics hardware based computing provides a cost effective means to perform genetic analysis of epistasis using MDR on large datasets without the infrastructure of a computing cluster.

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less

New frontiers in design synthesis

NASA Technical Reports Server (NTRS)

Goldin, D. S.; Venneri, S. L.; Noor, A. K.

1999-01-01

The Intelligent Synthesis Environment (ISE), which is one of the major strategic technologies under development at NASA centers and the University of Virginia, is described. One of the major objectives of ISE is to significantly enhance the rapid creation of innovative affordable products and missions. ISE uses a synergistic combination of leading-edge technologies, including high performance computing, high capacity communications and networking, human-centered computing, knowledge-based engineering, computational intelligence, virtual product development, and product information management. The environment will link scientists, design teams, manufacturers, suppliers, and consultants who participate in the mission synthesis as well as in the creation and operation of the aerospace system. It will radically advance the process by which complex science missions are synthesized, and high-tech engineering Systems are designed, manufactured and operated. The five major components critical to ISE are human-centered computing, infrastructure for distributed collaboration, rapid synthesis and simulation tools, life cycle integration and validation, and cultural change in both the engineering and science creative process. The five components and their subelements are described. Related U.S. government programs are outlined and the future impact of ISE on engineering research and education is discussed.

Demand for large freighter aircraft as projected by the NASA cargo/logistics airlift systems studies

NASA Technical Reports Server (NTRS)

Whitehead, A. H., Jr.; Kuhlman, W. H.

1979-01-01

This paper examines the market conditions up through the year 2008 to provide a preliminary assessment of the potential for and the characteristics of an advanced, all-cargo transport aircraft. Any new freighter must compete with current wide-body aircraft and their derivatives. Aircraft larger than the wide-bodies may incur economic penalties and operational problems. A lower direct operating cost is not a sufficient criterion to base a decision for the initiation of a new aircraft development or to select aircraft characteristics. Other factors of equal importance that are reviewed in this paper include considerations of the system infrastructure, the economics of the airlines, and the aircraft manufacturer return on investment. The results of the market forecast and a computer simulation show that an advanced long range aircraft with a payload between 68 to 181 tonnes (75 to 200 tons) could generate a solid foothold beginning around 1994.

Identification and Analysis of Critical Gaps in Nuclear Fuel Cycle Codes Required by the SINEMA Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adrian Miron; Joshua Valentine; John Christenson

2009-10-01

The current state of the art in nuclear fuel cycle (NFC) modeling is an eclectic mixture of codes with various levels of applicability, flexibility, and availability. In support of the advanced fuel cycle systems analyses, especially those by the Advanced Fuel Cycle Initiative (AFCI), Unviery of Cincinnati in collaboration with Idaho State University carried out a detailed review of the existing codes describing various aspects of the nuclear fuel cycle and identified the research and development needs required for a comprehensive model of the global nuclear energy infrastructure and the associated nuclear fuel cycles. Relevant information obtained on the NFCmore » codes was compiled into a relational database that allows easy access to various codes' properties. Additionally, the research analyzed the gaps in the NFC computer codes with respect to their potential integration into programs that perform comprehensive NFC analysis.« less

Demand for large freighter aircraft as projected by the NASA cargo/logistics airlift system studies

NASA Technical Reports Server (NTRS)

Whitehead, A. H., Jr.; Kuhlman, W. H.

1979-01-01

The market conditions are examined up through the year 2008 to provide a preliminary assessment of the potential for and the characteristics of an advanced, all-cargo transport aircraft. Any new freighter must compete with current wide-body aircraft and their derivatives. Aircraft larger than the wide-bodies may incur economic penalties and operational problems. A lower direct operating cost is not a sufficient criterion to base a decision for the initiation of a new aircraft development or to select aircraft characteristics. Other factors of equal importance that are reviewed in this paper include considerations of the system infrastructure, the economics of the airlines, and the aircraft manufacturer return on investment. The results of the market forecast and a computer simulation show that an advanced long range aircraft with a payload between 68 to 181 tonnes (75 to 200 tons) could generate a solid foothold beginning around 1994.

Dynamic VM Provisioning for TORQUE in a Cloud Environment

NASA Astrophysics Data System (ADS)

Zhang, S.; Boland, L.; Coddington, P.; Sevior, M.

2014-06-01

Cloud computing, also known as an Infrastructure-as-a-Service (IaaS), is attracting more interest from the commercial and educational sectors as a way to provide cost-effective computational infrastructure. It is an ideal platform for researchers who must share common resources but need to be able to scale up to massive computational requirements for specific periods of time. This paper presents the tools and techniques developed to allow the open source TORQUE distributed resource manager and Maui cluster scheduler to dynamically integrate OpenStack cloud resources into existing high throughput computing clusters.

VMEbus based computer and real-time UNIX as infrastructure of DAQ

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yasu, Y.; Fujii, H.; Nomachi, M.

1994-12-31

This paper describes what the authors have constructed as the infrastructure of data acquisition system (DAQ). The paper reports recent developments concerned with HP VME board computer with LynxOS (HP742rt/HP-RT) and Alpha/OSF1 with VMEbus adapter. The paper also reports current status of developing a Benchmark Suite for Data Acquisition (DAQBENCH) for measuring not only the performance of VME/CAMAC access but also that of the context switching, the inter-process communications and so on, for various computers including Workstation-based systems and VME board computers.

Technography and Design-Actuality Gap-Analysis of Internet Computer Technologies-Assisted Education: Western Expectations and Global Education

ERIC Educational Resources Information Center

Greenhalgh-Spencer, Heather; Jerbi, Moja

2017-01-01

In this paper, we provide a design-actuality gap-analysis of the internet infrastructure that exists in developing nations and nations in the global South with the deployed internet computer technologies (ICT)-assisted programs that are designed to use internet infrastructure to provide educational opportunities. Programs that specifically…

Closing the Gap: Cybersecurity for U.S. Forces and Commands

DTIC Science & Technology

2017-03-30

Dickson, Ph.D. Professor of Military Studies , JAWS Thesis Advisor Kevin Therrien, Col, USAF Committee Member Stephen Rogers, Colonel, USA Director...infrastructures, and includes the Internet, telecommunications networks, computer systems, and embedded processors and controllers in critical industries.”5...of information technology infrastructures, including the Internet, telecommunications networks, computer systems, and embedded processors and

The Role of Planetary Dust and Regolith Mechanics in Technology Developments at NASA

NASA Technical Reports Server (NTRS)

Agui, Juan H.

2011-01-01

One of NASA's long term goals continues to be the exploration of other planets and orbital bodies in our solar system. Our sustained presence through the installation of stations or bases on these planetary surfaces will depend on developing properly designed habitation modules, mobility systems and supporting infrastructure. NASA Glenn Research Center is involved in several technology developments in support of this overarching goal. Two key developments are in the area of advanced filtration and excavation systems. The first addresses the issues posed by the accumulation of particulate matter over long duration missions and the intrusion of planetary dust into spacecraft and habitat pressurized cabins. The latter supports the operation and infrastructure of insitu resource utilization (ISRU) processes to derive consumables and construction materials from the planetary regolith. These two developments require a basic understanding of the lunar regolith at the micro (particle) to macro (bulk) level. Investigation of the relevant properties of the lunar regolith and characterization of the standard simulant materials used in. testing were important first steps in these developments. The fundamentals and operational concepts of these technologies as well as descriptions of new NASA facilities, including the Particulate Filtration Testing and the NASA Excavation and Traction Testing facilities, and their capabilities for testing and advancing these technologies will be presented. The test data also serves to validate and anchor computational simulation models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykstra, Dave; Garzoglio, Gabriele; Kim, Hyunwoo

As of 2012, a number of US Department of Energy (DOE) National Laboratories have access to a 100 Gb/s wide-area network backbone. The ESnet Advanced Networking Initiative (ANI) project is intended to develop a prototype network, based on emerging 100 Gb/s Ethernet technology. The ANI network will support DOE's science research programs. A 100 Gb/s network test bed is a key component of the ANI project. The test bed offers the opportunity for early evaluation of 100Gb/s network infrastructure for supporting the high impact data movement typical of science collaborations and experiments. In order to make effective use of thismore » advanced infrastructure, the applications and middleware currently used by the distributed computing systems of large-scale science need to be adapted and tested within the new environment, with gaps in functionality identified and corrected. As a user of the ANI test bed, Fermilab aims to study the issues related to end-to-end integration and use of 100 Gb/s networks for the event simulation and analysis applications of physics experiments. In this paper we discuss our findings from evaluating existing HEP Physics middleware and application components, including GridFTP, Globus Online, etc. in the high-speed environment. These will include possible recommendations to the system administrators, application and middleware developers on changes that would make production use of the 100 Gb/s networks, including data storage, caching and wide area access.« less

The National Information Infrastructure: Agenda for Action.

ERIC Educational Resources Information Center

Department of Commerce, Washington, DC. Information Infrastructure Task Force.

The National Information Infrastructure (NII) is planned as a web of communications networks, computers, databases, and consumer electronics that will put vast amounts of information at the users' fingertips. Private sector firms are beginning to develop this infrastructure, but essential roles remain for the Federal Government. The National…

Helix Nebula: Enabling federation of existing data infrastructures and data services to an overarching cross-domain e-infrastructure

NASA Astrophysics Data System (ADS)

Lengert, Wolfgang; Farres, Jordi; Lanari, Riccardo; Casu, Francesco; Manunta, Michele; Lassalle-Balier, Gerard

2014-05-01

Helix Nebula has established a growing public private partnership of more than 30 commercial cloud providers, SMEs, and publicly funded research organisations and e-infrastructures. The Helix Nebula strategy is to establish a federated cloud service across Europe. Three high-profile flagships, sponsored by CERN (high energy physics), EMBL (life sciences) and ESA/DLR/CNES/CNR (earth science), have been deployed and extensively tested within this federated environment. The commitments behind these initial flagships have created a critical mass that attracts suppliers and users to the initiative, to work together towards an "Information as a Service" market place. Significant progress in implementing the following 4 programmatic goals (as outlined in the strategic Plan Ref.1) has been achieved: × Goal #1 Establish a Cloud Computing Infrastructure for the European Research Area (ERA) serving as a platform for innovation and evolution of the overall infrastructure. × Goal #2 Identify and adopt suitable policies for trust, security and privacy on a European-level can be provided by the European Cloud Computing framework and infrastructure. × Goal #3 Create a light-weight governance structure for the future European Cloud Computing Infrastructure that involves all the stakeholders and can evolve over time as the infrastructure, services and user-base grows. × Goal #4 Define a funding scheme involving the three stake-holder groups (service suppliers, users, EC and national funding agencies) into a Public-Private-Partnership model to implement a Cloud Computing Infrastructure that delivers a sustainable business environment adhering to European level policies. Now in 2014 a first version of this generic cross-domain e-infrastructure is ready to go into operations building on federation of European industry and contributors (data, tools, knowledge, ...). This presentation describes how Helix Nebula is being used in the domain of earth science focusing on geohazards. The so called "Supersite Exploitation Platform" (SSEP) provides scientists an overarching federated e-infrastructure with a very fast access to (i) large volume of data (EO/non-space data), (ii) computing resources (e.g. hybrid cloud/grid), (iii) processing software (e.g. toolboxes, RTMs, retrieval baselines, visualization routines), and (iv) general platform capabilities (e.g. user management and access control, accounting, information portal, collaborative tools, social networks etc.). In this federation each data provider remains in full control of the implementation of its data policy. This presentation outlines the Architecture (technical and services) supporting very heterogeneous science domains as well as the procedures for new-comers to join the Helix Nebula Market Place. Ref.1 http://cds.cern.ch/record/1374172/files/CERN-OPEN-2011-036.pdf

Advanced space-based InSAR risk analysis of planned and existing transportation infrastructure.

DOT National Transportation Integrated Search

2017-03-21

The purpose of this document is to summarize activities by Stanford University and : MDA Geospatial Services Inc. (MDA) to estimate surface deformation and associated : risk to transportation infrastructure using SAR Interferometric methods for the :...

Advancing innovative high-speed remote-sensing highway infrastructure assessment using emerging technologies : technical report.

DOT National Transportation Integrated Search

2017-02-01

Asset management is a strategic approach to the optimal allocation of resources for the management, operation, maintenance, and preservation of transportation infrastructure. Asset management combines engineering and economic principles with sound bu...

Preparing to use vehicle infrastructure integration in transportation operations : phase I.

DOT National Transportation Integrated Search

2007-01-01

The close integration of vehicles and the infrastructure in the surface transportation system has been envisioned for years, but recent advances in wireless communications has made such integration feasible. Given this feasibility, a coalition of the...

Cybernation : the American infrastructure in the information age : a technical primer on risks and reliability

DOT National Transportation Integrated Search

1997-04-01

The infrastructure on which American society depends, in sectors such as transportation, finance, energy, and telecommunications is becoming increasingly automated as advances in information technology open up new possibilities for improved service, ...

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

Grid Computing and Collaboration Technology in Support of Fusion Energy Sciences

NASA Astrophysics Data System (ADS)

Schissel, D. P.

2004-11-01

The SciDAC Initiative is creating a computational grid designed to advance scientific understanding in fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling, and allowing more efficient use of experimental facilities. The philosophy is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as easy to use network available services. Access to services is stressed rather than portability. Services share the same basic security infrastructure so that stakeholders can control their own resources and helps ensure fair use of resources. The collaborative control room is being developed using the open-source Access Grid software that enables secure group-to-group collaboration with capabilities beyond teleconferencing including application sharing and control. The ability to effectively integrate off-site scientists into a dynamic control room will be critical to the success of future international projects like ITER. Grid computing, the secure integration of computer systems over high-speed networks to provide on-demand access to data analysis capabilities and related functions, is being deployed as an alternative to traditional resource sharing among institutions. The first grid computational service deployed was the transport code TRANSP and included tools for run preparation, submission, monitoring and management. This approach saves user sites from the laborious effort of maintaining a complex code while at the same time reducing the burden on developers by avoiding the support of a large number of heterogeneous installations. This tutorial will present the philosophy behind an advanced collaborative environment, give specific examples, and discuss its usage beyond FES.

Integration of Cloud resources in the LHCb Distributed Computing

NASA Astrophysics Data System (ADS)

Úbeda García, Mario; Méndez Muñoz, Víctor; Stagni, Federico; Cabarrou, Baptiste; Rauschmayr, Nathalie; Charpentier, Philippe; Closier, Joel

2014-06-01

This contribution describes how Cloud resources have been integrated in the LHCb Distributed Computing. LHCb is using its specific Dirac extension (LHCbDirac) as an interware for its Distributed Computing. So far, it was seamlessly integrating Grid resources and Computer clusters. The cloud extension of DIRAC (VMDIRAC) allows the integration of Cloud computing infrastructures. It is able to interact with multiple types of infrastructures in commercial and institutional clouds, supported by multiple interfaces (Amazon EC2, OpenNebula, OpenStack and CloudStack) - instantiates, monitors and manages Virtual Machines running on this aggregation of Cloud resources. Moreover, specifications for institutional Cloud resources proposed by Worldwide LHC Computing Grid (WLCG), mainly by the High Energy Physics Unix Information Exchange (HEPiX) group, have been taken into account. Several initiatives and computing resource providers in the eScience environment have already deployed IaaS in production during 2013. Keeping this on mind, pros and cons of a cloud based infrasctructure have been studied in contrast with the current setup. As a result, this work addresses four different use cases which represent a major improvement on several levels of our infrastructure. We describe the solution implemented by LHCb for the contextualisation of the VMs based on the idea of Cloud Site. We report on operational experience of using in production several institutional Cloud resources that are thus becoming integral part of the LHCb Distributed Computing resources. Furthermore, we describe as well the gradual migration of our Service Infrastructure towards a fully distributed architecture following the Service as a Service (SaaS) model.

An Immersed Boundary Method for Solving the Compressible Navier-Stokes Equations with Fluid Structure Interaction

NASA Technical Reports Server (NTRS)

Brehm, Christoph; Barad, Michael F.; Kiris, Cetin C.

2016-01-01

An immersed boundary method for the compressible Navier-Stokes equation and the additional infrastructure that is needed to solve moving boundary problems and fully coupled fluid-structure interaction is described. All the methods described in this paper were implemented in NASA's LAVA solver framework. The underlying immersed boundary method is based on the locally stabilized immersed boundary method that was previously introduced by the authors. In the present paper this method is extended to account for all aspects that are involved for fluid structure interaction simulations, such as fast geometry queries and stencil computations, the treatment of freshly cleared cells, and the coupling of the computational fluid dynamics solver with a linear structural finite element method. The current approach is validated for moving boundary problems with prescribed body motion and fully coupled fluid structure interaction problems in 2D and 3D. As part of the validation procedure, results from the second AIAA aeroelastic prediction workshop are also presented. The current paper is regarded as a proof of concept study, while more advanced methods for fluid structure interaction are currently being investigated, such as geometric and material nonlinearities, and advanced coupling approaches.

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

PubMed

Dinov, Ivo D

2016-01-01

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

Optimization of tomographic reconstruction workflows on geographically distributed resources

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar; ...

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

Optimization of tomographic reconstruction workflows on geographically distributed resources

PubMed Central

Bicer, Tekin; Gürsoy, Doǧa; Kettimuthu, Rajkumar; De Carlo, Francesco; Foster, Ian T.

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Moreover, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks. PMID:27359149

Optimization of tomographic reconstruction workflows on geographically distributed resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

A Grid Infrastructure for Supporting Space-based Science Operations

NASA Technical Reports Server (NTRS)

Bradford, Robert N.; Redman, Sandra H.; McNair, Ann R. (Technical Monitor)

2002-01-01

Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.

Foundational Tools for Petascale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Barton

2014-05-19

The Paradyn project has a history of developing algorithms, techniques, and software that push the cutting edge of tool technology for high-end computing systems. Under this funding, we are working on a three-year agenda to make substantial new advances in support of new and emerging Petascale systems. The overall goal for this work is to address the steady increase in complexity of these petascale systems. Our work covers two key areas: (1) The analysis, instrumentation and control of binary programs. Work in this area falls under the general framework of the Dyninst API tool kits. (2) Infrastructure for building toolsmore » and applications at extreme scale. Work in this area falls under the general framework of the MRNet scalability framework. Note that work done under this funding is closely related to work done under a contemporaneous grant, “High-Performance Energy Applications and Systems”, SC0004061/FG02-10ER25972, UW PRJ36WV.« less

Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

PubMed

Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

2009-01-01

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

Preserving differential privacy for similarity measurement in smart environments.

PubMed

Wong, Kok-Seng; Kim, Myung Ho

2014-01-01

Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people's life and living styles. However, collecting and storing user's data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection is now an emerging issue that we need to consider especially when data sharing is essential for analysis purpose. In this paper, we consider the case where two agents in the smart environment want to measure the similarity of their collected or stored data. We use similarity coefficient function (F SC) as the measurement metric for the comparison with differential privacy model. Unlike the existing solutions, our protocol can facilitate more than one request to compute F SC without modifying the protocol. Our solution ensures privacy protection for both the inputs and the computed F SC results.

Diamond Eye: a distributed architecture for image data mining

NASA Astrophysics Data System (ADS)

Burl, Michael C.; Fowlkes, Charless; Roden, Joe; Stechert, Andre; Mukhtar, Saleem

1999-02-01

Diamond Eye is a distributed software architecture, which enables users (scientists) to analyze large image collections by interacting with one or more custom data mining servers via a Java applet interface. Each server is coupled with an object-oriented database and a computational engine, such as a network of high-performance workstations. The database provides persistent storage and supports querying of the 'mined' information. The computational engine provides parallel execution of expensive image processing, object recognition, and query-by-content operations. Key benefits of the Diamond Eye architecture are: (1) the design promotes trial evaluation of advanced data mining and machine learning techniques by potential new users (all that is required is to point a web browser to the appropriate URL), (2) software infrastructure that is common across a range of science mining applications is factored out and reused, and (3) the system facilitates closer collaborations between algorithm developers and domain experts.

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles.

PubMed

Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V; Imran, Muhammad; Zhou, Keliang

2016-01-11

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

Geoinformatics in the public service: building a cyberinfrastructure across the geological surveys

USGS Publications Warehouse

Allison, M. Lee; Gundersen, Linda C.; Richard, Stephen M.; Keller, G. Randy; Baru, Chaitanya

2011-01-01

Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

PubMed Central

Wan, Jiafu; Liu, Jianqi; Shao, Zehui; Vasilakos, Athanasios V.; Imran, Muhammad; Zhou, Keliang

2016-01-01

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction. PMID:26761013

Alternative Fuels Data Center

Science.gov Websites

jobs, economic growth, tax relief, improvements in education and healthcare, infrastructure of alternative fuel and advanced vehicle technologies through grant programs, tax credits, research Section 1123 amends the alternative fuel infrastructure tax credit for qualified equipment placed into

Examination of State-of-the-Art Rehabilitation Technologies for the Nation's Water Infrastructure - slides

EPA Science Inventory

The research overview of the US EPA Aging Water Infrastructure Research Program includes: Research areas: condition assessment; rehabilitation; advanced design/treatment concepts and Research project focused on innovative rehabilitation technologies to reduce costs and increase...

Quantifying Online Learning Contact Hours

ERIC Educational Resources Information Center

Powell, Karan; Helm, Jennifer Stephens; Layne, Melissa; Ice, Phil

2012-01-01

Technological and pedagogical advances in distance education have accentuated the necessity for higher education to keep pace regarding institutional infrastructures. Each infrastructure--driven by a common mission to provide quality learning--interprets quality according to standards established by various governmental and accrediting entities.…

Energy Theft in the Advanced Metering Infrastructure

NASA Astrophysics Data System (ADS)

McLaughlin, Stephen; Podkuiko, Dmitry; McDaniel, Patrick

Global energy generation and delivery systems are transitioning to a new computerized "smart grid". One of the principle components of the smart grid is an advanced metering infrastructure (AMI). AMI replaces the analog meters with computerized systems that report usage over digital communication interfaces, e.g., phone lines. However, with this infrastructure comes new risk. In this paper, we consider adversary means of defrauding the electrical grid by manipulating AMI systems. We document the methods adversaries will use to attempt to manipulate energy usage data, and validate the viability of these attacks by performing penetration testing on commodity devices. Through these activities, we demonstrate that not only is theft still possible in AMI systems, but that current AMI devices introduce a myriad of new vectors for achieving it.

Network Computing Infrastructure to Share Tools and Data in Global Nuclear Energy Partnership

NASA Astrophysics Data System (ADS)

Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer-Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP.

Geospatial-enabled Data Exploration and Computation through Data Infrastructure Building Blocks

NASA Astrophysics Data System (ADS)

Song, C. X.; Biehl, L. L.; Merwade, V.; Villoria, N.

2015-12-01

Geospatial data are present everywhere today with the proliferation of location-aware computing devices and sensors. This is especially true in the scientific community where large amounts of data are driving research and education activities in many domains. Collaboration over geospatial data, for example, in modeling, data analysis and visualization, must still overcome the barriers of specialized software and expertise among other challenges. The GABBs project aims at enabling broader access to geospatial data exploration and computation by developing spatial data infrastructure building blocks that leverage capabilities of end-to-end application service and virtualized computing framework in HUBzero. Funded by NSF Data Infrastructure Building Blocks (DIBBS) initiative, GABBs provides a geospatial data architecture that integrates spatial data management, mapping and visualization and will make it available as open source. The outcome of the project will enable users to rapidly create tools and share geospatial data and tools on the web for interactive exploration of data without requiring significant software development skills, GIS expertise or IT administrative privileges. This presentation will describe the development of geospatial data infrastructure building blocks and the scientific use cases that help drive the software development, as well as seek feedback from the user communities.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

NASA Astrophysics Data System (ADS)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

2014-06-01

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared overmore » the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.« less

ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

PubMed

Neves Tafula, Sérgio M; Moreira da Silva, Nádia; Rozanski, Verena E; Silva Cunha, João Paulo

2014-01-01

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability.

Computational simulation of concurrent engineering for aerospace propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1992-01-01

Results are summarized of an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulations methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties - fundamental in developing such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering for propulsion systems and systems in general. Benefits and facets needing early attention in the development are outlined.

Computational simulation for concurrent engineering of aerospace propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.

Computational simulation for concurrent engineering of aerospace propulsion systems

NASA Astrophysics Data System (ADS)

Chamis, C. C.; Singhal, S. N.

1993-02-01

Results are summarized for an investigation to assess the infrastructure available and the technology readiness in order to develop computational simulation methods/software for concurrent engineering. These results demonstrate that development of computational simulation methods for concurrent engineering is timely. Extensive infrastructure, in terms of multi-discipline simulation, component-specific simulation, system simulators, fabrication process simulation, and simulation of uncertainties--fundamental to develop such methods, is available. An approach is recommended which can be used to develop computational simulation methods for concurrent engineering of propulsion systems and systems in general. Benefits and issues needing early attention in the development are outlined.

A service-based BLAST command tool supported by cloud infrastructures.

PubMed

Carrión, Abel; Blanquer, Ignacio; Hernández, Vicente

2012-01-01

Notwithstanding the benefits of distributed-computing infrastructures for empowering bioinformatics analysis tools with the needed computing and storage capability, the actual use of these infrastructures is still low. Learning curves and deployment difficulties have reduced the impact on the wide research community. This article presents a porting strategy of BLAST based on a multiplatform client and a service that provides the same interface as sequential BLAST, thus reducing learning curve and with minimal impact on their integration on existing workflows. The porting has been done using the execution and data access components from the EC project Venus-C and the Windows Azure infrastructure provided in this project. The results obtained demonstrate a low overhead on the global execution framework and reasonable speed-up and cost-efficiency with respect to a sequential version.

Grids, virtualization, and clouds at Fermilab

DOE PAGES

Timm, S.; Chadwick, K.; Garzoglio, G.; ...

2014-06-11

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture andmore » the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.« less

Grids, virtualization, and clouds at Fermilab

NASA Astrophysics Data System (ADS)

Timm, S.; Chadwick, K.; Garzoglio, G.; Noh, S.

2014-06-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). This work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

State-of-the-art survey of advanced materials and their potential application in highway infrastructure.

DOT National Transportation Integrated Search

2004-01-01

This study attempted to identify new materials that might have applications in highway infrastructure that could lead to savings for the Virginia Department of Transportation (VDOT) and other transportation agencies. This search identified 47 materia...

Advanced Decentralized Water/Energy Network Design for Sustainable Infrastructure

EPA Science Inventory

In order to provide a water infrastructure that is more sustainable into and beyond the 21st century, drinking water distribution systems and wastewater collection systems must account for our diminishing water supply, increasing demands, climate change, energy cost and availabil...

Advanced Development of Certified OS Kernels

DTIC Science & Technology

2015-06-01

It provides an infrastructure to map a physical page into multiple processes’ page maps in different address spaces. Their ownership mechanism ensures...of their shared memory infrastructure . Trap module The trap module specifies the behaviors of exception handlers and mCertiKOS system calls. In...layers), 1 pm for the shared memory infrastructure (3 layers), 3.5 pm for the thread management (10 layers), 1 pm for the process management (4 layers

The department of transportation's advanced materials research and technology initiatives

DOT National Transportation Integrated Search

1995-02-28

This report provides an overview of DOT's current research and technology efforts, as well as those planned for Fiscal Year (FY) 1996, in two major areas: 1) Advanced Materials Research for Transportation Infrastructure, and 2) Advanced Materials Res...

Enabling Data Intensive Science through Service Oriented Science: Virtual Laboratories and Science Gateways

NASA Astrophysics Data System (ADS)

Lescinsky, D. T.; Wyborn, L. A.; Evans, B. J. K.; Allen, C.; Fraser, R.; Rankine, T.

2014-12-01

We present collaborative work on a generic, modular infrastructure for virtual laboratories (VLs, similar to science gateways) that combine online access to data, scientific code, and computing resources as services that support multiple data intensive scientific computing needs across a wide range of science disciplines. We are leveraging access to 10+ PB of earth science data on Lustre filesystems at Australia's National Computational Infrastructure (NCI) Research Data Storage Infrastructure (RDSI) node, co-located with NCI's 1.2 PFlop Raijin supercomputer and a 3000 CPU core research cloud. The development, maintenance and sustainability of VLs is best accomplished through modularisation and standardisation of interfaces between components. Our approach has been to break up tightly-coupled, specialised application packages into modules, with identified best techniques and algorithms repackaged either as data services or scientific tools that are accessible across domains. The data services can be used to manipulate, visualise and transform multiple data types whilst the scientific tools can be used in concert with multiple scientific codes. We are currently designing a scalable generic infrastructure that will handle scientific code as modularised services and thereby enable the rapid/easy deployment of new codes or versions of codes. The goal is to build open source libraries/collections of scientific tools, scripts and modelling codes that can be combined in specially designed deployments. Additional services in development include: provenance, publication of results, monitoring, workflow tools, etc. The generic VL infrastructure will be hosted at NCI, but can access alternative computing infrastructures (i.e., public/private cloud, HPC).The Virtual Geophysics Laboratory (VGL) was developed as a pilot project to demonstrate the underlying technology. This base is now being redesigned and generalised to develop a Virtual Hazards Impact and Risk Laboratory (VHIRL); any enhancements and new capabilities will be incorporated into a generic VL infrastructure. At same time, we are scoping seven new VLs and in the process, identifying other common components to prioritise and focus development.

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

PubMed

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI).

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System

PubMed Central

Passerat-Palmbach, Jonathan; Reuillon, Romain; Leclaire, Mathieu; Makropoulos, Antonios; Robinson, Emma C.; Parisot, Sarah; Rueckert, Daniel

2017-01-01

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI). PMID:28381997

Cloud computing applications for biomedical science: A perspective.

PubMed

Navale, Vivek; Bourne, Philip E

2018-06-01

Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

Cloud computing applications for biomedical science: A perspective

PubMed Central

2018-01-01

Biomedical research has become a digital data–intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research. PMID:29902176

Remote third shift EAST operation: a new paradigm

NASA Astrophysics Data System (ADS)

Schissel, D. P.; Coviello, E.; Eidietis, N.; Flanagan, S.; Garcia, F.; Humphreys, D.; Kostuk, M.; Lanctot, M.; Lee, X.; Margo, M.; Miller, D.; Parker, C.; Penaflor, B.; Qian, J. P.; Sun, X.; Tan, H.; Walker, M.; Xiao, B.; Yuan, Q.

2017-05-01

General Atomics’ (GA) scientists in the United States remotely conducted experimental operation of the experimental advanced superconducting tokamak (EAST) in China during its third shift. Scientists led these experiments in a dedicated remote control room that utilized a novel computer science hardware and software infrastructure to allow data movement, visualization, and communication on the time scale of EAST’s pulse cycle. This Fusion Science Collaboration Zone infrastructure allows the movement of large amounts of data between continents in a short time scale with a 300-fold increase in data transfer rate over that available using the traditional transmission protocol. Real-time data from control systems is moved almost instantaneously. An event system tied to the EAST pulse cycle allows automatic initiation of data transfers, resulting in bulk EAST data to be transferred to GA within minutes. The EAST data at GA is served via MDSplus to approved US collaborators avoiding multiple US clients from requesting data from EAST and competing for the long-haul network’s bandwidth. At present there are 37 approved scientists from 8 US research institutions.

New paradigms in telemedicine: ambient intelligence, wearable, pervasive and personalized.

PubMed

Rubel, Paul; Fayn, Jocelyne; Simon-Chautemps, Lucas; Atoui, Hussein; Ohlsson, Mattias; Telisson, David; Adami, Stefano; Arod, Sébastien; Forlini, Marie Claire; Malossi, Cesare; Placide, Joël; Ziliani, Gian Luca; Assanelli, Deodato; Chevalier, Philippe

2004-01-01

After decades of development of information systems dedicated to health professionals, there is an increasing demand for personalized and non-hospital based care. An especially critical domain is cardiology: almost two third of cardiac deaths occur out of hospital, and victims do not survive long enough to benefit from in-hospital treatments. We need to reduce the time before treatment. But symptoms are often interpreted wrongly. The only immediate diagnostic tool to assess the possibility of a cardiac event is the electrocardiogram (ECG). Event and transtelephonic ECG recorders are used to improve decision making but require setting up new infrastructures. The European EPI-MEDICS project has developed an intelligent Personal ECG Monitor (PEM) for the early detection of cardiac events. The PEM embeds advanced decision making techniques, generates different alarm levels and forwards alarm messages to the relevant care providers by means of new generation wireless communication. It is cost saving, involving care provider only if necessary and requiring no specific infrastructure. This solution is a typical example of pervasive computing and ambient intelligence that demonstrates how personalized, wearable, ubiquitous devices could improve healthcare.

National Computational Infrastructure for Lattice Gauge Theory SciDAC-2 Closeout Report Indiana University Component

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gottlieb, Steven Arthur; DeTar, Carleton; Tousaint, Doug

This is the closeout report for the Indiana University portion of the National Computational Infrastructure for Lattice Gauge Theory project supported by the United States Department of Energy under the SciDAC program. It includes information about activities at Indian University, the University of Arizona, and the University of Utah, as those three universities coordinated their activities.

Deploying Crowd-Sourced Formal Verification Systems in a DoD Network

DTIC Science & Technology

2013-09-01

INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION A. INTRODUCTION In 2014 cyber attacks on critical infrastructure are expected to increase...CSFV systems on the Internet‒‒possibly using cloud infrastructure (Dean, 2013). By using Amazon Compute Cloud (EC2) systems, DARPA will use ordinary...through standard access methods. Those clients could be mobile phones, laptops, netbooks, tablet computers or personal digital assistants (PDAs) (Smoot

#WomenInSTEM: Identifying an Opportunity for Change

ScienceCinema

Lefkowitz, Karen

2018-01-16

Karen Lefkowitz remembers being the only woman in the room thirty years ago at a conference when she started her career off as a computer programmer. Karen is a firm supporter of mentors and states that women, no matter whether they're in science or any other career, should ask for someone to mentor them. Karen is currently Vice President of Business Transformation at Pepco Holdings, Inc. She is responsible for the deployment of Advanced Metering Infrastructure (AMI) meters, a Department of Energy funded project, in Delaware, DC and Maryland. The meters have a two-way wireless communication that provides hourly consumption data at the premise allowing customers to take control of their energy use.

Methods and successes of New York University workshops for science graduate students and post-docs in science writing for general audiences (readers and radio listeners)

NASA Astrophysics Data System (ADS)

Hall, S. S.

2012-12-01

Scientists and science administrators often stress the importance of communication to the general public, but rarely develop educational infrastructures to achieve this goal. Since 2009, the Arthur L. Carter Journalism Institute at New York University has offered a series of basic and advanced writing workshops for graduate students and post-docs in NYU's eight scientific divisions (neuroscience, psychology, physics, biology, chemistry, mathematics, anthropology, and computer science). The basic methodology of the NYU approach will be described, along with successful examples of both written and radio work by students that have been either published or broadcast by general interest journalism outlets.

Energy Systems Integration Facility (ESIF): Golden, CO - Energy Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheppy, Michael; VanGeet, Otto; Pless, Shanti

2015-03-01

At NREL's Energy Systems Integration Facility (ESIF) in Golden, Colo., scientists and engineers work to overcome challenges related to how the nation generates, delivers and uses energy by modernizing the interplay between energy sources, infrastructure, and data. Test facilities include a megawatt-scale ac electric grid, photovoltaic simulators and a load bank. Additionally, a high performance computing data center (HPCDC) is dedicated to advancing renewable energy and energy efficient technologies. A key design strategy is to use waste heat from the HPCDC to heat parts of the building. The ESIF boasts an annual EUI of 168.3 kBtu/ft2. This article describes themore » building's procurement, design and first year of performance.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lefkowitz, Karen

Karen Lefkowitz remembers being the only woman in the room thirty years ago at a conference when she started her career off as a computer programmer. Karen is a firm supporter of mentors and states that women, no matter whether they're in science or any other career, should ask for someone to mentor them. Karen is currently Vice President of Business Transformation at Pepco Holdings, Inc. She is responsible for the deployment of Advanced Metering Infrastructure (AMI) meters, a Department of Energy funded project, in Delaware, DC and Maryland. The meters have a two-way wireless communication that provides hourly consumptionmore » data at the premise allowing customers to take control of their energy use.« less

Applicability of microelectronic and mechanical systems (MEMS) for transportation infrastructure management.

DOT National Transportation Integrated Search

2008-08-11

It will be advantageous to have information on the state of health of infrastructure at all times in : order to carry out effective on-demand maintenance. With the tremendous advancement in technology, it is : possible to employ devices embedded in s...

Evaluation of intelligent transportation infrastructure program (ITIP) in Pittsburgh and Philadelphia, Pennsylvania

DOT National Transportation Integrated Search

2003-03-20

The Transportation Equity Act for the 21st Century (TEA-21) Public Laws 105-178 and 105-206, Title V, Section 5117(b) (3) provides for an Intelligent Transportation Infrastructure Program (ITIP) to advance the deployment of operational intelligent tr...

Leading by Success: Impact of a Clinical & Translational Research Infrastructure Program to Address Health Inequities

PubMed Central

Shiramizu, Bruce; Shambaugh, Vicki; Petrovich, Helen; Seto, Todd B.; Ho, Tammy; Mokuau, Noreen; Hedges, Jerris R.

2016-01-01

Building research infrastructure capacity to address clinical and translational gaps has been a focus of funding agencies and foundations. Clinical and Translational Sciences Awards, Research Centers in Minority Institutions Infrastructure for Clinical and Translational Research (RCTR) and the Institutional Development Award Infrastructure for Clinical and Translational Research funded by United States (US) government to fund clinical translational research programs have existed for over a decade to address racial and ethnic health disparities across the US. While the impact on the nation’s health can’t be made in a short period, assessment of a program’s impact could be a litmus test to gauge its effectiveness at the institution and communities. We report the success of a Pilot Project Program in the University of Hawaii RCTR Award in advancing careers of emerging investigators and community collaborators. Our findings demonstrated that the investment has a far-reaching impact on engagement with community-based research collaborators, career advancement of health disparities investigators, and favorable impacts on health policy. PMID:27797013

Modernization of the USGS Hawaiian Volcano Observatory Seismic Processing Infrastructure

NASA Astrophysics Data System (ADS)

Antolik, L.; Shiro, B.; Friberg, P. A.

2016-12-01

The USGS Hawaiian Volcano Observatory (HVO) operates a Tier 1 Advanced National Seismic System (ANSS) seismic network to monitor, characterize, and report on volcanic and earthquake activity in the State of Hawaii. Upgrades at the observatory since 2009 have improved the digital telemetry network, computing resources, and seismic data processing with the adoption of the ANSS Quake Management System (AQMS) system. HVO aims to build on these efforts by further modernizing its seismic processing infrastructure and strengthen its ability to meet ANSS performance standards. Most notably, this will also allow HVO to support redundant systems, both onsite and offsite, in order to provide better continuity of operation during intermittent power and network outages. We are in the process of implementing a number of upgrades and improvements on HVO's seismic processing infrastructure, including: 1) Virtualization of AQMS physical servers; 2) Migration of server operating systems from Solaris to Linux; 3) Consolidation of AQMS real-time and post-processing services to a single server; 4) Upgrading database from Oracle 10 to Oracle 12; and 5) Upgrading to the latest Earthworm and AQMS software. These improvements will make server administration more efficient, minimize hardware resources required by AQMS, simplify the Oracle replication setup, and provide better integration with HVO's existing state of health monitoring tools and backup system. Ultimately, it will provide HVO with the latest and most secure software available while making the software easier to deploy and support.

To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne

2012-08-01

A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.

Scaling the CERN OpenStack cloud

NASA Astrophysics Data System (ADS)

Bell, T.; Bompastor, B.; Bukowiec, S.; Castro Leon, J.; Denis, M. K.; van Eldik, J.; Fermin Lobo, M.; Fernandez Alvarez, L.; Fernandez Rodriguez, D.; Marino, A.; Moreira, B.; Noel, B.; Oulevey, T.; Takase, W.; Wiebalck, A.; Zilli, S.

2015-12-01

CERN has been running a production OpenStack cloud since July 2013 to support physics computing and infrastructure services for the site. In the past year, CERN Cloud Infrastructure has seen a constant increase in nodes, virtual machines, users and projects. This paper will present what has been done in order to make the CERN cloud infrastructure scale out.

Science of Security Lablet - Scalability and Usability

DTIC Science & Technology

2014-12-16

mobile computing [19]. However, the high-level infrastructure design and our own implementation (both described throughout this paper) can easily...critical and infrastructural systems demands high levels of sophistication in the technical aspects of cybersecurity, software and hardware design...Forget, S. Komanduri, Alessandro Acquisti, Nicolas Christin, Lorrie Cranor, Rahul Telang. "Security Behavior Observatory: Infrastructure for Long-term

Performance measurement and modeling of component applications in a high performance computing environment : a case study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armstrong, Robert C.; Ray, Jaideep; Malony, A.

2003-11-01

We present a case study of performance measurement and modeling of a CCA (Common Component Architecture) component-based application in a high performance computing environment. We explore issues peculiar to component-based HPC applications and propose a performance measurement infrastructure for HPC based loosely on recent work done for Grid environments. A prototypical implementation of the infrastructure is used to collect data for a three components in a scientific application and construct performance models for two of them. Both computational and message-passing performance are addressed.

Role of Computational Fluid Dynamics and Wind Tunnels in Aeronautics R and D

NASA Technical Reports Server (NTRS)

Malik, Murjeeb R.; Bushnell, Dennis M.

2012-01-01

The purpose of this report is to investigate the status and future projections for the question of supplantation of wind tunnels by computation in design and to intuit the potential impact of computation approaches on wind-tunnel utilization all with an eye toward reducing the infrastructure cost at aeronautics R&D centers. Wind tunnels have been closing for myriad reasons, and such closings have reduced infrastructure costs. Further cost reductions are desired, and the work herein attempts to project which wind-tunnel capabilities can be replaced in the future and, if possible, the timing of such. If the possibility exists to project when a facility could be closed, then maintenance and other associated costs could be rescheduled accordingly (i.e., before the fact) to obtain an even greater infrastructure cost reduction.

Evolution of a Materials Data Infrastructure

NASA Astrophysics Data System (ADS)

Warren, James A.; Ward, Charles H.

2018-06-01

The field of materials science and engineering is writing a new chapter in its evolution, one of digitally empowered materials discovery, development, and deployment. The 2008 Integrated Computational Materials Engineering (ICME) study report helped usher in this paradigm shift, making a compelling case and strong recommendations for an infrastructure supporting ICME that would enable access to precompetitive materials data for both scientific and engineering applications. With the launch of the Materials Genome Initiative in 2011, which drew substantial inspiration from the ICME study, digital data was highlighted as a core component of a Materials Innovation Infrastructure, along with experimental and computational tools. Over the past 10 years, our understanding of what it takes to provide accessible materials data has matured and rapid progress has been made in establishing a Materials Data Infrastructure (MDI). We are learning that the MDI is essential to eliminating the seams between experiment and computation by providing a means for them to connect effortlessly. Additionally, the MDI is becoming an enabler, allowing materials engineering to tie into a much broader model-based engineering enterprise for product design.

Research Challenges in Water Infrastructure Condition Assessment, Rehabilitation and System Optimization – The U.S. Perspective

EPA Science Inventory

This presentation first provides an overview of U.S.EPA research activities on water infrastructure condition assessment, system rehabilitation, and asset management. It then describes in detail specific activities in pipe leak detection, water conservation and the advanced wate...

Information technology developments within the national biological information infrastructure

USGS Publications Warehouse

Cotter, G.; Frame, M.T.

2000-01-01

Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

Use of agents to implement an integrated computing environment

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implement the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.

EGI-EUDAT integration activity - Pair data and high-throughput computing resources together

NASA Astrophysics Data System (ADS)

Scardaci, Diego; Viljoen, Matthew; Vitlacil, Dejan; Fiameni, Giuseppe; Chen, Yin; sipos, Gergely; Ferrari, Tiziana

2016-04-01

EGI (www.egi.eu) is a publicly funded e-infrastructure put together to give scientists access to more than 530,000 logical CPUs, 200 PB of disk capacity and 300 PB of tape storage to drive research and innovation in Europe. The infrastructure provides both high throughput computing and cloud compute/storage capabilities. Resources are provided by about 350 resource centres which are distributed across 56 countries in Europe, the Asia-Pacific region, Canada and Latin America. EUDAT (www.eudat.eu) is a collaborative Pan-European infrastructure providing research data services, training and consultancy for researchers, research communities, research infrastructures and data centres. EUDAT's vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europe's largest scientific data centres. EGI and EUDAT, in the context of their flagship projects, EGI-Engage and EUDAT2020, started in March 2015 a collaboration to harmonise the two infrastructures, including technical interoperability, authentication, authorisation and identity management, policy and operations. The main objective of this work is to provide end-users with a seamless access to an integrated infrastructure offering both EGI and EUDAT services and, then, pairing data and high-throughput computing resources together. To define the roadmap of this collaboration, EGI and EUDAT selected a set of relevant user communities, already collaborating with both infrastructures, which could bring requirements and help to assign the right priorities to each of them. In this way, from the beginning, this activity has been really driven by the end users. The identified user communities are relevant European Research infrastructure in the field of Earth Science (EPOS and ICOS), Bioinformatics (BBMRI and ELIXIR) and Space Physics (EISCAT-3D). The first outcome of this activity has been the definition of a generic use case that captures the typical user scenario with respect the integrated use of the EGI and EUDAT infrastructures. This generic use case allows a user to instantiate a set of Virtual Machine images on the EGI Federated Cloud to perform computational jobs that analyse data previously stored on EUDAT long-term storage systems. The results of such analysis can be staged back to EUDAT storages, and if needed, allocated with Permanent identifyers (PIDs) for future use. The implementation of this generic use case requires the following integration activities between EGI and EUDAT: (1) harmonisation of the user authentication and authorisation models, (2) implementing interface connectors between the relevant EGI and EUDAT services, particularly EGI Cloud compute facilities and EUDAT long-term storage and PID systems. In the presentation, the collected user requirements and the implementation status of the universal use case will be showed. Furthermore, how the universal use case is currently applied to satisfy EPOS and ICOS needs will be described.

Benchmarking infrastructure for mutation text mining

PubMed Central

2014-01-01

Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

Benchmarking infrastructure for mutation text mining.

PubMed

Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

2014-02-25

Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure1. PMID:24795619

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2012 CFR

2012-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2013 CFR

2013-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

32 CFR 240.4 - Policy.

Code of Federal Regulations, 2014 CFR

2014-07-01

... enterprise information infrastructure requirements. (c) The academic disciplines, with concentrations in IA..., computer systems analysis, cyber operations, cybersecurity, database administration, data management... infrastructure development and academic research to support the DoD IA/IT critical areas of interest. ...

Acquisition of specialized testing equipment for advanced cement-based materials.

DOT National Transportation Integrated Search

2014-07-01

This equipment purchase will enabled the development, manufacturing, and implementation of advanced and sustainable materials for transportation infrastructure, with emphasis on concrete. The developments of green technologies that can lead to ...

Flexible Description and Adaptive Processing of Earth Observation Data through the BigEarth Platform

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Bacu, Victor; Stefanut, Teodor; Nandra, Cosmin; Mihon, Danut

2016-04-01

The Earth Observation data repositories extending periodically by several terabytes become a critical issue for organizations. The management of the storage capacity of such big datasets, accessing policy, data protection, searching, and complex processing require high costs that impose efficient solutions to balance the cost and value of data. Data can create value only when it is used, and the data protection has to be oriented toward allowing innovation that sometimes depends on creative people, which achieve unexpected valuable results through a flexible and adaptive manner. The users need to describe and experiment themselves different complex algorithms through analytics in order to valorize data. The analytics uses descriptive and predictive models to gain valuable knowledge and information from data analysis. Possible solutions for advanced processing of big Earth Observation data are given by the HPC platforms such as cloud. With platforms becoming more complex and heterogeneous, the developing of applications is even harder and the efficient mapping of these applications to a suitable and optimum platform, working on huge distributed data repositories, is challenging and complex as well, even by using specialized software services. From the user point of view, an optimum environment gives acceptable execution times, offers a high level of usability by hiding the complexity of computing infrastructure, and supports an open accessibility and control to application entities and functionality. The BigEarth platform [1] supports the entire flow of flexible description of processing by basic operators and adaptive execution over cloud infrastructure [2]. The basic modules of the pipeline such as the KEOPS [3] set of basic operators, the WorDeL language [4], the Planner for sequential and parallel processing, and the Executor through virtual machines, are detailed as the main components of the BigEarth platform [5]. The presentation exemplifies the development of some Earth Observation oriented applications based on flexible description of processing, and adaptive and portable execution over Cloud infrastructure. Main references for further information: [1] BigEarth project, http://cgis.utcluj.ro/projects/bigearth [2] Gorgan, D., "Flexible and Adaptive Processing of Earth Observation Data over High Performance Computation Architectures", International Conference and Exhibition Satellite 2015, August 17-19, Houston, Texas, USA. [3] Mihon, D., Bacu, V., Colceriu, V., Gorgan, D., "Modeling of Earth Observation Use Cases through the KEOPS System", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 455-460, (2015). [4] Nandra, C., Gorgan, D., "Workflow Description Language for Defining Big Earth Data Processing Tasks", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp. 461-468, (2015). [5] Bacu, V., Stefan, T., Gorgan, D., "Adaptive Processing of Earth Observation Data on Cloud Infrastructures Based on Workflow Description", Proceedings of the Intelligent Computer Communication and Processing (ICCP), IEEE-Press, pp.444-454, (2015).

Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P

Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify andmore » analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.« less

Current Practice and Infrastructures for Campus Centers of Community Engagement

ERIC Educational Resources Information Center

Welch, Marshall; Saltmarsh, John

2013-01-01

This article provides an overview of current practice and essential infrastructure of campus community engagement centers in their efforts to establish and advance community engagement as part of the college experience. The authors identified key characteristics and the prevalence of activities of community engagement centers at engaged campuses…

Use of Green Infrastructure Integrated with Conventional Gray Infrastructure for Combined Sewer Overflow Control: Kansas City, MO

EPA Science Inventory

Advanced design concepts such as Low Impact Development (LID) and Green Solutions (or upland runoff control techniques) are currently being encouraged by the United States Environmental Protection Agency (EPA) as a management practice to contain and control stormwater at the lot ...

Efficient operating system level virtualization techniques for cloud resources

NASA Astrophysics Data System (ADS)

Ansu, R.; Samiksha; Anju, S.; Singh, K. John

2017-11-01

Cloud computing is an advancing technology which provides the servcies of Infrastructure, Platform and Software. Virtualization and Computer utility are the keys of Cloud computing. The numbers of cloud users are increasing day by day. So it is the need of the hour to make resources available on demand to satisfy user requirements. The technique in which resources namely storage, processing power, memory and network or I/O are abstracted is known as Virtualization. For executing the operating systems various virtualization techniques are available. They are: Full System Virtualization and Para Virtualization. In Full Virtualization, the whole architecture of hardware is duplicated virtually. No modifications are required in Guest OS as the OS deals with the VM hypervisor directly. In Para Virtualization, modifications of OS is required to run in parallel with other OS. For the Guest OS to access the hardware, the host OS must provide a Virtual Machine Interface. OS virtualization has many advantages such as migrating applications transparently, consolidation of server, online maintenance of OS and providing security. This paper briefs both the virtualization techniques and discusses the issues in OS level virtualization.

AIMES Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katz, Daniel S; Jha, Shantenu; Weissman, Jon

2017-01-31

This is the final technical report for the AIMES project. Many important advances in science and engineering are due to large-scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). This is evidenced by missing design principles for DCI, and an absence of generally acceptable and usable distributed computing abstractions. The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scientific distributed applications. AIMES laid the foundations to address the tripartite challenge of dynamic resource management, integrating information, and portable and interoperablemore » distributed applications. Four abstractions were defined and implemented: skeleton, resource bundle, pilot, and execution strategy. The four abstractions were implemented into software modules and then aggregated into the AIMES middleware. This middleware successfully integrates information across the application layer (skeletons) and resource layer (Bundles), derives a suitable execution strategy for the given skeleton and enacts its execution by means of pilots on one or more resources, depending on the application requirements, and resource availabilities and capabilities.« less

AIMES Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weissman, Jon; Katz, Dan; Jha, Shantenu

2017-01-31

This is the final technical report for the AIMES project. Many important advances in science and engineering are due to large scale distributed computing. Notwithstanding this reliance, we are still learning how to design and deploy large-scale production Distributed Computing Infrastructures (DCI). This is evidenced by missing design principles for DCI, and an absence of generally acceptable and usable distributed computing abstractions. The AIMES project was conceived against this backdrop, following on the heels of a comprehensive survey of scientific distributed applications. AIMES laid the foundations to address the tripartite challenge of dynamic resource management, integrating information, and portable andmore » interoperable distributed applications. Four abstractions were defined and implemented: skeleton, resource bundle, pilot, and execution strategy. The four abstractions were implemented into software modules and then aggregated into the AIMES middleware. This middleware successfully integrates information across the application layer (skeletons) and resource layer (Bundles), derives a suitable execution strategy for the given skeleton and enacts its execution by means of pilots on one or more resources, depending on the application requirements, and resource availabilities and capabilities.« less

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

PubMed

Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K; Kalinin, Alexandr; Christou, Nicolas

2016-06-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome , which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the learning assessment protocols.

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions

PubMed Central

Dinov, Ivo D.; Siegrist, Kyle; Pearl, Dennis K.; Kalinin, Alexandr; Christou, Nicolas

2015-01-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome, which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the learning assessment protocols. PMID:27158191

Understanding space weather to shield society: A global road map for 2015-2025 commissioned by COSPAR and ILWS

NASA Astrophysics Data System (ADS)

Schrijver, Carolus J.; Kauristie, Kirsti; Aylward, Alan D.; Denardini, Clezio M.; Gibson, Sarah E.; Glover, Alexi; Gopalswamy, Nat; Grande, Manuel; Hapgood, Mike; Heynderickx, Daniel; Jakowski, Norbert; Kalegaev, Vladimir V.; Lapenta, Giovanni; Linker, Jon A.; Liu, Siqing; Mandrini, Cristina H.; Mann, Ian R.; Nagatsuma, Tsutomu; Nandy, Dibyendu; Obara, Takahiro; Paul O'Brien, T.; Onsager, Terrance; Opgenoorth, Hermann J.; Terkildsen, Michael; Valladares, Cesar E.; Vilmer, Nicole

2015-06-01

There is a growing appreciation that the environmental conditions that we call space weather impact the technological infrastructure that powers the coupled economies around the world. With that comes the need to better shield society against space weather by improving forecasts, environmental specifications, and infrastructure design. We recognize that much progress has been made and continues to be made with a powerful suite of research observatories on the ground and in space, forming the basis of a Sun-Earth system observatory. But the domain of space weather is vast - extending from deep within the Sun to far outside the planetary orbits - and the physics complex - including couplings between various types of physical processes that link scales and domains from the microscopic to large parts of the solar system. Consequently, advanced understanding of space weather requires a coordinated international approach to effectively provide awareness of the processes within the Sun-Earth system through observation-driven models. This roadmap prioritizes the scientific focus areas and research infrastructure that are needed to significantly advance our understanding of space weather of all intensities and of its implications for society. Advancement of the existing system observatory through the addition of small to moderate state-of-the-art capabilities designed to fill observational gaps will enable significant advances. Such a strategy requires urgent action: key instrumentation needs to be sustained, and action needs to be taken before core capabilities are lost in the aging ensemble. We recommend advances through priority focus (1) on observation-based modeling throughout the Sun-Earth system, (2) on forecasts more than 12 h ahead of the magnetic structure of incoming coronal mass ejections, (3) on understanding the geospace response to variable solar-wind stresses that lead to intense geomagnetically-induced currents and ionospheric and radiation storms, and (4) on developing a comprehensive specification of space climate, including the characterization of extreme space storms to guide resilient and robust engineering of technological infrastructures. The roadmap clusters its implementation recommendations by formulating three action pathways, and outlines needed instrumentation and research programs and infrastructure for each of these. An executive summary provides an overview of all recommendations.

SeaDataCloud - further developing the pan-European SeaDataNet infrastructure for marine and ocean data management

NASA Astrophysics Data System (ADS)

Schaap, Dick M. A.; Fichaut, Michele

2017-04-01

SeaDataCloud marks the third phase of developing the pan-European SeaDataNet infrastructure for marine and ocean data management. The SeaDataCloud project is funded by EU and runs for 4 years from 1st November 2016. It succeeds the successful SeaDataNet II (2011 - 2015) and SeaDataNet (2006 - 2011) projects. SeaDataNet has set up and operates a pan-European infrastructure for managing marine and ocean data and is undertaken by National Oceanographic Data Centres (NODC's) and oceanographic data focal points from 34 coastal states in Europe. The infrastructure comprises a network of interconnected data centres and central SeaDataNet portal. The portal provides users a harmonised set of metadata directories and controlled access to the large collections of datasets, managed by the interconnected data centres. The population of directories has increased considerably in cooperation with and involvement in many associated EU projects and initiatives such as EMODnet. SeaDataNet at present gives overview and access to more than 1.9 million data sets for physical oceanography, chemistry, geology, geophysics, bathymetry and biology from more than 100 connected data centres from 34 countries riparian to European seas. SeaDataNet is also active in setting and governing marine data standards, and exploring and establishing interoperability solutions to connect to other e-infrastructures on the basis of standards of ISO (19115, 19139), and OGC (WMS, WFS, CS-W and SWE). Standards and associated SeaDataNet tools are made available at the SeaDataNet portal for wide uptake by data handling and managing organisations. SeaDataCloud aims at further developing standards, innovating services & products, adopting new technologies, and giving more attention to users. Moreover, it is about implementing a cooperation between the SeaDataNet consortium of marine data centres and the EUDAT consortium of e-infrastructure service providers. SeaDataCloud aims at considerably advancing services and increasing their usage by adopting cloud and High Performance Computing technology. SeaDataCloud will empower researchers with a packaged collection of services and tools, tailored to their specific needs, supporting research and enabling generation of added-value products from marine and ocean data. Substantial activities will be focused on developing added-value services, such as data subsetting, analysis, visualisation, and publishing workflows for users, both regular and advanced users, as part of a Virtual Research Environment (VRE). SeaDataCloud aims at a number of leading user communities that have new challenges for upgrading and expanding the SeaDataNet standards and services: Science, EMODnet, Copernicus Marine Environmental Monitoring Service (CMEMS) and EuroGOOS, and International scientific programmes. The presentation will give information on present services of the SeaDataNet infrastructure and services, and the new challenges in SeaDataCloud, and will highlight a number of key achievements in SeaDataCloud so far.

GEO Supersites Data Exploitation Platform

NASA Astrophysics Data System (ADS)

Lengert, W.; Popp, H.-J.; Gleyzes, J.-P.

2012-04-01

In the framework of the GEO Geohazard Supersite initiative, an international partnership of organizations and scientists involved in the monitoring and assessment of geohazards has been established. The mission is to advance the scientific understanding of geohazards by improving geohazard monitoring through the combination of in-situ and space-based data, and by facilitating the access to data relevant for geohazard research. The stakeholders are: (1) governmental organizations or research institutions responsible for the ground-based monitoring of earthquake and volcanic areas, (2) space agencies and satellite operators providing satellite data, (3) the global geohazard scientific community. The 10.000's of ESA's SAR products are accessible, since beginning 2008, using ESA's "Virtual Archive", a Cloud Computing assets, allowing the global community an utmost downloading performance of these high volume data sets for mass-market costs. In the GEO collaborative context, the management of ESA's "Virtual Archive" and the ordering of these large data sets is being performed by UNAVCO, who is also coordinating the data demand for the several hundreds of co-PIs. ESA is envisaging to provide scientists and developers access to a highly elastic operational e-infrastructure, providing interdisciplinary data on a large scale as well as tools ensuring innovation and a permanent evolution of the products. Consequently, this science environment will help in defining and testing new applications and technologies fostering innovation and new science findings. In Europe, the collaboration between EPOS, "European Plate Observatory System" lead by INGV, and ESA with support of DLR, ASI, and CNES are the main institutional stakeholders for the GEO Supersites contributing also to a unifying e-infrastructure. The overarching objective of the Geohazard Supersites is: "To implement a sustainable Global Earthquake Observation System and a Global Volcano Observation System as part of the Global Earth Observation System of Systems (GEOSS)." This presentation will outline the overall concept, objectives, and examples of the e-infrastructure, which is currently being set up for the GEO Supersite initiative helping to advance science.

Development of high-availability ATCA/PCIe data acquisition instrumentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Correia, Miguel; Sousa, Jorge; Batista, Antonio J.N.

2015-07-01

Latest Fusion energy experiments envision a quasi-continuous operation regime. In consequence, the largest experimental devices, currently in development, specify high-availability (HA) requirements for the whole plant infrastructure. HA features enable the whole facility to perform seamlessly in the case of failure of any of its components, coping with the increasing duration of plasma discharges (steady-state) and assuring safety of equipment, people, environment and investment. IPFN developed a control and data acquisition system, aiming for fast control of advanced Fusion devices, which is thus required to provide such HA features. The system is based on in-house developed Advanced Telecommunication Computing Architecturemore » (ATCA) instrumentation modules - IO blades and data switch blades, establishing a PCIe network on the ATCA shelf's back-plane. The data switch communicates to an external host computer through a PCIe data network. At the hardware management level, the system architecture takes advantage of ATCA native redundancy and hot swap specifications to implement fail-over substitution of IO or data switch blades. A redundant host scheme is also supported by the ATCA/PCIe platform. At the software level, PCIe provides implementation of hot plug services, which translate the hardware changes to the corresponding software/operating system devices. The paper presents how the ATCA and PCIe based system can be setup to perform with the desired degree of HA, thus being suitable for advanced Fusion control and data acquisition systems. (authors)« less

Space-based Communications Infrastructure for Developing Countries

NASA Technical Reports Server (NTRS)

Barker, Keith; Barnes, Carl; Price, K. M.

1995-01-01

This study examines the potential use of satellites to augment the telecommunications infrastructure of developing countries with advanced satellites. The study investigated the potential market for using satellites in developing countries, the role of satellites in national information infractructures (NII), the technical feasibility of augmenting NIIs with satellites, and a nation's financial conditions necessary for procuring satellite systems. In addition, the study examined several technical areas including onboard processing, intersatellite links, frequency of operation, multibeam and active antennas, and advanced satellite technologies. The marketing portion of this study focused on three case studies: China, Brazil, and Mexico. These cases represent countries in various stages of telecommunication infrastructure development. The study concludes by defining the needs of developing countries for satellites, and recommends steps that both industry and NASA can take to improve the competitiveness of U.S. satellite manufacturing.

Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments

PubMed Central

Zapater, Marina; Sanchez, Cesar; Ayala, Jose L.; Moya, Jose M.; Risco-Martín, José L.

2012-01-01

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time. PMID:23112621

GSDC: A Unique Data Center in Korea for HEP research

NASA Astrophysics Data System (ADS)

Ahn, Sang-Un

2017-04-01

Global Science experimental Data hub Center (GSDC) at Korea Institute of Science and Technology Information (KISTI) is a unique data center in South Korea established for promoting the fundamental research fields by supporting them with the expertise on Information and Communication Technology (ICT) and the infrastructure for High Performance Computing (HPC), High Throughput Computing (HTC) and Networking. GSDC has supported various research fields in South Korea dealing with the large scale of data, e.g. RENO experiment for neutrino research, LIGO experiment for gravitational wave detection, Genome sequencing project for bio-medical, and HEP experiments such as CDF at FNAL, Belle at KEK, and STAR at BNL. In particular, GSDC has run a Tier-1 center for ALICE experiment using the LHC at CERN since 2013. In this talk, we present the overview on computing infrastructure that GSDC runs for the research fields and we discuss on the data center infrastructure management system deployed at GSDC.

First results from a combined analysis of CERN computing infrastructure metrics

NASA Astrophysics Data System (ADS)

Duellmann, Dirk; Nieke, Christian

2017-10-01

The IT Analysis Working Group (AWG) has been formed at CERN across individual computing units and the experiments to attempt a cross cutting analysis of computing infrastructure and application metrics. In this presentation we will describe the first results obtained using medium/long term data (1 months — 1 year) correlating box level metrics, job level metrics from LSF and HTCondor, IO metrics from the physics analysis disk pools (EOS) and networking and application level metrics from the experiment dashboards. We will cover in particular the measurement of hardware performance and prediction of job duration, the latency sensitivity of different job types and a search for bottlenecks with the production job mix in the current infrastructure. The presentation will conclude with the proposal of a small set of metrics to simplify drawing conclusions also in the more constrained environment of public cloud deployments.

Ubiquitous green computing techniques for high demand applications in Smart environments.

PubMed

Zapater, Marina; Sanchez, Cesar; Ayala, Jose L; Moya, Jose M; Risco-Martín, José L

2012-01-01

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

NAS infrastructure management system build 1.5 computer-human interface

DOT National Transportation Integrated Search

2001-01-01

Human factors engineers from the National Airspace System (NAS) Human Factors Branch (ACT-530) of the Federal Aviation Administration William J. Hughes Technical Center conducted an evaluation of the NAS Infrastructure Management System (NIMS) Build ...

Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review

NASA Technical Reports Server (NTRS)

Antonsson, Erik; Gombosi, Tamas

2005-01-01

Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.

Advanced Telescopes and Observatories Capability Roadmap Presentation to the NRC

NASA Technical Reports Server (NTRS)

2005-01-01

This viewgraph presentation provides an overview of the NASA Advanced Planning and Integration Office (APIO) roadmap for developing technological capabilities for telescopes and observatories in the following areas: Optics; Wavefront Sensing and Control and Interferometry; Distributed and Advanced Spacecraft; Large Precision Structures; Cryogenic and Thermal Control Systems; Infrastructure.

The GÉANT network: addressing current and future needs of the HEP community

NASA Astrophysics Data System (ADS)

Capone, Vincenzo; Usman, Mian

2015-12-01

The GÉANT infrastructure is the backbone that serves the scientific communities in Europe for their data movement needs and their access to international research and education networks. Using the extensive fibre footprint and infrastructure in Europe the GÉANT network delivers a portfolio of services aimed to best fit the specific needs of the users, including Authentication and Authorization Infrastructure, end-to-end performance monitoring, advanced network services (dynamic circuits, L2-L3VPN, MD-VPN). This talk will outline the factors that help the GÉANT network to respond to the needs of the High Energy Physics community, both in Europe and worldwide. The Pan-European network provides the connectivity between 40 European national research and education networks. In addition, GÉANT also connects the European NRENs to the R&E networks in other world region and has reach to over 110 NREN worldwide, making GÉANT the best connected Research and Education network, with its multiple intercontinental links to different continents e.g. North and South America, Africa and Asia-Pacific. The High Energy Physics computational needs have always had (and will keep having) a leading role among the scientific user groups of the GÉANT network: the LHCONE overlay network has been built, in collaboration with the other big world REN, specifically to address the peculiar needs of the LHC data movement. Recently, as a result of a series of coordinated efforts, the LHCONE network has been expanded to the Asia-Pacific area, and is going to include some of the main regional R&E network in the area. The LHC community is not the only one that is actively using a distributed computing model (hence the need for a high-performance network); new communities are arising, as BELLE II. GÉANT is deeply involved also with the BELLE II Experiment, to provide full support to their distributed computing model, along with a perfSONAR-based network monitoring system. GÉANT has also coordinated the setup of the network infrastructure to perform the BELLE II Trans-Atlantic Data Challenge, and has been active on helping the BELLE II community to sort out their end-to-end performance issues. In this talk we will provide information about the current GÉANT network architecture and of the international connectivity, along with the upcoming upgrades and the planned and foreseeable improvements. We will also describe the implementation of the solutions provided to support the LHC and BELLE II experiments.

Advanced Engineering Environment FY09/10 pilot project.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamph, Jane Ann; Kiba, Grant W.; Pomplun, Alan R.

2010-06-01

The Advanced Engineering Environment (AEE) project identifies emerging engineering environment tools and assesses their value to Sandia National Laboratories and our partners in the Nuclear Security Enterprise (NSE) by testing them in our design environment. This project accomplished several pilot activities, including: the preliminary definition of an engineering bill of materials (BOM) based product structure in the Windchill PDMLink 9.0 application; an evaluation of Mentor Graphics Data Management System (DMS) application for electrical computer-aided design (ECAD) library administration; and implementation and documentation of a Windchill 9.1 application upgrade. The project also supported the migration of legacy data from existing corporatemore » product lifecycle management systems into new classified and unclassified Windchill PDMLink 9.0 systems. The project included two infrastructure modernization efforts: the replacement of two aging AEE development servers for reliable platforms for ongoing AEE project work; and the replacement of four critical application and license servers that support design and engineering work at the Sandia National Laboratories/California site.« less

Developing a European grid infrastructure for cancer research: vision, architecture and services

PubMed Central

Tsiknakis, M; Rueping, S; Martin, L; Sfakianakis, S; Bucur, A; Sengstag, T; Brochhausen, M; Pucaski, J; Graf, N

2007-01-01

Life sciences are currently at the centre of an information revolution. The nature and amount of information now available opens up areas of research that were once in the realm of science fiction. During this information revolution, the data-gathering capabilities have greatly surpassed the data-analysis techniques. Data integration across heterogeneous data sources and data aggregation across different aspects of the biomedical spectrum, therefore, is at the centre of current biomedical and pharmaceutical R&D. This paper reports on original results from the ACGT integrated project, focusing on the design and development of a European Biomedical Grid infrastructure in support of multi-centric, post-genomic clinical trials (CTs) on cancer. Post-genomic CTs use multi-level clinical and genomic data and advanced computational analysis and visualization tools to test hypotheses in trying to identify the molecular reasons for a disease and the stratification of patients in terms of treatment. The paper provides a presentation of the needs of users involved in post-genomic CTs and presents indicative scenarios, which drive the requirements of the engineering phase of the project. Subsequently, the initial architecture specified by the project is presented, and its services are classified and discussed. A range of such key services, including the Master Ontology on sCancer, which lie at the heart of the integration architecture of the project, is presented. Special efforts have been taken to describe the methodological and technological framework of the project, enabling the creation of a legally compliant and trustworthy infrastructure. Finally, a short discussion of the forthcoming work is included, and the potential involvement of the cancer research community in further development or utilization of the infrastructure is described. PMID:22275955

University of Washington/ Northwest National Marine Renewable Energy Center Tidal Current Technology Test Protocol, Instrumentation, Design Code, and Oceanographic Modeling Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-11-452

DOE Office of Scientific and Technical Information (OSTI.GOV)

Driscoll, Frederick R.

The University of Washington (UW) - Northwest National Marine Renewable Energy Center (UW-NNMREC) and the National Renewable Energy Laboratory (NREL) will collaborate to advance research and development (R&D) of Marine Hydrokinetic (MHK) renewable energy technology, specifically renewable energy captured from ocean tidal currents. UW-NNMREC is endeavoring to establish infrastructure, capabilities and tools to support in-water testing of marine energy technology. NREL is leveraging its experience and capabilities in field testing of wind systems to develop protocols and instrumentation to advance field testing of MHK systems. Under this work, UW-NNMREC and NREL will work together to develop a common instrumentation systemmore » and testing methodologies, standards and protocols. UW-NNMREC is also establishing simulation capabilities for MHK turbine and turbine arrays. NREL has extensive experience in wind turbine array modeling and is developing several computer based numerical simulation capabilities for MHK systems. Under this CRADA, UW-NNMREC and NREL will work together to augment single device and array modeling codes. As part of this effort UW NNMREC will also work with NREL to run simulations on NREL's high performance computer system.« less

EPOS-Seismology: building the Thematic Core Service for Seismology during the EPOS Implementation Phase

NASA Astrophysics Data System (ADS)

Haslinger, Florian; EPOS Seismology Consortium, the

2015-04-01

After the successful completion of the EPOS Preparatory Phase, the community of European Research Infrastructures in Seismology is now moving ahead with the build-up of the Thematic Core Service (TCS) for Seismology in EPOS, EPOS-Seismology. Seismology is a domain where European-level infrastructures have been developed since decades, often supported by large-scale EU projects. Today these infrastructures provide services to access earthquake waveforms (ORFEUS), parameters (EMSC) and hazard data and products (EFEHR). The existing organizations constitute the backbone of infrastructures that also in future will continue to manage and host the services of the TCS EPOS-Seismology. While the governance and internal structure of these organizations will remain active, and continue to provide direct interaction with the community, EPOS-Seismology will provide the integration of these within EPOS. The main challenge in the build-up of the TCS EPOS-Seismology is to improve and extend these existing services, producing a single framework which is technically, organizationally and financially integrated with the EPOS architecture, and to further engage various kinds of end users (e.g. scientists, engineers, public managers, citizen scientists). On the technical side the focus lies on four major tasks: - the construction of the next generation software architecture for the European Integrated (waveform) Data Archive EIDA, developing advanced metadata and station information services, fully integrate strong motion waveforms and derived parametric engineering-domain data, and advancing the integration of mobile (temporary) networks and OBS deployments in EIDA; - the further development and expansion of services to access seismological products of scientific interest as provided by the community by implementing a common collection and development (IT) platform, improvements in the earthquake information services e.g. by introducing more robust quality indicators and diversifying collection and dissemination mechanisms, as well as improving historical earthquake data services; - the development of a comprehensive suite of earthquake hazard products, tools, and services harmonized on the European level and available through a common access platform, encompassing information on seismic sources, seismogenic faults, ground-motion prediction equations, geotechnical information, and strong-motion recordings in buildings, together with an interface to earthquake risk; - a portal implementation of computational seismology tools and services, specifically for seismic waveform propagation in complex 3D media following the results of the VERCE project, and initiating the inclusion of further suitable codes on that portal in discussion with the community, forming the basis of EPOS computational earth science infrastructure. Important features common to all tasks are the development of EPOS-wide integrated and interoperable metadata structures, the introduction and utilization of adequate and referencable persistent identifiers for data and products, and the implementation of appropriate user access and authorization mechanisms. Here we present further details on the technical work plan for Seismology during the EPOS Implementation Phase and its integration into the overall EPOS build-up, together with the current view and state of the discussion on the development of adequate governance structures, and discuss how we envision the interaction with and involvement of the wider community outside the consortium in these activities.

Towards the Big Data Strategies for EISCAT-3D

NASA Astrophysics Data System (ADS)

Häggström, I.; Chen, Y.; Hardisty, A.; Sipos, G.; Krakowian, M.; Ferreira, N. L.; Savolainen, V.

2013-12-01

The design of the next generation incoherent scatter radar system, EISCAT-3D, opens up opportunities for physicists to explore many new research fields in the studies of the atmosphere and near-Earth space. On the other hand, it also introduces significant challenges in handling the large-scale experimental data which will be massively generated at great speeds and volumes. During its first operation stage in 2018, EISCAT-3D will produce 5PB data per year, and the total data volume will rise up to 40PB per year in its full operations stage in 2023. This refers to the so-called big data problem, whose size is beyond the capabilities of the current database technology [1]. To unlock the value from these data, new forms of processing and platforms of tools are needed. Advanced e-Science infrastructures such as, EGI, EUDAT, and PRACE, and their enabling technologies are making large-scale computational capacities more accessible to researchers of all scientific disciplines. The European Grid Infrastructure (EGI), a not-for-profit foundation created to manage the infrastructures on behalf of the National Grid Initiatives and European Intergovernmental Research Organisations, operates more than 370,000 logical CPUs, 248 PB disk and 176 PB of disk capacity (June 2013 statistics). EUDAT is a European project aiming to take the first steps towards building a Collaborative Data Infrastructure for European scientific data products. It will offer services for data storage and replication, data staging to computational resources (and vice versa) and services for data cataloguing and discovery. PRACE is the pan-European supercomputing infrastructure that forms the top-tier of HPC provision across Europe, with the aim of enabling high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness. We propose e-Science approaches to tackle the challenges of processing and searching EISCAT-3D data, and will provide solutions for: 1. Staging EISCAT-3D lower-level data (voltage data) into the large-scale e-Science storage, such as EGI or EUDAT; 2. Providing various processing and mining facilities such as, auto-correlation and spatial/temporal integration, to allow individual scientists to analyse data as their will; 3. Providing advanced searching facilities to enable individual scientists to search through all level of data and identify specific signatures, e.g., plasma features, meteors, space debris, astronomical features. The new data processing and searching strategy will offer more flexible way for EISCAT users to analyse and discover interesting data patterns which are not yet available. Space physicists will be able to make better use of the observation data and exploit the growing wealth of them. This will eventually lead to a new data-centric way of conceptualising, organising and carrying out research activities which could lead to an introduction of new approaches to solve problems that were previously considered extremely hard or, in some cases, impossible to solve and also lead to serendipitous discoveries and significant breakthrough [1]. [1] C. Thanos, S. Manegold and M. Kersten, 'Big Data', ERCIM Special Theme: Big Data, No. 89, Apr. 2012.

Computer vision-based technologies and commercial best practices for the advancement of the motion imagery tradecraft

NASA Astrophysics Data System (ADS)

Phipps, Marja; Capel, David; Srinivasan, James

2014-06-01

Motion imagery capabilities within the Department of Defense/Intelligence Community (DoD/IC) have advanced significantly over the last decade, attempting to meet continuously growing data collection, video processing and analytical demands in operationally challenging environments. The motion imagery tradecraft has evolved accordingly, enabling teams of analysts to effectively exploit data and generate intelligence reports across multiple phases in structured Full Motion Video (FMV) Processing Exploitation and Dissemination (PED) cells. Yet now the operational requirements are drastically changing. The exponential growth in motion imagery data continues, but to this the community adds multi-INT data, interoperability with existing and emerging systems, expanded data access, nontraditional users, collaboration, automation, and support for ad hoc configurations beyond the current FMV PED cells. To break from the legacy system lifecycle, we look towards a technology application and commercial adoption model course which will meet these future Intelligence, Surveillance and Reconnaissance (ISR) challenges. In this paper, we explore the application of cutting edge computer vision technology to meet existing FMV PED shortfalls and address future capability gaps. For example, real-time georegistration services developed from computer-vision-based feature tracking, multiple-view geometry, and statistical methods allow the fusion of motion imagery with other georeferenced information sources - providing unparalleled situational awareness. We then describe how these motion imagery capabilities may be readily deployed in a dynamically integrated analytical environment; employing an extensible framework, leveraging scalable enterprise-wide infrastructure and following commercial best practices.

Transportation Infrastructure Design and Construction \\0x16 Virtual Training Tools

DOT National Transportation Integrated Search

2003-09-01

This project will develop 3D interactive computer-training environments for a major element of transportation infrastructure : hot mix asphalt paving. These tools will include elements of hot mix design (including laboratory equipment) and constructi...

Putting the Information Infrastructure to Work. Report of the Information Infrastructure Task Force Committee on Applications and Technology. NIST Special Publication 857.

ERIC Educational Resources Information Center

National Inst. of Standards and Technology, Gaithersburg, MD.

An interconnection of computer networks, telecommunications services, and applications, the National Information Infrastructure (NII) can open up new vistas and profoundly change much of American life. This report explores some of the opportunities and obstacles to the use of the NII by people and organizations. The goal is to express how…

Integrating Network Management for Cloud Computing Services

DTIC Science & Technology

2015-06-01

abstraction and system design. In this dissertation, we make three major contributions. We rst propose to consolidate the tra c and infrastructure management...abstraction and system design. In this dissertation, we make three major contributions. We first propose to consolidate the traffic and infrastructure ...1.3.1 Safe Datacenter Traffic/ Infrastructure Management . . . . . . 9 1.3.2 End-host/Network Cooperative Traffic Management . . . . . . 10 1.3.3 Direct

Local Infrastructures for School Networking: Current Models and Prospects. Technical Report No. 22.

ERIC Educational Resources Information Center

Newman, Denis; And Others

This paper identifies a paradigm shift that must take place in school networking. The ultimate goal is to retool the schools with a local technical infrastructure that gives teachers and students immediate access to communication systems and information resources, thereby supporting the implementation of advances in pedagogy and educational…

Planning: supporting and optimizing clinical guidelines execution.

PubMed

Anselma, Luca; Montani, Stefania

2008-01-01

A crucial feature of computerized clinical guidelines (CGs) lies in the fact that they may be used not only as conventional documents (as if they were just free text) describing general procedures that users have to follow. In fact, thanks to a description of their actions and control flow in some semiformal representation language, CGs can also take advantage of Computer Science methods and Information Technology infrastructures and techniques, to become executable documents, in the sense that they may support clinical decision making and clinical procedures execution. In order to reach this goal, some advanced planning techniques, originally developed within the Artificial Intelligence (AI) community, may be (at least partially) resorted too, after a proper adaptation to the specific CG needs has been carried out.

Social Media as a New Vital Sign: Commentary

PubMed Central

2018-01-01

Mobile technologies, such as wireless glucometers and mobile health apps, are increasingly being integrated into health and medical care. Because patients openly share real-time information about their health behaviors and outcomes on social media, social media data may also be used as a tool for monitoring patient care. This commentary describes how recent advances in computer science, psychology, and medicine enable social media data to become a new health “vital sign,” as well as actionable steps that public health officials, health systems, and clinics can take to integrate social data into both public and population health as well as into individual patient care. Barriers that first need to be addressed, including privacy concerns, legal and ethical responsibilities, and infrastructure support, are discussed. PMID:29712631

Microelectromechanical Systems

NASA Technical Reports Server (NTRS)

Gabriel, Kaigham J.

1995-01-01

Micro-electromechanical systems (MEMS) is an enabling technology that merges computation and communication with sensing and actuation to change the way people and machines interact with the physical world. MEMS is a manufacturing technology that will impact widespread applications including: miniature inertial measurement measurement units for competent munitions and personal navigation; distributed unattended sensors; mass data storage devices; miniature analytical instruments; embedded pressure sensors; non-invasive biomedical sensors; fiber-optics components and networks; distributed aerodynamic control; and on-demand structural strength. The long term goal of ARPA's MEMS program is to merge information processing with sensing and actuation to realize new systems and strategies for both perceiving and controlling systems, processes, and the environment. The MEMS program has three major thrusts: advanced devices and processes, system design, and infrastructure.

Generation of multiphoton entangled quantum states by means of integrated frequency combs.

PubMed

Reimer, Christian; Kues, Michael; Roztocki, Piotr; Wetzel, Benjamin; Grazioso, Fabio; Little, Brent E; Chu, Sai T; Johnston, Tudor; Bromberg, Yaron; Caspani, Lucia; Moss, David J; Morandotti, Roberto

2016-03-11

Complex optical photon states with entanglement shared among several modes are critical to improving our fundamental understanding of quantum mechanics and have applications for quantum information processing, imaging, and microscopy. We demonstrate that optical integrated Kerr frequency combs can be used to generate several bi- and multiphoton entangled qubits, with direct applications for quantum communication and computation. Our method is compatible with contemporary fiber and quantum memory infrastructures and with chip-scale semiconductor technology, enabling compact, low-cost, and scalable implementations. The exploitation of integrated Kerr frequency combs, with their ability to generate multiple, customizable, and complex quantum states, can provide a scalable, practical, and compact platform for quantum technologies. Copyright © 2016, American Association for the Advancement of Science.

Controlling Infrastructure Costs: Right-Sizing the Mission Control Facility

NASA Technical Reports Server (NTRS)

Martin, Keith; Sen-Roy, Michael; Heiman, Jennifer

2009-01-01

Johnson Space Center's Mission Control Center is a space vehicle, space program agnostic facility. The current operational design is essentially identical to the original facility architecture that was developed and deployed in the mid-90's. In an effort to streamline the support costs of the mission critical facility, the Mission Operations Division (MOD) of Johnson Space Center (JSC) has sponsored an exploratory project to evaluate and inject current state-of-the-practice Information Technology (IT) tools, processes and technology into legacy operations. The general push in the IT industry has been trending towards a data-centric computer infrastructure for the past several years. Organizations facing challenges with facility operations costs are turning to creative solutions combining hardware consolidation, virtualization and remote access to meet and exceed performance, security, and availability requirements. The Operations Technology Facility (OTF) organization at the Johnson Space Center has been chartered to build and evaluate a parallel Mission Control infrastructure, replacing the existing, thick-client distributed computing model and network architecture with a data center model utilizing virtualization to provide the MCC Infrastructure as a Service. The OTF will design a replacement architecture for the Mission Control Facility, leveraging hardware consolidation through the use of blade servers, increasing utilization rates for compute platforms through virtualization while expanding connectivity options through the deployment of secure remote access. The architecture demonstrates the maturity of the technologies generally available in industry today and the ability to successfully abstract the tightly coupled relationship between thick-client software and legacy hardware into a hardware agnostic "Infrastructure as a Service" capability that can scale to meet future requirements of new space programs and spacecraft. This paper discusses the benefits and difficulties that a migration to cloud-based computing philosophies has uncovered when compared to the legacy Mission Control Center architecture. The team consists of system and software engineers with extensive experience with the MCC infrastructure and software currently used to support the International Space Station (ISS) and Space Shuttle program (SSP).

e-Infrastructures supporting research into depression, self-harm and suicide.

PubMed

McCafferty, S; Doherty, T; Sinnott, R O; Watt, J

2010-08-28

The Economic and Social Research Council (ESRC)-funded Data Management through e-Social Sciences (DAMES) project is investigating, as one of its four research themes, how research into depression, self-harm and suicide may be enhanced through the adoption of e-Science infrastructures and techniques. In this paper, we explore the challenges in supporting such research infrastructures and describe the distributed and heterogeneous datasets that need to be provisioned to support such research. We describe and demonstrate the application of an advanced user and security-driven infrastructure that has been developed specifically to meet these challenges in an on-going study into depression, self-harm and suicide.

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

PubMed Central

Duarte, Afonso M. S.; Psomopoulos, Fotis E.; Blanchet, Christophe; Bonvin, Alexandre M. J. J.; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C.; de Lucas, Jesus M.; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B.

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community. PMID:26157454

Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis.

PubMed

Duarte, Afonso M S; Psomopoulos, Fotis E; Blanchet, Christophe; Bonvin, Alexandre M J J; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C; de Lucas, Jesus M; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B

2015-01-01

With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

GLIDE: a grid-based light-weight infrastructure for data-intensive environments

NASA Technical Reports Server (NTRS)

Mattmann, Chris A.; Malek, Sam; Beckman, Nels; Mikic-Rakic, Marija; Medvidovic, Nenad; Chrichton, Daniel J.

2005-01-01

The promise of the grid is that it will enable public access and sharing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread adoption. To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms.

Integrating multiple scientific computing needs via a Private Cloud infrastructure

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Berzano, D.; Brunetti, R.; Lusso, S.; Vallero, S.

2014-06-01

In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.

Knowledge-Based Environmental Context Modeling

NASA Astrophysics Data System (ADS)

Pukite, P. R.; Challou, D. J.

2017-12-01

As we move from the oil-age to an energy infrastructure based on renewables, the need arises for new educational tools to support the analysis of geophysical phenomena and their behavior and properties. Our objective is to present models of these phenomena to make them amenable for incorporation into more comprehensive analysis contexts. Starting at the level of a college-level computer science course, the intent is to keep the models tractable and therefore practical for student use. Based on research performed via an open-source investigation managed by DARPA and funded by the Department of Interior [1], we have adapted a variety of physics-based environmental models for a computer-science curriculum. The original research described a semantic web architecture based on patterns and logical archetypal building-blocks (see figure) well suited for a comprehensive environmental modeling framework. The patterns span a range of features that cover specific land, atmospheric and aquatic domains intended for engineering modeling within a virtual environment. The modeling engine contained within the server relied on knowledge-based inferencing capable of supporting formal terminology (through NASA JPL's Semantic Web for Earth and Environmental Technology (SWEET) ontology and a domain-specific language) and levels of abstraction via integrated reasoning modules. One of the key goals of the research was to simplify models that were ordinarily computationally intensive to keep them lightweight enough for interactive or virtual environment contexts. The breadth of the elements incorporated is well-suited for learning as the trend toward ontologies and applying semantic information is vital for advancing an open knowledge infrastructure. As examples of modeling, we have covered such geophysics topics as fossil-fuel depletion, wind statistics, tidal analysis, and terrain modeling, among others. Techniques from the world of computer science will be necessary to promote efficient use of our renewable natural resources. [1] C2M2L (Component, Context, and Manufacturing Model Library) Final Report, https://doi.org/10.13140/RG.2.1.4956.3604

IEDA: Making Small Data BIG Through Interdisciplinary Partnerships Among Long-tail Domains

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Carbotte, S. M.; Arko, R. A.; Ferrini, V. L.; Hsu, L.; Song, L.; Ghiorso, M. S.; Walker, D. J.

2014-12-01

The Big Data world in the Earth Sciences so far exists primarily for disciplines that generate massive volumes of observational or computed data using large-scale, shared instrumentation such as global sensor networks, satellites, or high-performance computing facilities. These data are typically managed and curated by well-supported community data facilities that also provide the tools for exploring the data through visualization or statistical analysis. In many other domains, especially those where data are primarily acquired by individual investigators or small teams (known as 'Long-tail data'), data are poorly shared and integrated, lacking a community-based data infrastructure that ensures persistent access, quality control, standardization, and integration of data, as well as appropriate tools to fully explore and mine the data within the context of broader Earth Science datasets. IEDA (Integrated Earth Data Applications, www.iedadata.org) is a data facility funded by the US NSF to develop and operate data services that support data stewardship throughout the full life cycle of observational data in the solid earth sciences, with a focus on the data management needs of individual researchers. IEDA builds on a strong foundation of mature disciplinary data systems for marine geology and geophysics, geochemistry, and geochronology. These systems have dramatically advanced data resources in those long-tail Earth science domains. IEDA has strengthened these resources by establishing a consolidated, enterprise-grade infrastructure that is shared by the domain-specific data systems, and implementing joint data curation and data publication services that follow community standards. In recent years, other domain-specific data efforts have partnered with IEDA to take advantage of this infrastructure and improve data services to their respective communities with formal data publication, long-term preservation of data holdings, and better sustainability. IEDA hopes to foster such partnerships with streamlined data services, including user-friendly, single-point interfaces for data submission, discovery, and access across the partner systems to support interdisciplinary science.

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

PubMed Central

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E.; Tkachenko, Valery; Torcivia-Rodriguez, John; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure. The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu PMID:26989153

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

PubMed

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

Cooperative high-performance storage in the accelerated strategic computing initiative

NASA Technical Reports Server (NTRS)

Gary, Mark; Howard, Barry; Louis, Steve; Minuzzo, Kim; Seager, Mark

1996-01-01

The use and acceptance of new high-performance, parallel computing platforms will be impeded by the absence of an infrastructure capable of supporting orders-of-magnitude improvement in hierarchical storage and high-speed I/O (Input/Output). The distribution of these high-performance platforms and supporting infrastructures across a wide-area network further compounds this problem. We describe an architectural design and phased implementation plan for a distributed, Cooperative Storage Environment (CSE) to achieve the necessary performance, user transparency, site autonomy, communication, and security features needed to support the Accelerated Strategic Computing Initiative (ASCI). ASCI is a Department of Energy (DOE) program attempting to apply terascale platforms and Problem-Solving Environments (PSEs) toward real-world computational modeling and simulation problems. The ASCI mission must be carried out through a unified, multilaboratory effort, and will require highly secure, efficient access to vast amounts of data. The CSE provides a logically simple, geographically distributed, storage infrastructure of semi-autonomous cooperating sites to meet the strategic ASCI PSE goal of highperformance data storage and access at the user desktop.

Privacy and the National Information Infrastructure.

ERIC Educational Resources Information Center

Rotenberg, Marc

1994-01-01

Explains the work of Computer Professionals for Social Responsibility regarding privacy issues in the use of electronic networks; recommends principles that should be adopted for a National Information Infrastructure privacy code; discusses the need for public education; and suggests pertinent legislative proposals. (LRW)

Effecting IT infrastructure culture change: management by processes and metrics

NASA Technical Reports Server (NTRS)

Miller, R. L.

2001-01-01

This talk describes the processes and metrics used by Jet Propulsion Laboratory to bring about the required IT infrastructure culture change to update and certify, as Y2K compliant, thousands of computers and millions of lines of code.

Meeting the challenges--the role of medical informatics in an ageing society.

PubMed

Koch, Sabine

2006-01-01

The objective of this paper is to identify trends and new technological developments that appear due to an ageing society and to relate them to current research in the field of medical informatics. A survey of the current literature reveals that recent technological advances have been made in the fields of "telecare and home-monitoring", "smart homes and robotics" and "health information systems and knowledge management". Innovative technologies such as wearable devices, bio- and environmental sensors and mobile, humanoid robots do already exist and ambient assistant living environments are being created for an ageing society. However, those technologies have to be adapted to older people's self-care processes and coping strategies, and to support new ways of healthcare delivery. Medical informatics can support this process by providing the necessary information infrastructure, contribute to standardisation, interoperability and security issues and provide modelling and simulation techniques for educational purposes. Research fields of increasing importance with regard to an ageing society are, moreover, the fields of knowledge management, ubiquitous computing and human-computer interaction.

High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding

NASA Astrophysics Data System (ADS)

Rizki, Permata Nur Miftahur; Lee, Heezin; Lee, Minsu; Oh, Sangyoon

2017-01-01

With the rapid advance of remote sensing technology, the amount of three-dimensional point-cloud data has increased extraordinarily, requiring faster processing in the construction of digital elevation models. There have been several attempts to accelerate the computation using parallel methods; however, little attention has been given to investigating different approaches for selecting the most suited parallel programming model for a given computing environment. We present our findings and insights identified by implementing three popular high-performance parallel approaches (message passing interface, MapReduce, and GPGPU) on time demanding but accurate kriging interpolation. The performances of the approaches are compared by varying the size of the grid and input data. In our empirical experiment, we demonstrate the significant acceleration by all three approaches compared to a C-implemented sequential-processing method. In addition, we also discuss the pros and cons of each method in terms of usability, complexity infrastructure, and platform limitation to give readers a better understanding of utilizing those parallel approaches for gridding purposes.

A modular (almost) automatic set-up for elastic multi-tenants cloud (micro)infrastructures

NASA Astrophysics Data System (ADS)

Amoroso, A.; Astorino, F.; Bagnasco, S.; Balashov, N. A.; Bianchi, F.; Destefanis, M.; Lusso, S.; Maggiora, M.; Pellegrino, J.; Yan, L.; Yan, T.; Zhang, X.; Zhao, X.

2017-10-01

An auto-installing tool on an usb drive can allow for a quick and easy automatic deployment of OpenNebula-based cloud infrastructures remotely managed by a central VMDIRAC instance. A single team, in the main site of an HEP Collaboration or elsewhere, can manage and run a relatively large network of federated (micro-)cloud infrastructures, making an highly dynamic and elastic use of computing resources. Exploiting such an approach can lead to modular systems of cloud-bursting infrastructures addressing complex real-life scenarios.

Distributed geospatial model sharing based on open interoperability standards

USGS Publications Warehouse

Feng, Min; Liu, Shuguang; Euliss, Ned H.; Fang, Yin

2009-01-01

Numerous geospatial computational models have been developed based on sound principles and published in journals or presented in conferences. However modelers have made few advances in the development of computable modules that facilitate sharing during model development or utilization. Constraints hampering development of model sharing technology includes limitations on computing, storage, and connectivity; traditional stand-alone and closed network systems cannot fully support sharing and integrating geospatial models. To address this need, we have identified methods for sharing geospatial computational models using Service Oriented Architecture (SOA) techniques and open geospatial standards. The service-oriented model sharing service is accessible using any tools or systems compliant with open geospatial standards, making it possible to utilize vast scientific resources available from around the world to solve highly sophisticated application problems. The methods also allow model services to be empowered by diverse computational devices and technologies, such as portable devices and GRID computing infrastructures. Based on the generic and abstract operations and data structures required for Web Processing Service (WPS) standards, we developed an interactive interface for model sharing to help reduce interoperability problems for model use. Geospatial computational models are shared on model services, where the computational processes provided by models can be accessed through tools and systems compliant with WPS. We developed a platform to help modelers publish individual models in a simplified and efficient way. Finally, we illustrate our technique using wetland hydrological models we developed for the prairie pothole region of North America.

Synthetic biology advances and applications in the biotechnology industry: a perspective.

PubMed

Katz, Leonard; Chen, Yvonne Y; Gonzalez, Ramon; Peterson, Todd C; Zhao, Huimin; Baltz, Richard H

2018-06-18

Synthetic biology is a logical extension of what has been called recombinant DNA (rDNA) technology or genetic engineering since the 1970s. As rDNA technology has been the driver for the development of a thriving biotechnology industry today, starting with the commercialization of biosynthetic human insulin in the early 1980s, synthetic biology has the potential to take the industry to new heights in the coming years. Synthetic biology advances have been driven by dramatic cost reductions in DNA sequencing and DNA synthesis; by the development of sophisticated tools for genome editing, such as CRISPR/Cas9; and by advances in informatics, computational tools, and infrastructure to facilitate and scale analysis and design. Synthetic biology approaches have already been applied to the metabolic engineering of microorganisms for the production of industrially important chemicals and for the engineering of human cells to treat medical disorders. It also shows great promise to accelerate the discovery and development of novel secondary metabolites from microorganisms through traditional, engineered, and combinatorial biosynthesis. We anticipate that synthetic biology will continue to have broadening impacts on the biotechnology industry to address ongoing issues of human health, world food supply, renewable energy, and industrial chemicals and enzymes.

Sustainability of transport structures - some aspects of the nonlinear reliability assessment

NASA Astrophysics Data System (ADS)

Pukl, Radomír; Sajdlová, Tereza; Strauss, Alfred; Lehký, David; Novák, Drahomír

2017-09-01

Efficient techniques for both nonlinear numerical analysis of concrete structures and advanced stochastic simulation methods have been combined in order to offer an advanced tool for assessment of realistic behaviour, failure and safety assessment of transport structures. The utilized approach is based on randomization of the non-linear finite element analysis of the structural models. Degradation aspects such as carbonation of concrete can be accounted in order predict durability of the investigated structure and its sustainability. Results can serve as a rational basis for the performance and sustainability assessment based on advanced nonlinear computer analysis of the structures of transport infrastructure such as bridges or tunnels. In the stochastic simulation the input material parameters obtained from material tests including their randomness and uncertainty are represented as random variables or fields. Appropriate identification of material parameters is crucial for the virtual failure modelling of structures and structural elements. Inverse analysis using artificial neural networks and virtual stochastic simulations approach is applied to determine the fracture mechanical parameters of the structural material and its numerical model. Structural response, reliability and sustainability have been investigated on different types of transport structures made from various materials using the above mentioned methodology and tools.

In-Use and Emerging Disruptive Technology Trends

DTIC Science & Technology

2015-03-31

blog/establishing-zero-trust- infrastructure / (accessed No- vember 7, 2014) Mobile Thin Client End Points In the early days of computing, the...companies are using their network infrastructure to break into the mobile broadband market. For example, Ca- blevision recently began providing a Wi-Fi...smartphones and mobile devic- es will be used within the Pentagon. A building-wide cellular infrastructure is not the an- swer to retrieving and sending

The International Symposium on Grids and Clouds

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2012 will be held at Academia Sinica in Taipei from 26 February to 2 March 2012, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). 2012 is the decennium anniversary of the ISGC which over the last decade has tracked the convergence, collaboration and innovation of individual researchers across the Asia Pacific region to a coherent community. With the continuous support and dedication from the delegates, ISGC has provided the primary international distributed computing platform where distinguished researchers and collaboration partners from around the world share their knowledge and experiences. The last decade has seen the wide-scale emergence of e-Infrastructure as a critical asset for the modern e-Scientist. The emergence of large-scale research infrastructures and instruments that has produced a torrent of electronic data is forcing a generational change in the scientific process and the mechanisms used to analyse the resulting data deluge. No longer can the processing of these vast amounts of data and production of relevant scientific results be undertaken by a single scientist. Virtual Research Communities that span organisations around the world, through an integrated digital infrastructure that connects the trust and administrative domains of multiple resource providers, have become critical in supporting these analyses. Topics covered in ISGC 2012 include: High Energy Physics, Biomedicine & Life Sciences, Earth Science, Environmental Changes and Natural Disaster Mitigation, Humanities & Social Sciences, Operations & Management, Middleware & Interoperability, Security and Networking, Infrastructure Clouds & Virtualisation, Business Models & Sustainability, Data Management, Distributed Volunteer & Desktop Grid Computing, High Throughput Computing, and High Performance, Manycore & GPU Computing.

[Relationship between water supply, sanitation, public health, and environment: elements for the formulation of a sanitary infrastructure planning model].

PubMed

Soares, Sérgio R A; Bernardes, Ricardo S; Netto, Oscar de M Cordeiro

2002-01-01

The understanding of sanitation infrastructure, public health, and environmental relations is a fundamental assumption for planning sanitation infrastructure in urban areas. This article thus suggests elements for developing a planning model for sanitation infrastructure. The authors performed a historical survey of environmental and public health issues related to the sector, an analysis of the conceptual frameworks involving public health and sanitation systems, and a systematization of the various effects that water supply and sanitation have on public health and the environment. Evaluation of these effects should guarantee the correct analysis of possible alternatives, deal with environmental and public health objectives (the main purpose of sanitation infrastructure), and provide the most reasonable indication of actions. The suggested systematization of the sanitation systems effects in each step of their implementation is an advance considering the association between the fundamental elements for formulating a planning model for sanitation infrastructure.

An infrastructure for the integration of geoscience instruments and sensors on the Grid

NASA Astrophysics Data System (ADS)

Pugliese, R.; Prica, M.; Kourousias, G.; Del Linz, A.; Curri, A.

2009-04-01

The Grid, as a computing paradigm, has long been in the attention of both academia and industry[1]. The distributed and expandable nature of its general architecture result to scalability and more efficient utilisation of the computing infrastructures. The scientific community, including that of geosciences, often handles problems with very high requirements in data processing, transferring, and storing[2,3]. This has raised the interest on Grid technologies but these are often viewed solely as an access gateway to HPC. Suitable Grid infrastructures could provide the geoscience community with additional benefits like those of sharing, remote access and control of scientific systems. These systems can be scientific instruments, sensors, robots, cameras and any other device used in geosciences. The solution for practical, general, and feasible Grid-enabling of such devices requires non-intrusive extensions on core parts of the current Grid architecture. We propose an extended version of an architecture[4] that can serve as the solution to the problem. The solution we propose is called Grid Instrument Element (IE) [5]. It is an addition to the existing core Grid parts; the Computing Element (CE) and the Storage Element (SE) that serve the purposes that their name suggests. The IE that we will be referring to, and the related technologies have been developed in the EU project on the Deployment of Remote Instrumentation Infrastructure (DORII1). In DORII, partners of various scientific communities including those of Earthquake, Environmental science, and Experimental science, have adopted the technology of the Instrument Element in order to integrate to the Grid their devices. The Oceanographic and coastal observation and modelling Mediterranean Ocean Observing Network (OGS2), a DORII partner, is in the process of deploying the above mentioned Grid technologies on two types of observational modules: Argo profiling floats and a novel Autonomous Underwater Vehicle (AUV). In this paper i) we define the need for integration of instrumentation in the Grid, ii) we introduce the solution of the Instrument Element, iii) we demonstrate a suitable end-user web portal for accessing Grid resources, iv) we describe from the Grid-technological point of view the process of the integration to the Grid of two advanced environmental monitoring devices. References [1] M. Surridge, S. Taylor, D. De Roure, and E. Zaluska, "Experiences with GRIA—Industrial Applications on a Web Services Grid," e-Science and Grid Computing, First International Conference on e-Science and Grid Computing, 2005, pp. 98-105. [2] A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke, "The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets," Journal of Network and Computer Applications, vol. 23, 2000, pp. 187-200. [3] B. Allcock, J. Bester, J. Bresnahan, A.L. Chervenak, I. Foster, C. Kesselman, S. Meder, V. Nefedova, D. Quesnel, and S. Tuecke, "Data management and transfer in high-performance computational grid environments," Parallel Computing, vol. 28, 2002, pp. 749-771. [4] E. Frizziero, M. Gulmini, F. Lelli, G. Maron, A. Oh, S. Orlando, A. Petrucci, S. Squizzato, and S. Traldi, "Instrument Element: A New Grid component that Enables the Control of Remote Instrumentation," Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)-Volume 00, IEEE Computer Society Washington, DC, USA, 2006. [5] R. Ranon, L. De Marco, A. Senerchia, S. Gabrielli, L. Chittaro, R. Pugliese, L. Del Cano, F. Asnicar, and M. Prica, "A Web-based Tool for Collaborative Access to Scientific Instruments in Cyberinfrastructures." 1 The DORII project is supported by the European Commission within the 7th Framework Programme (FP7/2007-2013) under grant agreement no. RI-213110. URL: http://www.dorii.eu 2 Istituto Nazionale di Oceanografia e di Geofisica Sperimentale. URL: http://www.ogs.trieste.it

Critical Infrastructure Interdependencies Assessment

DOE PAGES

Petit, Frederic; Verner, Duane

2016-11-01

Throughout the world there is strong recognition that critical infrastructure security and resilience needs to be improved. In the United States, the National Infrastructure Protection Plan (NIPP) provides the strategic vision to guide the national effort to manage risk to the Nation’s critical infrastructure.”1 The achievement of this vision is challenged by the complexity of critical infrastructure systems and their inherent interdependencies. The update to the NIPP presents an opportunity to advance the nation’s efforts to further understand and analyze interdependencies. Such an important undertaking requires the involvement of public and private sector stakeholders and the reinforcement of existing partnershipsmore » and collaborations within the U.S. Department of Homeland Security (DHS) and other Federal agencies, including national laboratories; State, local, tribal, and territorial governments; and nongovernmental organizations.« less

TRANSVAC research infrastructure - Results and lessons learned from the European network of vaccine research and development.

PubMed

Geels, Mark J; Thøgersen, Regitze L; Guzman, Carlos A; Ho, Mei Mei; Verreck, Frank; Collin, Nicolas; Robertson, James S; McConkey, Samuel J; Kaufmann, Stefan H E; Leroy, Odile

2015-10-05

TRANSVAC was a collaborative infrastructure project aimed at enhancing European translational vaccine research and training. The objective of this four year project (2009-2013), funded under the European Commission's (EC) seventh framework programme (FP7), was to support European collaboration in the vaccine field, principally through the provision of transnational access (TNA) to critical vaccine research and development (R&D) infrastructures, as well as by improving and harmonising the services provided by these infrastructures through joint research activities (JRA). The project successfully provided all available services to advance 29 projects and, through engaging all vaccine stakeholders, successfully laid down the blueprint for the implementation of a permanent research infrastructure for early vaccine R&D in Europe. Copyright © 2015. Published by Elsevier Ltd.

GraphMeta: Managing HPC Rich Metadata in Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Dong; Chen, Yong; Carns, Philip

High-performance computing (HPC) systems face increasingly critical metadata management challenges, especially in the approaching exascale era. These challenges arise not only from exploding metadata volumes, but also from increasingly diverse metadata, which contains data provenance and arbitrary user-defined attributes in addition to traditional POSIX metadata. This ‘rich’ metadata is becoming critical to supporting advanced data management functionality such as data auditing and validation. In our prior work, we identified a graph-based model as a promising solution to uniformly manage HPC rich metadata due to its flexibility and generality. However, at the same time, graph-based HPC rich metadata anagement also introducesmore » significant challenges to the underlying infrastructure. In this study, we first identify the challenges on the underlying infrastructure to support scalable, high-performance rich metadata management. Based on that, we introduce GraphMeta, a graphbased engine designed for this use case. It achieves performance scalability by introducing a new graph partitioning algorithm and a write-optimal storage engine. We evaluate GraphMeta under both synthetic and real HPC metadata workloads, compare it with other approaches, and demonstrate its advantages in terms of efficiency and usability for rich metadata management in HPC systems.« less

Development of an informatics infrastructure for data exchange of biomolecular simulations: architecture, data models and ontology$

PubMed Central

Thibault, J. C.; Roe, D. R.; Eilbeck, K.; Cheatham, T. E.; Facelli, J. C.

2015-01-01

Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data – both within the same organization and among different ones – remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations. PMID:26387907

Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

PubMed

Thibault, J C; Roe, D R; Eilbeck, K; Cheatham, T E; Facelli, J C

2015-01-01

Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations.

Testing of SWMM Model’s LID Modules

EPA Science Inventory

EPA’s Storm Water Management Model (SWMM) is a computational code heavily relied upon by industry for the simulation of wastewater and stormwater infrastructure performance to . design and build multi-billion-dollar, multi-decade infrastructure upgrades. Since the 1970’s, EPA a...

Extensible Infrastructure for Browsing and Searching Abstracted Spacecraft Data

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Crockett, Thomas M.; Joswig, Joseph C.; Torres, Recaredo J.; Norris, Jeffrey S.; Fox, Jason M.; Powell, Mark W.; Mittman, David S.; Abramyan, Lucy; Shams, Khawaja S.;

The Path to Convergence: Design, Coordination and Social Issues in the Implementation of a Middleware Data Broker.

NASA Astrophysics Data System (ADS)

Slota, S.; Khalsa, S. J. S.

2015-12-01

Infrastructures are the result of systems, networks, and inter-networks that accrete, overlay and segment one another over time. As a result, working infrastructures represent a broad heterogeneity of elements - data types, computational resources, material substrates (computing hardware, physical infrastructure, labs, physical information resources, etc.) as well as organizational and social functions which result in divergent outputs and goals. Cyber infrastructure's engineering often defaults to a separation of the social from the technical that results in the engineering succeeding in limited ways, or the exposure of unanticipated points of failure within the system. Studying the development of middleware intended to mediate interactions among systems within an earth systems science infrastructure exposes organizational, technical and standards-focused negotiations endemic to a fundamental trait of infrastructure: its characteristic invisibility in use. Intended to perform a core function within the EarthCube cyberinfrastructure, the development, governance and maintenance of an automated brokering system is a microcosm of large-scale infrastructural efforts. Points of potential system failure, regardless of the extent to which they are more social or more technical in nature, can be considered in terms of the reverse salient: a point of social and material configuration that momentarily lags behind the progress of an emerging or maturing infrastructure. The implementation of the BCube data broker has exposed reverse salients in regards to the overall EarthCube infrastructure (and the role of middleware brokering) in the form of organizational factors such as infrastructural alignment, maintenance and resilience; differing and incompatible practices of data discovery and evaluation among users and stakeholders; and a preponderance of local variations in the implementation of standards and authentication in data access. These issues are characterized by their role in increasing tension or friction among components that are on the path to convergence and may help to predict otherwise-occluded endogenous points of failure or non-adoption in the infrastructure.

A Theoretical Secure Enterprise Architecture for Multi Revenue Generating Smart Grid Sub Electric Infrastructure

ERIC Educational Resources Information Center

Chaudhry, Hina

2013-01-01

This study is a part of the smart grid initiative providing electric vehicle charging infrastructure. It is a refueling structure, an energy generating photovoltaic system and charge point electric vehicle charging station. The system will utilize advanced design and technology allowing electricity to flow from the site's normal electric service…

Parallel, distributed and GPU computing technologies in single-particle electron microscopy

PubMed Central

Schmeisser, Martin; Heisen, Burkhard C.; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

2009-01-01

Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today’s technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined. PMID:19564686

Parallel, distributed and GPU computing technologies in single-particle electron microscopy.

PubMed

Schmeisser, Martin; Heisen, Burkhard C; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

2009-07-01

Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today's technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined.

Alternative Fuels Data Center

Science.gov Websites

Advanced Technology Vehicle (ATV) and Alternative Fuel Infrastructure Manufacturing Incentives Through the Advanced Technology Vehicles Manufacturing Loan Program, manufacturers may be eligible for direct loans for up to 30% of the cost of re-equipping, expanding, or establishing manufacturing

Cloud Computing and Its Applications in GIS

NASA Astrophysics Data System (ADS)

Kang, Cao

2011-12-01

Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature of cloud computing. This paper presents a parallel Euclidean distance algorithm that works seamlessly with the distributed nature of cloud computing infrastructures. The mechanism of this algorithm is to subdivide a raster image into sub-images and wrap them with a one pixel deep edge layer of individually computed distance information. Each sub-image is then processed by a separate node, after which the resulting sub-images are reassembled into the final output. It is shown that while any rectangular sub-image shape can be used, those approximating squares are computationally optimal. This study also serves as a demonstration of this subdivide and layer-wrap strategy, which would enable the migration of many truly spatial GIS algorithms to cloud computing infrastructures. However, this research also indicates that certain spatial GIS algorithms such as cost distance cannot be migrated by adopting this mechanism, which presents significant challenges for the development of cloud-based GIS systems. The third article is entitled "A Distributed Storage Schema for Cloud Computing based Raster GIS Systems". This paper proposes a NoSQL Database Management System (NDDBMS) based raster GIS data storage schema. NDDBMS has good scalability and is able to use distributed commodity computers, which make it superior to Relational Database Management Systems (RDBMS) in a cloud computing environment. In order to provide optimized data service performance, the proposed storage schema analyzes the nature of commonly used raster GIS data sets. It discriminates two categories of commonly used data sets, and then designs corresponding data storage models for both categories. As a result, the proposed storage schema is capable of hosting and serving enormous volumes of raster GIS data speedily and efficiently on cloud computing infrastructures. In addition, the scheme also takes advantage of the data compression characteristics of Quadtrees, thus promoting efficient data storage. Through this assessment of cloud computing technology, the exploration of the challenges and solutions to the migration of GIS algorithms to cloud computing infrastructures, and the examination of strategies for serving large amounts of GIS data in a cloud computing infrastructure, this dissertation lends support to the feasibility of building a cloud-based GIS system. However, there are still challenges that need to be addressed before a full-scale functional cloud-based GIS system can be successfully implemented. (Abstract shortened by UMI.)

Infrastructure Retrofit Design via Composite Mechanics

NASA Technical Reports Server (NTRS)

Chamis, Christos, C.; Gotsis,Pascal K.

1998-01-01

Select applications are described to illustrate the concept for retrofitting reinforced concrete infrastructure with fiber reinforced plastic laminates. The concept is first illustrated by using an axially loaded reinforced concrete column. A reinforced concrete arch and a dome are then used to illustrate the versatility of the concept. Advanced methods such as finite element structural analysis and progressive structural fracture are then used to evaluate the retrofitting laminate adequacy. Results obtains show that retrofits can be designed to double and even triple the as-designed load of the select reinforced concrete infrastructures.

The diverse use of clouds by CMS

DOE PAGES

Andronis, Anastasios; Bauer, Daniela; Chaze, Olivier; ...

2015-12-23

The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of themore » trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.« less

Open source system OpenVPN in a function of Virtual Private Network

NASA Astrophysics Data System (ADS)

Skendzic, A.; Kovacic, B.

2017-05-01

Using of Virtual Private Networks (VPN) can establish high security level in network communication. VPN technology enables high security networking using distributed or public network infrastructure. VPN uses different security and managing rules inside networks. It can be set up using different communication channels like Internet or separate ISP communication infrastructure. VPN private network makes security communication channel over public network between two endpoints (computers). OpenVPN is an open source software product under GNU General Public License (GPL) that can be used to establish VPN communication between two computers inside business local network over public communication infrastructure. It uses special security protocols and 256-bit Encryption and it is capable of traversing network address translators (NATs) and firewalls. It allows computers to authenticate each other using a pre-shared secret key, certificates or username and password. This work gives review of VPN technology with a special accent on OpenVPN. This paper will also give comparison and financial benefits of using open source VPN software in business environment.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hale, M.A.; Craig, J.I.

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implementmore » the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.« less

Cloudweaver: Adaptive and Data-Driven Workload Manager for Generic Clouds

NASA Astrophysics Data System (ADS)

Li, Rui; Chen, Lei; Li, Wen-Syan

Cloud computing denotes the latest trend in application development for parallel computing on massive data volumes. It relies on clouds of servers to handle tasks that used to be managed by an individual server. With cloud computing, software vendors can provide business intelligence and data analytic services for internet scale data sets. Many open source projects, such as Hadoop, offer various software components that are essential for building a cloud infrastructure. Current Hadoop (and many others) requires users to configure cloud infrastructures via programs and APIs and such configuration is fixed during the runtime. In this chapter, we propose a workload manager (WLM), called CloudWeaver, which provides automated configuration of a cloud infrastructure for runtime execution. The workload management is data-driven and can adapt to dynamic nature of operator throughput during different execution phases. CloudWeaver works for a single job and a workload consisting of multiple jobs running concurrently, which aims at maximum throughput using a minimum set of processors.

Assessing the uptake of persistent identifiers by research infrastructure users

PubMed Central

Maull, Keith E.

2017-01-01

Significant progress has been made in the past few years in the development of recommendations, policies, and procedures for creating and promoting citations to data sets, software, and other research infrastructures like computing facilities. Open questions remain, however, about the extent to which referencing practices of authors of scholarly publications are changing in ways desired by these initiatives. This paper uses four focused case studies to evaluate whether research infrastructures are being increasingly identified and referenced in the research literature via persistent citable identifiers. The findings of the case studies show that references to such resources are increasing, but that the patterns of these increases are variable. In addition, the study suggests that citation practices for data sets may change more slowly than citation practices for software and research facilities, due to the inertia of existing practices for referencing the use of data. Similarly, existing practices for acknowledging computing support may slow the adoption of formal citations for computing resources. PMID:28394907

Big-BOE: Fusing Spanish Official Gazette with Big Data Technology.

PubMed

Basanta-Val, Pablo; Sánchez-Fernández, Luis

2018-06-01

The proliferation of new data sources, stemmed from the adoption of open-data schemes, in combination with an increasing computing capacity causes the inception of new type of analytics that process Internet of things with low-cost engines to speed up data processing using parallel computing. In this context, the article presents an initiative, called BIG-Boletín Oficial del Estado (BOE), designed to process the Spanish official government gazette (BOE) with state-of-the-art processing engines, to reduce computation time and to offer additional speed up for big data analysts. The goal of including a big data infrastructure is to be able to process different BOE documents in parallel with specific analytics, to search for several issues in different documents. The application infrastructure processing engine is described from an architectural perspective and from performance, showing evidence on how this type of infrastructure improves the performance of different types of simple analytics as several machines cooperate.

The SCEC Community Modeling Environment(SCEC/CME): A Collaboratory for Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Jordan, T. H.; Minster, J. B.; Moore, R.; Kesselman, C.

2005-12-01

The SCEC Community Modeling Environment (SCEC/CME) Project is an NSF-supported Geosciences/IT partnership that is actively developing an advanced information infrastructure for system-level earthquake science in Southern California. This partnership includes SCEC, USC's Information Sciences Institute (ISI), the San Diego Supercomputer Center (SDSC), the Incorporated Institutions for Research in Seismology (IRIS), and the U.S. Geological Survey. The goal of the SCEC/CME is to develop seismological applications and information technology (IT) infrastructure to support the development of Seismic Hazard Analysis (SHA) programs and other geophysical simulations. The SHA application programs developed on the Project include a Probabilistic Seismic Hazard Analysis system called OpenSHA. OpenSHA computational elements that are currently available include a collection of attenuation relationships, and several Earthquake Rupture Forecasts (ERFs). Geophysicists in the collaboration have also developed Anelastic Wave Models (AWMs) using both finite-difference and finite-element approaches. Earthquake simulations using these codes have been run for a variety of earthquake sources. Rupture Dynamic Model (RDM) codes have also been developed that simulate friction-based fault slip. The SCEC/CME collaboration has also developed IT software and hardware infrastructure to support the development, execution, and analysis of these SHA programs. To support computationally expensive simulations, we have constructed a grid-based scientific workflow system. Using the SCEC grid, project collaborators can submit computations from the SCEC/CME servers to High Performance Computers at USC and TeraGrid High Performance Computing Centers. Data generated and archived by the SCEC/CME is stored in a digital library system, the Storage Resource Broker (SRB). This system provides a robust and secure system for maintaining the association between the data seta and their metadata. To provide an easy-to-use system for constructing SHA computations, a browser-based workflow assembly web portal has been developed. Users can compose complex SHA calculations, specifying SCEC/CME data sets as inputs to calculations, and calling SCEC/CME computational programs to process the data and the output. Knowledge-based software tools have been implemented that utilize ontological descriptions of SHA software and data can validate workflows created with this pathway assembly tool. Data visualization software developed by the collaboration supports analysis and validation of data sets. Several programs have been developed to visualize SCEC/CME data including GMT-based map making software for PSHA codes, 4D wavefield propagation visualization software based on OpenGL, and 3D Geowall-based visualization of earthquakes, faults, and seismic wave propagation. The SCEC/CME Project also helps to sponsor the SCEC UseIT Intern program. The UseIT Intern Program provides research opportunities in both Geosciences and Information Technology to undergraduate students in a variety of fields. The UseIT group has developed a 3D data visualization tool, called SCEC-VDO, as a part of this undergraduate research program.

The StratusLab cloud distribution: Use-cases and support for scientific applications

NASA Astrophysics Data System (ADS)

Floros, E.

2012-04-01

The StratusLab project is integrating an open cloud software distribution that enables organizations to setup and provide their own private or public IaaS (Infrastructure as a Service) computing clouds. StratusLab distribution capitalizes on popular infrastructure virtualization solutions like KVM, the OpenNebula virtual machine manager, Claudia service manager and SlipStream deployment platform, which are further enhanced and expanded with additional components developed within the project. The StratusLab distribution covers the core aspects of a cloud IaaS architecture, namely Computing (life-cycle management of virtual machines), Storage, Appliance management and Networking. The resulting software stack provides a packaged turn-key solution for deploying cloud computing services. The cloud computing infrastructures deployed using StratusLab can support a wide range of scientific and business use cases. Grid computing has been the primary use case pursued by the project and for this reason the initial priority has been the support for the deployment and operation of fully virtualized production-level grid sites; a goal that has already been achieved by operating such a site as part of EGI's (European Grid Initiative) pan-european grid infrastructure. In this area the project is currently working to provide non-trivial capabilities like elastic and autonomic management of grid site resources. Although grid computing has been the motivating paradigm, StratusLab's cloud distribution can support a wider range of use cases. Towards this direction, we have developed and currently provide support for setting up general purpose computing solutions like Hadoop, MPI and Torque clusters. For what concerns scientific applications the project is collaborating closely with the Bioinformatics community in order to prepare VM appliances and deploy optimized services for bioinformatics applications. In a similar manner additional scientific disciplines like Earth Science can take advantage of StratusLab cloud solutions. Interested users are welcomed to join StratusLab's user community by getting access to the reference cloud services deployed by the project and offered to the public.

Study of Pu consumption in advanced light water reactors: Evaluation of GE advanced boiling water reactor plants - compilation of Phase 1B task reports

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1993-09-15

This report contains an extensive evaluation of GE advanced boiling water reactor plants prepared for United State Department of Energy. The general areas covered in this report are: core and system performance; fuel cycle; infrastructure and deployment; and safety and environmental approval.

Advanced Manufacturing Technologies

NASA Technical Reports Server (NTRS)

Fikes, John

2016-01-01

Advanced Manufacturing Technologies (AMT) is developing and maturing innovative and advanced manufacturing technologies that will enable more capable and lower-cost spacecraft, launch vehicles and infrastructure to enable exploration missions. The technologies will utilize cutting edge materials and emerging capabilities including metallic processes, additive manufacturing, composites, and digital manufacturing. The AMT project supports the National Manufacturing Initiative involving collaboration with other government agencies.

Research infrastructure support to address ecosystem dynamics

NASA Astrophysics Data System (ADS)

Los, Wouter

2014-05-01

Predicting the evolution of ecosystems to climate change or human pressures is a challenge. Even understanding past or current processes is complicated as a result of the many interactions and feedbacks that occur within and between components of the system. This talk will present an example of current research on changes in landscape evolution, hydrology, soil biogeochemical processes, zoological food webs, and plant community succession, and how these affect feedbacks to components of the systems, including the climate system. Multiple observations, experiments, and simulations provide a wealth of data, but not necessarily understanding. Model development on the coupled processes on different spatial and temporal scales is sensitive for variations in data and of parameter change. Fast high performance computing may help to visualize the effect of these changes and the potential stability (and reliability) of the models. This may than allow for iteration between data production and models towards stable models reducing uncertainty and improving the prediction of change. The role of research infrastructures becomes crucial is overcoming barriers for such research. Environmental infrastructures are covering physical site facilities, dedicated instrumentation and e-infrastructure. The LifeWatch infrastructure for biodiversity and ecosystem research will provide services for data integration, analysis and modeling. But it has to cooperate intensively with the other kinds of infrastructures in order to support the iteration between data production and model computation. The cooperation in the ENVRI project (Common operations of environmental research infrastructures) is one of the initiatives to foster such multidisciplinary research.

Physicists Get INSPIREd: INSPIRE Project and Grid Applications

NASA Astrophysics Data System (ADS)

Klem, Jukka; Iwaszkiewicz, Jan

2011-12-01

INSPIRE is the new high-energy physics scientific information system developed by CERN, DESY, Fermilab and SLAC. INSPIRE combines the curated and trusted contents of SPIRES database with Invenio digital library technology. INSPIRE contains the entire HEP literature with about one million records and in addition to becoming the reference HEP scientific information platform, it aims to provide new kinds of data mining services and metrics to assess the impact of articles and authors. Grid and cloud computing provide new opportunities to offer better services in areas that require large CPU and storage resources including document Optical Character Recognition (OCR) processing, full-text indexing of articles and improved metrics. D4Science-II is a European project that develops and operates an e-Infrastructure supporting Virtual Research Environments (VREs). It develops an enabling technology (gCube) which implements a mechanism for facilitating the interoperation of its e-Infrastructure with other autonomously running data e-Infrastructures. As a result, this creates the core of an e-Infrastructure ecosystem. INSPIRE is one of the e-Infrastructures participating in D4Science-II project. In the context of the D4Science-II project, the INSPIRE e-Infrastructure makes available some of its resources and services to other members of the resulting ecosystem. Moreover, it benefits from the ecosystem via a dedicated Virtual Organization giving access to an array of resources ranging from computing and storage resources of grid infrastructures to data and services.

Cyberdyn supercomputer - a tool for imaging geodinamic processes

NASA Astrophysics Data System (ADS)

Pomeran, Mihai; Manea, Vlad; Besutiu, Lucian; Zlagnean, Luminita

2014-05-01

More and more physical processes developed within the deep interior of our planet, but with significant impact on the Earth's shape and structure, become subject to numerical modelling by using high performance computing facilities. Nowadays, worldwide an increasing number of research centers decide to make use of such powerful and fast computers for simulating complex phenomena involving fluid dynamics and get deeper insight to intricate problems of Earth's evolution. With the CYBERDYN cybernetic infrastructure (CCI), the Solid Earth Dynamics Department in the Institute of Geodynamics of the Romanian Academy boldly steps into the 21st century by entering the research area of computational geodynamics. The project that made possible this advancement, has been jointly supported by EU and Romanian Government through the Structural and Cohesion Funds. It lasted for about three years, ending October 2013. CCI is basically a modern high performance Beowulf-type supercomputer (HPCC), combined with a high performance visualization cluster (HPVC) and a GeoWall. The infrastructure is mainly structured around 1344 cores and 3 TB of RAM. The high speed interconnect is provided by a Qlogic InfiniBand switch, able to transfer up to 40 Gbps. The CCI storage component is a 40 TB Panasas NAS. The operating system is Linux (CentOS). For control and maintenance, the Bright Cluster Manager package is used. The SGE job scheduler manages the job queues. CCI has been designed for a theoretical peak performance up to 11.2 TFlops. Speed tests showed that a high resolution numerical model (256 × 256 × 128 FEM elements) could be resolved with a mean computational speed of 1 time step at 30 seconds, by employing only a fraction of the computing power (20%). After passing the mandatory tests, the CCI has been involved in numerical modelling of various scenarios related to the East Carpathians tectonic and geodynamic evolution, including the Neogene magmatic activity, and the intriguing intermediate-depth seismicity within the so-called Vrancea zone. The CFD code for numerical modelling is CitcomS, a widely employed open source package specifically developed for earth sciences. Several preliminary 3D geodynamic models for simulating an assumed subduction or the effect of a mantle plume will be presented and discussed.

SEED: A Suite of Instructional Laboratories for Computer Security Education

ERIC Educational Resources Information Center

Du, Wenliang; Wang, Ronghua

2008-01-01

The security and assurance of our computing infrastructure has become a national priority. To address this priority, higher education has gradually incorporated the principles of computer and information security into the mainstream undergraduate and graduate computer science curricula. To achieve effective education, learning security principles…

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herner, K.; Alba Hernandex, A. F.; Bhat, S.

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasinglymore » complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.« less

Advances in Grid Computing for the Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Herner, K.; Alba Hernandez, A. F.; Bhat, S.; Box, D.; Boyd, J.; Di Benedetto, V.; Ding, P.; Dykstra, D.; Fattoruso, M.; Garzoglio, G.; Kirby, M.; Kreymer, A.; Levshina, T.; Mazzacane, A.; Mengel, M.; Mhashilkar, P.; Podstavkov, V.; Retzke, K.; Sharma, N.; Teheran, J.

2017-10-01

The Fabric for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientific Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of differing size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certificate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have significantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the efforts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production workflows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular workflows, and support troubleshooting and triage in case of problems. Recently a new certificate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specific third-party Certificate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Critical issues in medical education and the implications for telemedicine technology.

PubMed

Mahapatra, Ashok Kumar; Mishra, Saroj Kanta; Kapoor, Lily; Singh, Indra Pratap

2009-01-01

Ensuring quality medical education in all the medical colleges across India based on uniform curriculum prescribed by a regulatory body and maintaining a uniform standard are dependent on availability of an excellent infrastructure. Such infrastructure includes qualified teachers, knowledge resources, learning materials, and advanced education technology, which is a challenge in developing countries due to financial and logistic constraints. Advancement in telecommunication, information science, and technology provides an opportunity to exchange knowledge and skill across geographically dispersed organizations by networking academic medical centers of excellence with medical colleges and institutes to practice distance learning using information and communication technology (ICT)-based tools. These may be as basic as commonly used Web-based tools or may be as advanced as virtual reality, simulation, and telepresence-based collaborative learning environment. The scenario in India is no different from any developing country, but there is considerable progress due to technical advancement in these sectors. Telemedicine and tele-education in health science, is gradually getting adopted into the Indian Health System after decade-long pilot studies across the country. A recent recommendation of the National Knowledge Commission, once implemented, would ensure a gigabyte network across all the educational institutions of the country including medical colleges. Availability of indigenous satellite communication technology and the government policy of free bandwidth provision for societal development sector have added strength to set up infrastructure to pilot several telemedicine educational projects across the country.

Monitoring performance of a highly distributed and complex computing infrastructure in LHCb

NASA Astrophysics Data System (ADS)

Mathe, Z.; Haen, C.; Stagni, F.

2017-10-01

In order to ensure an optimal performance of the LHCb Distributed Computing, based on LHCbDIRAC, it is necessary to be able to inspect the behavior over time of many components: firstly the agents and services on which the infrastructure is built, but also all the computing tasks and data transfers that are managed by this infrastructure. This consists of recording and then analyzing time series of a large number of observables, for which the usage of SQL relational databases is far from optimal. Therefore within DIRAC we have been studying novel possibilities based on NoSQL databases (ElasticSearch, OpenTSDB and InfluxDB) as a result of this study we developed a new monitoring system based on ElasticSearch. It has been deployed on the LHCb Distributed Computing infrastructure for which it collects data from all the components (agents, services, jobs) and allows creating reports through Kibana and a web user interface, which is based on the DIRAC web framework. In this paper we describe this new implementation of the DIRAC monitoring system. We give details on the ElasticSearch implementation within the DIRAC general framework, as well as an overview of the advantages of the pipeline aggregation used for creating a dynamic bucketing of the time series. We present the advantages of using the ElasticSearch DSL high-level library for creating and running queries. Finally we shall present the performances of that system.

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duque, Earl P.N.; Whitlock, Brad J.

High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ inmore » situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.« less

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

A new implementation of full resolution SBAS-DInSAR processing chain for the effective monitoring of structures and infrastructures

NASA Astrophysics Data System (ADS)

Bonano, Manuela; Buonanno, Sabatino; Ojha, Chandrakanta; Berardino, Paolo; Lanari, Riccardo; Zeni, Giovanni; Manunta, Michele

2017-04-01

The advanced DInSAR technique referred to as Small BAseline Subset (SBAS) algorithm has already largely demonstrated its effectiveness to carry out multi-scale and multi-platform surface deformation analyses relevant to both natural and man-made hazards. Thanks to its capability to generate displacement maps and long-term deformation time series at both regional (low resolution analysis) and local (full resolution analysis) spatial scales, it allows to get more insights on the spatial and temporal patterns of localized displacements relevant to single buildings and infrastructures over extended urban areas, with a key role in supporting risk mitigation and preservation activities. The extensive application of the multi-scale SBAS-DInSAR approach in many scientific contexts has gone hand in hand with new SAR satellite mission development, characterized by different frequency bands, spatial resolution, revisit times and ground coverage. This brought to the generation of huge DInSAR data stacks to be efficiently handled, processed and archived, with a strong impact on both the data storage and the computational requirements needed for generating the full resolution SBAS-DInSAR results. Accordingly, innovative and effective solutions for the automatic processing of massive SAR data archives and for the operational management of the derived SBAS-DInSAR products need to be designed and implemented, by exploiting the high efficiency (in terms of portability, scalability and computing performances) of the new ICT methodologies. In this work, we present a novel parallel implementation of the full resolution SBAS-DInSAR processing chain, aimed at investigating localized displacements affecting single buildings and infrastructures relevant to very large urban areas, relying on different granularity level parallelization strategies. The image granularity level is applied in most steps of the SBAS-DInSAR processing chain and exploits the multiprocessor systems with distributed memory. Moreover, in some processing steps very heavy from the computational point of view, the Graphical Processing Units (GPU) are exploited for the processing of blocks working on a pixel-by-pixel basis, requiring strong modifications on some key parts of the sequential full resolution SBAS-DInSAR processing chain. GPU processing is implemented by efficiently exploiting parallel processing architectures (as CUDA) for increasing the computing performances, in terms of optimization of the available GPU memory, as well as reduction of the Input/Output operations on the GPU and of the whole processing time for specific blocks w.r.t. the corresponding sequential implementation, particularly critical in presence of huge DInSAR datasets. Moreover, to efficiently handle the massive amount of DInSAR measurements provided by the new generation SAR constellations (CSK and Sentinel-1), we perform a proper re-design strategy aimed at the robust assimilation of the full resolution SBAS-DInSAR results into the web-based Geonode platform of the Spatial Data Infrastructure, thus allowing the efficient management, analysis and integration of the interferometric results with different data sources.

Transportation Energy Futures Series: Alternative Fuel Infrastructure Expansion: Costs, Resources, Production Capacity, and Retail Availability for Low-Carbon Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melaina, M. W.; Heath, G.; Sandor, D.

2013-04-01

Achieving the Department of Energy target of an 80% reduction in greenhouse gas emissions by 2050 depends on transportation-related strategies combining technology innovation, market adoption, and changes in consumer behavior. This study examines expanding low-carbon transportation fuel infrastructure to achieve deep GHG emissions reductions, with an emphasis on fuel production facilities and retail components serving light-duty vehicles. Three distinct low-carbon fuel supply scenarios are examined: Portfolio: Successful deployment of a range of advanced vehicle and fuel technologies; Combustion: Market dominance by hybridized internal combustion engine vehicles fueled by advanced biofuels and natural gas; Electrification: Market dominance by electric drive vehiclesmore » in the LDV sector, including battery electric, plug-in hybrid, and fuel cell vehicles, that are fueled by low-carbon electricity and hydrogen. A range of possible low-carbon fuel demand outcomes are explored in terms of the scale and scope of infrastructure expansion requirements and evaluated based on fuel costs, energy resource utilization, fuel production infrastructure expansion, and retail infrastructure expansion for LDVs. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored transportation-related strategies for abating GHGs and reducing petroleum dependence.« less

An Open Computing Infrastructure that Facilitates Integrated Product and Process Development from a Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Hale, Mark A.

1996-01-01

Computer applications for design have evolved rapidly over the past several decades, and significant payoffs are being achieved by organizations through reductions in design cycle times. These applications are overwhelmed by the requirements imposed during complex, open engineering systems design. Organizations are faced with a number of different methodologies, numerous legacy disciplinary tools, and a very large amount of data. Yet they are also faced with few interdisciplinary tools for design collaboration or methods for achieving the revolutionary product designs required to maintain a competitive advantage in the future. These organizations are looking for a software infrastructure that integrates current corporate design practices with newer simulation and solution techniques. Such an infrastructure must be robust to changes in both corporate needs and enabling technologies. In addition, this infrastructure must be user-friendly, modular and scalable. This need is the motivation for the research described in this dissertation. The research is focused on the development of an open computing infrastructure that facilitates product and process design. In addition, this research explicitly deals with human interactions during design through a model that focuses on the role of a designer as that of decision-maker. The research perspective here is taken from that of design as a discipline with a focus on Decision-Based Design, Theory of Languages, Information Science, and Integration Technology. Given this background, a Model of IPPD is developed and implemented along the lines of a traditional experimental procedure: with the steps of establishing context, formalizing a theory, building an apparatus, conducting an experiment, reviewing results, and providing recommendations. Based on this Model, Design Processes and Specification can be explored in a structured and implementable architecture. An architecture for exploring design called DREAMS (Developing Robust Engineering Analysis Models and Specifications) has been developed which supports the activities of both meta-design and actual design execution. This is accomplished through a systematic process which is comprised of the stages of Formulation, Translation, and Evaluation. During this process, elements from a Design Specification are integrated into Design Processes. In addition, a software infrastructure was developed and is called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment). This represents a virtual apparatus in the Design Experiment conducted in this research. IMAGE is an innovative architecture because it explicitly supports design-related activities. This is accomplished through a GUI driven and Agent-based implementation of DREAMS. A HSCT design has been adopted from the Framework for Interdisciplinary Design Optimization (FIDO) and is implemented in IMAGE. This problem shows how Design Processes and Specification interact in a design system. In addition, the problem utilizes two different solution models concurrently: optimal and satisfying. The satisfying model allows for more design flexibility and allows a designer to maintain design freedom. As a result of following this experimental procedure, this infrastructure is an open system that it is robust to changes in both corporate needs and computer technologies. The development of this infrastructure leads to a number of significant intellectual contributions: 1) A new approach to implementing IPPD with the aid of a computer; 2) A formal Design Experiment; 3) A combined Process and Specification architecture that is language-based; 4) An infrastructure for exploring design; 5) An integration strategy for implementing computer resources; and 6) A seamless modeling language. The need for these contributions is emphasized by the demand by industry and government agencies for the development of these technologies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

National Research Council

The United States has jurisdiction over 3.4 million square miles of ocean expanse greater than the land area of all fifty states combined. This vast marine area offers researchers opportunities to investigate the ocean's role in an integrated Earth system, but also presents challenges to society, including damaging tsunamis and hurricanes, industrial accidents, and outbreaks of waterborne diseases. The 2010 Gulf of Mexico Deepwater Horizon oil spill and 2011 Japanese earthquake and tsunami are vivid reminders that a broad range of infrastructure is needed to advance our still-incomplete understanding of the ocean. The National Research Council (NRC)'s Ocean Studies Boardmore » was asked by the National Science and Technology Council's Subcommittee on Ocean Science and Technology, comprised of 25 U.S. government agencies, to examine infrastructure needs for ocean research in the year 2030. This request reflects concern, among a myriad of marine issues, over the present state of aging and obsolete infrastructure, insufficient capacity, growing technological gaps, and declining national leadership in marine technological development; issues brought to the nation's attention in 2004 by the U.S. Commission on Ocean Policy. A 15-member committee of experts identified four themes that encompass 32 future ocean research questions enabling stewardship of the environment, protecting life and property, promoting economic vitality, and increasing fundamental scientific understanding. Many of the questions in the report (e.g., sea level rise, sustainable fisheries, the global water cycle) reflect challenging, multidisciplinary science questions that are clearly relevant today, and are likely to take decades of effort to solve. As such, U.S. ocean research will require a growing suite of ocean infrastructure for a range of activities, such as high quality, sustained time series observations or autonomous monitoring at a broad range of spatial and temporal scales. Consequently, a coordinated national plan for making future strategic investments becomes an imperative to address societal needs. Such a plan should be based upon known priorities and should be reviewed every 5-10 years to optimize the federal investment. The committee examined the past 20 years of technological advances and ocean infrastructure investments (such as the rise in use of self-propelled, uncrewed, underwater autonomous vehicles), assessed infrastructure that would be required to address future ocean research questions, and characterized ocean infrastructure trends for 2030. One conclusion was that ships will continue to be essential, especially because they provide a platform for enabling other infrastructure autonomous and remotely operated vehicles; samplers and sensors; moorings and cabled systems; and perhaps most importantly, the human assets of scientists, technical staff, and students. A comprehensive, long-term research fleet plan should be implemented in order to retain access to the sea. The current report also calls for continuing U.S. capability to access fully and partially ice-covered seas; supporting innovation, particularly the development of biogeochemical sensors; enhancing computing and modeling capacity and capability; establishing broadly accessible data management facilities; and increasing interdisciplinary education and promoting a technically-skilled workforce. The committee also provided a framework for prioritizing future investment in ocean infrastructure. They recommend that development, maintenance, or replacement of ocean research infrastructure assets should be prioritized in terms of societal benefit, with particular consideration given to usefulness for addressing important science questions; affordability, efficiency, and longevity; and ability to contribute to other missions or applications. These criteria are the foundation for prioritizing ocean research infrastructure investments by estimating the economic costs and benefits of each potential infrastructure investment, and funding those investments that collectively produce the largest expected net benefit over time. While this type of process is clearly subject to budget constraints, it could quantify the often informal evaluation of linkages between infrastructure, ocean research, the value of information produced, societal objectives, and economic benefits. Addressing the numerous complex science questions facing the entire ocean research enterprise in 2030 from government to academia, industry to nonprofits, local to global scale represents a major challenge, requiring collaboration across the breadth of the ocean sciences community and nearly seamless coordination between ocean-related federal agencies.« less

Challenges in integrating multidisciplinary data into a single e-infrastructure

NASA Astrophysics Data System (ADS)

Atakan, Kuvvet; Jeffery, Keith G.; Bailo, Daniele; Harrison, Matthew

2015-04-01

The European Plate Observing System (EPOS) aims to create a pan-European infrastructure for solid Earth science to support a safe and sustainable society. The mission of EPOS is to monitor and understand the dynamic and complex Earth system by relying on new e-science opportunities and integrating diverse and advanced Research Infrastructures in Europe for solid Earth Science. EPOS will enable innovative multidisciplinary research for a better understanding of the Earth's physical and chemical processes that control earthquakes, volcanic eruptions, ground instability and tsunami as well as the processes driving tectonics and Earth's surface dynamics. EPOS will improve our ability to better manage the use of the subsurface of the Earth. Through integration of data, models and facilities EPOS will allow the Earth Science community to make a step change in developing new concepts and tools for key answers to scientific and socio-economic questions concerning geo-hazards and geo-resources as well as Earth sciences applications to the environment and to human welfare. EPOS is now getting into its Implementation Phase (EPOS-IP). One of the main challenges during the implementation phase is the integration of multidisciplinary data into a single e-infrastructure. Multidisciplinary data are organized and governed by the Thematic Core Services (TCS) and are driven by various scientific communities encompassing a wide spectrum of Earth science disciplines. TCS data, data products and services will be integrated into a platform "the ICS system" that will ensure their interoperability and access to these services by the scientific community as well as other users within the society. This requires dedicated tasks for interactions with the various TCS-WPs, as well as the various distributed ICS (ICS-Ds), such as High Performance Computing (HPC) facilities, large scale data storage facilities, complex processing and visualization tools etc. Computational Earth Science (CES) services are identified as a transversal activity and as such need to be harmonized and provided within the ICS. In order to develop a metadata catalogue and the ICS system, the content from the entire spectrum of services included in TCS, ICS-Ds as well as CES activities, need to be organized in a systematic manner taking into account global and European IT-standards, while complying with the user needs and data provider requirements.

Advancing Water Science through Improved Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Koch, B. J.; Miles, B.; Rai, A.; Ahalt, S.; Band, L. E.; Minsker, B.; Palmer, M.; Williams, M. R.; Idaszak, R.; Whitton, M. C.

2012-12-01

Major scientific advances are needed to help address impacts of climate change and increasing human-mediated environmental modification on the water cycle at global and local scales. However, such advances within the water sciences are limited in part by inadequate information infrastructures. For example, cyberinfrastructure (CI) includes the integrated computer hardware, software, networks, sensors, data, and human capital that enable scientific workflows to be carried out within and among individual research efforts and across varied disciplines. A coordinated transformation of existing CI and development of new CI could accelerate the productivity of water science by enabling greater discovery, access, and interoperability of data and models, and by freeing scientists to do science rather than create and manage technological tools. To elucidate specific ways in which improved CI could advance water science, three challenges confronting the water science community were evaluated: 1) How does ecohydrologic patch structure affect nitrogen transport and fate in watersheds?, 2) How can human-modified environments emulate natural water and nutrient cycling to enhance both human and ecosystem well-being?, 3) How do changes in climate affect water availability to support biodiversity and human needs? We assessed the approaches used by researchers to address components of these challenges, identified barriers imposed by limitations of current CI, and interviewed leaders in various water science subdisciplines to determine the most recent CI tools employed. Our preliminary findings revealed four areas where CI improvements are likely to stimulate scientific advances: 1) sensor networks, 2) data quality assurance/quality control, 3) data and modeling standards, 4) high performance computing. In addition, the full potential of a re-envisioned water science CI cannot be realized without a substantial training component. In light of these findings, we suggest that CI industry-proven practices such as open-source community architecture, agile development methodologies, and sound software engineering methods offer a promising pathway to a transformed water science CI capable of meeting the demands of both individual scientists and community-wide research initiatives.

Grid Computing at GSI for ALICE and FAIR - present and future

NASA Astrophysics Data System (ADS)

Schwarz, Kilian; Uhlig, Florian; Karabowicz, Radoslaw; Montiel-Gonzalez, Almudena; Zynovyev, Mykhaylo; Preuss, Carsten

2012-12-01

The future FAIR experiments CBM and PANDA have computing requirements that fall in a category that could currently not be satisfied by one single computing centre. One needs a larger, distributed computing infrastructure to cope with the amount of data to be simulated and analysed. Since 2002, GSI operates a tier2 center for ALICE@CERN. The central component of the GSI computing facility and hence the core of the ALICE tier2 centre is a LSF/SGE batch farm, currently split into three subclusters with a total of 15000 CPU cores shared by the participating experiments, and accessible both locally and soon also completely via Grid. In terms of data storage, a 5.5 PB Lustre file system, directly accessible from all worker nodes is maintained, as well as a 300 TB xrootd-based Grid storage element. Based on this existing expertise, and utilising ALICE's middleware ‘AliEn’, the Grid infrastructure for PANDA and CBM is being built. Besides a tier0 centre at GSI, the computing Grids of the two FAIR collaborations encompass now more than 17 sites in 11 countries and are constantly expanding. The operation of the distributed FAIR computing infrastructure benefits significantly from the experience gained with the ALICE tier2 centre. A close collaboration between ALICE Offline and FAIR provides mutual advantages. The employment of a common Grid middleware as well as compatible simulation and analysis software frameworks ensure significant synergy effects.

An integrated bioinformatics infrastructure essential for advancing pharmacogenomics and personalized medicine in the context of the FDA's Critical Path Initiative.

PubMed

Tong, Weida; Harris, Stephen C; Fang, Hong; Shi, Leming; Perkins, Roger; Goodsaid, Federico; Frueh, Felix W

2007-01-01

Pharmacogenomics (PGx) is identified in the FDA Critical Path document as a major opportunity for advancing medical product development and personalized medicine. An integrated bioinformatics infrastructure for use in FDA data review is crucial to realize the benefits of PGx for public health. We have developed an integrated bioinformatics tool, called ArrayTrack, for managing, analyzing and interpreting genomic and other biomarker data (e.g. proteomic and metabolomic data). ArrayTrack is a highly flexible and robust software platform, which allows evolving with technological advances and changing user needs. ArrayTrack is used in the routine review of genomic data submitted to the FDA; here, three hypothetical examples of its use in the Voluntary eXploratory Data Submission (VXDS) program are illustrated.: © Published by Elsevier Ltd.

COMBAT: mobile-Cloud-based cOmpute/coMmunications infrastructure for BATtlefield applications

NASA Astrophysics Data System (ADS)

Soyata, Tolga; Muraleedharan, Rajani; Langdon, Jonathan; Funai, Colin; Ames, Scott; Kwon, Minseok; Heinzelman, Wendi

2012-05-01

The amount of data processed annually over the Internet has crossed the zetabyte boundary, yet this Big Data cannot be efficiently processed or stored using today's mobile devices. Parallel to this explosive growth in data, a substantial increase in mobile compute-capability and the advances in cloud computing have brought the state-of-the- art in mobile-cloud computing to an inflection point, where the right architecture may allow mobile devices to run applications utilizing Big Data and intensive computing. In this paper, we propose the MObile Cloud-based Hybrid Architecture (MOCHA), which formulates a solution to permit mobile-cloud computing applications such as object recognition in the battlefield by introducing a mid-stage compute- and storage-layer, called the cloudlet. MOCHA is built on the key observation that many mobile-cloud applications have the following characteristics: 1) they are compute-intensive, requiring the compute-power of a supercomputer, and 2) they use Big Data, requiring a communications link to cloud-based database sources in near-real-time. In this paper, we describe the operation of MOCHA in battlefield applications, by formulating the aforementioned mobile and cloudlet to be housed within a soldier's vest and inside a military vehicle, respectively, and enabling access to the cloud through high latency satellite links. We provide simulations using the traditional mobile-cloud approach as well as utilizing MOCHA with a mid-stage cloudlet to quantify the utility of this architecture. We show that the MOCHA platform for mobile-cloud computing promises a future for critical battlefield applications that access Big Data, which is currently not possible using existing technology.

Exploring Cloud Computing for Large-scale Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

NGScloud: RNA-seq analysis of non-model species using cloud computing.

PubMed

Mora-Márquez, Fernando; Vázquez-Poletti, José Luis; López de Heredia, Unai

2018-05-03

RNA-seq analysis usually requires large computing infrastructures. NGScloud is a bioinformatic system developed to analyze RNA-seq data using the cloud computing services of Amazon that permit the access to ad hoc computing infrastructure scaled according to the complexity of the experiment, so its costs and times can be optimized. The application provides a user-friendly front-end to operate Amazon's hardware resources, and to control a workflow of RNA-seq analysis oriented to non-model species, incorporating the cluster concept, which allows parallel runs of common RNA-seq analysis programs in several virtual machines for faster analysis. NGScloud is freely available at https://github.com/GGFHF/NGScloud/. A manual detailing installation and how-to-use instructions is available with the distribution. unai.lopezdeheredia@upm.es.

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

ESR/ERS white paper on lung cancer screening

PubMed Central

Bonomo, Lorenzo; Gaga, Mina; Nackaerts, Kristiaan; Peled, Nir; Prokop, Mathias; Remy-Jardin, Martine; von Stackelberg, Oyunbileg; Sculier, Jean-Paul

2015-01-01

Lung cancer is the most frequently fatal cancer, with poor survival once the disease is advanced. Annual low dose computed tomography has shown a survival benefit in screening individuals at high risk for lung cancer. Based on the available evidence, the European Society of Radiology and the European Respiratory Society recommend lung cancer screening in comprehensive, quality-assured, longitudinal programmes within a clinical trial or in routine clinical practice at certified multidisciplinary medical centres. Minimum requirements include: standardised operating procedures for low dose image acquisition, computer-assisted nodule evaluation, and positive screening results and their management; inclusion/exclusion criteria; expectation management; and smoking cessation programmes. Further refinements are recommended to increase quality, outcome and cost-effectiveness of lung cancer screening: inclusion of risk models, reduction of effective radiation dose, computer-assisted volumetric measurements and assessment of comorbidities (chronic obstructive pulmonary disease and vascular calcification). All these requirements should be adjusted to the regional infrastructure and healthcare system, in order to exactly define eligibility using a risk model, nodule management and quality assurance plan. The establishment of a central registry, including biobank and image bank, and preferably on a European level, is strongly encouraged. PMID:25929956

Robonaut's Flexible Information Technology Infrastructure

NASA Technical Reports Server (NTRS)

Askew, Scott; Bluethmann, William; Alder, Ken; Ambrose, Robert

2003-01-01

Robonaut, NASA's humanoid robot, is designed to work as both an astronaut assistant and, in certain situations, an astronaut surrogate. This highly dexterous robot performs complex tasks under telepresence control that could previously only be carried out directly by humans. Currently with 47 degrees of freedom (DOF), Robonaut is a state-of-the-art human size telemanipulator system. while many of Robonaut's embedded components have been custom designed to meet packaging or environmental requirements, the primary computing systems used in Robonaut are currently commercial-off-the-shelf (COTS) products which have some correlation to flight qualified computer systems. This loose coupling of information technology (IT) resources allows Robonaut to exploit cost effective solutions while floating the technology base to take advantage of the rapid pace of IT advances. These IT systems utilize a software development environment, which is both compatible with COTS hardware as well as flight proven computing systems, preserving the majority of software development for a flight system. The ability to use highly integrated and flexible COTS software development tools improves productivity while minimizing redesign for a space flight system. Further, the flexibility of Robonaut's software and communication architecture has allowed it to become a widely used distributed development testbed for integrating new capabilities and furthering experimental research.

Applied Operations Research: Augmented Reality in an Industrial Environment

NASA Technical Reports Server (NTRS)

Cole, Stuart K.

2015-01-01

Augmented reality is the application of computer generated data or graphics onto a real world view. Its use provides the operator additional information or a heightened situational awareness. While advancements have been made in automation and diagnostics of high value critical equipment to improve readiness, reliability and maintenance, the need for assisting and support to Operations and Maintenance staff persists. AR can improve the human machine interface where computer capabilities maximize the human experience and analysis capabilities. NASA operates multiple facilities with complex ground based HVCE in support of national aerodynamics and space exploration, and the need exists to improve operational support and close a gap related to capability sustainment where key and experienced staff consistently rotate work assignments and reach their expiration of term of service. The initiation of an AR capability to augment and improve human abilities and training experience in the industrial environment requires planning and establishment of a goal and objectives for the systems and specific applications. This paper explored use of AR in support of Operation staff in real time operation of HVCE and its maintenance. The results identified include identification of specific goal and objectives, challenges related to availability and computer system infrastructure.

Mantle convection on modern supercomputers

NASA Astrophysics Data System (ADS)

Weismüller, Jens; Gmeiner, Björn; Mohr, Marcus; Waluga, Christian; Wohlmuth, Barbara; Rüde, Ulrich; Bunge, Hans-Peter

2015-04-01

Mantle convection is the cause for plate tectonics, the formation of mountains and oceans, and the main driving mechanism behind earthquakes. The convection process is modeled by a system of partial differential equations describing the conservation of mass, momentum and energy. Characteristic to mantle flow is the vast disparity of length scales from global to microscopic, turning mantle convection simulations into a challenging application for high-performance computing. As system size and technical complexity of the simulations continue to increase, design and implementation of simulation models for next generation large-scale architectures demand an interdisciplinary co-design. Here we report about recent advances of the TERRA-NEO project, which is part of the high visibility SPPEXA program, and a joint effort of four research groups in computer sciences, mathematics and geophysical application under the leadership of FAU Erlangen. TERRA-NEO develops algorithms for future HPC infrastructures, focusing on high computational efficiency and resilience in next generation mantle convection models. We present software that can resolve the Earth's mantle with up to 1012 grid points and scales efficiently to massively parallel hardware with more than 50,000 processors. We use our simulations to explore the dynamic regime of mantle convection assessing the impact of small scale processes on global mantle flow.

Parallel Higher-order Finite Element Method for Accurate Field Computations in Wakefield and PIC Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Candel, A.; Kabel, A.; Lee, L.

Over the past years, SLAC's Advanced Computations Department (ACD), under SciDAC sponsorship, has developed a suite of 3D (2D) parallel higher-order finite element (FE) codes, T3P (T2P) and Pic3P (Pic2P), aimed at accurate, large-scale simulation of wakefields and particle-field interactions in radio-frequency (RF) cavities of complex shape. The codes are built on the FE infrastructure that supports SLAC's frequency domain codes, Omega3P and S3P, to utilize conformal tetrahedral (triangular)meshes, higher-order basis functions and quadratic geometry approximation. For time integration, they adopt an unconditionally stable implicit scheme. Pic3P (Pic2P) extends T3P (T2P) to treat charged-particle dynamics self-consistently using the PIC (particle-in-cell)more » approach, the first such implementation on a conformal, unstructured grid using Whitney basis functions. Examples from applications to the International Linear Collider (ILC), Positron Electron Project-II (PEP-II), Linac Coherent Light Source (LCLS) and other accelerators will be presented to compare the accuracy and computational efficiency of these codes versus their counterparts using structured grids.« less

Securing the Data Storage and Processing in Cloud Computing Environment

ERIC Educational Resources Information Center

Owens, Rodney

2013-01-01

Organizations increasingly utilize cloud computing architectures to reduce costs and energy consumption both in the data warehouse and on mobile devices by better utilizing the computing resources available. However, the security and privacy issues with publicly available cloud computing infrastructures have not been studied to a sufficient depth…

Building Efficient Wireless Infrastructures for Pervasive Computing Environments

ERIC Educational Resources Information Center

Sheng, Bo

2010-01-01

Pervasive computing is an emerging concept that thoroughly brings computing devices and the consequent technology into people's daily life and activities. Most of these computing devices are very small, sometimes even "invisible", and often embedded into the objects surrounding people. In addition, these devices usually are not isolated, but…

GEMSS: grid-infrastructure for medical service provision.

PubMed

Benkner, S; Berti, G; Engelbrecht, G; Fingberg, J; Kohring, G; Middleton, S E; Schmidt, R

2005-01-01

The European GEMSS Project is concerned with the creation of medical Grid service prototypes and their evaluation in a secure service-oriented infrastructure for distributed on demand/supercomputing. Key aspects of the GEMSS Grid middleware include negotiable QoS support for time-critical service provision, flexible support for business models, and security at all levels in order to ensure privacy of patient data as well as compliance to EU law. The GEMSS Grid infrastructure is based on a service-oriented architecture and is being built on top of existing standard Grid and Web technologies. The GEMSS infrastructure offers a generic Grid service provision framework that hides the complexity of transforming existing applications into Grid services. For the development of client-side applications or portals, a pluggable component framework has been developed, providing developers with full control over business processes, service discovery, QoS negotiation, and workflow, while keeping their underlying implementation hidden from view. A first version of the GEMSS Grid infrastructure is operational and has been used for the set-up of a Grid test-bed deploying six medical Grid service prototypes including maxillo-facial surgery simulation, neuro-surgery support, radio-surgery planning, inhaled drug-delivery simulation, cardiovascular simulation and advanced image reconstruction. The GEMSS Grid infrastructure is based on standard Web Services technology with an anticipated future transition path towards the OGSA standard proposed by the Global Grid Forum. GEMSS demonstrates that the Grid can be used to provide medical practitioners and researchers with access to advanced simulation and image processing services for improved preoperative planning and near real-time surgical support.

DIRAC universal pilots

NASA Astrophysics Data System (ADS)

Stagni, F.; McNab, A.; Luzzi, C.; Krzemien, W.; Consortium, DIRAC

2017-10-01

In the last few years, new types of computing models, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are in the form of opportunistic ones. Most but not all of these new infrastructures are based on virtualization techniques. In addition, some of them, present opportunities for multi-processor computing slots to the users. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to provide the transparent, uniform interface has become essential. The transparent access to the underlying resources is realized by implementing the pilot model. DIRAC’s newest generation of generic pilots (the so-called Pilots 2.0) are the “pilots for all the skies”, and have been successfully released in production more than a year ago. They use a plugin mechanism that makes them easily adaptable. Pilots 2.0 have been used for fetching and running jobs on every type of resource, being it a Worker Node (WN) behind a CREAM/ARC/HTCondor/DIRAC Computing element, a Virtual Machine running on IaaC infrastructures like Vac or BOINC, on IaaS cloud resources managed by Vcycle, the LHCb High Level Trigger farm nodes, and any type of opportunistic computing resource. Make a machine a “Pilot Machine”, and all diversities between them will disappear. This contribution describes how pilots are made suitable for different resources, and the recent steps taken towards a fully unified framework, including monitoring. Also, the cases of multi-processor computing slots either on real or virtual machines, with the whole node or a partition of it, is discussed.

NiftyNet: a deep-learning platform for medical imaging.

PubMed

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

LEMON - LHC Era Monitoring for Large-Scale Infrastructures

NASA Astrophysics Data System (ADS)

Marian, Babik; Ivan, Fedorko; Nicholas, Hook; Hector, Lansdale Thomas; Daniel, Lenkes; Miroslav, Siket; Denis, Waldron

2011-12-01

At the present time computer centres are facing a massive rise in virtualization and cloud computing as these solutions bring advantages to service providers and consolidate the computer centre resources. However, as a result the monitoring complexity is increasing. Computer centre management requires not only to monitor servers, network equipment and associated software but also to collect additional environment and facilities data (e.g. temperature, power consumption, cooling efficiency, etc.) to have also a good overview of the infrastructure performance. The LHC Era Monitoring (Lemon) system is addressing these requirements for a very large scale infrastructure. The Lemon agent that collects data on every client and forwards the samples to the central measurement repository provides a flexible interface that allows rapid development of new sensors. The system allows also to report on behalf of remote devices such as switches and power supplies. Online and historical data can be visualized via a web-based interface or retrieved via command-line tools. The Lemon Alarm System component can be used for notifying the operator about error situations. In this article, an overview of the Lemon monitoring is provided together with a description of the CERN LEMON production instance. No direct comparison is made with other monitoring tool.

DICOMGrid: a middleware to integrate PACS and EELA-2 grid infrastructure

NASA Astrophysics Data System (ADS)

Moreno, Ramon A.; de Sá Rebelo, Marina; Gutierrez, Marco A.

2010-03-01

Medical images provide lots of information for physicians, but the huge amount of data produced by medical image equipments in a modern Health Institution is not completely explored in its full potential yet. Nowadays medical images are used in hospitals mostly as part of routine activities while its intrinsic value for research is underestimated. Medical images can be used for the development of new visualization techniques, new algorithms for patient care and new image processing techniques. These research areas usually require the use of huge volumes of data to obtain significant results, along with enormous computing capabilities. Such qualities are characteristics of grid computing systems such as EELA-2 infrastructure. The grid technologies allow the sharing of data in large scale in a safe and integrated environment and offer high computing capabilities. In this paper we describe the DicomGrid to store and retrieve medical images, properly anonymized, that can be used by researchers to test new processing techniques, using the computational power offered by grid technology. A prototype of the DicomGrid is under evaluation and permits the submission of jobs into the EELA-2 grid infrastructure while offering a simple interface that requires minimal understanding of the grid operation.

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems

PubMed Central

Menychtas, Andreas; Tsanakas, Panayiotis

2016-01-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging. PMID:27222731

CADC and CANFAR: Extending the role of the data centre

NASA Astrophysics Data System (ADS)

Gaudet, Severin

2015-12-01

Over the past six years, the CADC has moved beyond the astronomy archive data centre to a multi-service system for the community. This evolution is based on two major initiatives. The first is the adoption of International Virtual Observatory Alliance (IVOA) standards in both the system and data architecture of the CADC, including a common characterization data model. The second is the Canadian Advanced Network for Astronomical Research (CANFAR), a digital infrastructure combining the Canadian national research network (CANARIE), cloud processing and storage resources (Compute Canada) and a data centre (Canadian Astronomy Data Centre) into a unified ecosystem for storage and processing for the astronomy community. This talk will describe the architecture and integration of IVOA and CANFAR services into CADC operations, the operational experiences, the lessons learned and future directions

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems.

PubMed

Menychtas, Andreas; Tsanakas, Panayiotis; Maglogiannis, Ilias

2016-03-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kervin, Karina E.; Cook, Robert B.; Michener, William K.

Conventional wisdom makes the suggestion that there are benefits to the creation of shared repositories of scientific data. Funding agencies require that the data from sponsored projects be shared publicly, but individual researchers often see little personal benefit to offset the work of creating easily sharable data. These conflicting forces have led to the emergence of a new role to support researchers: data managers. This paper identifies key differences between the socio-technical context of data managers and other "human infrastructure" roles articulated previously in Computer Supported Cooperative Work (CSCW) literature and summarizes the challenges that data managers face when acceptingmore » data for archival and reuse. Finally, while data managers' work is critical for advancing science and science policy, their work is often invisible and under-appreciated since it takes place behind the scenes.« less

PGAS in-memory data processing for the Processing Unit of the Upgraded Electronics of the Tile Calorimeter of the ATLAS Detector

NASA Astrophysics Data System (ADS)

Ohene-Kwofie, Daniel; Otoo, Ekow

2015-10-01

The ATLAS detector, operated at the Large Hadron Collider (LHC) records proton-proton collisions at CERN every 50ns resulting in a sustained data flow up to PB/s. The upgraded Tile Calorimeter of the ATLAS experiment will sustain about 5PB/s of digital throughput. These massive data rates require extremely fast data capture and processing. Although there has been a steady increase in the processing speed of CPU/GPGPU assembled for high performance computing, the rate of data input and output, even under parallel I/O, has not kept up with the general increase in computing speeds. The problem then is whether one can implement an I/O subsystem infrastructure capable of meeting the computational speeds of the advanced computing systems at the petascale and exascale level. We propose a system architecture that leverages the Partitioned Global Address Space (PGAS) model of computing to maintain an in-memory data-store for the Processing Unit (PU) of the upgraded electronics of the Tile Calorimeter which is proposed to be used as a high throughput general purpose co-processor to the sROD of the upgraded Tile Calorimeter. The physical memory of the PUs are aggregated into a large global logical address space using RDMA- capable interconnects such as PCI- Express to enhance data processing throughput.

Cyber-Physical Correlations for Infrastructure Resilience: A Game-Theoretic Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S; He, Fei; Ma, Chris Y. T.

In several critical infrastructures, the cyber and physical parts are correlated so that disruptions to one affect the other and hence the whole system. These correlations may be exploited to strategically launch components attacks, and hence must be accounted for ensuring the infrastructure resilience, specified by its survival probability. We characterize the cyber-physical interactions at two levels: (i) the failure correlation function specifies the conditional survival probability of cyber sub-infrastructure given the physical sub-infrastructure as a function of their marginal probabilities, and (ii) the individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions. We formulate a resiliencemore » problem for infrastructures composed of discrete components as a game between the provider and attacker, wherein their utility functions consist of an infrastructure survival probability term and a cost term expressed in terms of the number of components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost term, correlation function and sub-infrastructure survival probabilities. These results generalize earlier ones based on linear failure correlation functions and independent component failures. We apply the results to models of cloud computing infrastructures and energy grids.« less

Advancing the Implementation of Hydrologic Models as Web-based Applications

NASA Astrophysics Data System (ADS)

Dahal, P.; Tarboton, D. G.; Castronova, A. M.

2017-12-01

Advanced computer simulations are required to understand hydrologic phenomenon such as rainfall-runoff response, groundwater hydrology, snow hydrology, etc. Building a hydrologic model instance to simulate a watershed requires investment in data (diverse geospatial datasets such as terrain, soil) and computer resources, typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce. This work introduces a web-based prototype infrastructure in the form of a web application that provides researchers with easy to use access to complete hydrological modeling functionality. This includes creating the necessary geospatial and forcing data, preparing input files for a model by applying complex data preprocessing, running the model for a user defined watershed, and saving the results to a web repository. The open source Tethys Platform was used to develop the web app front-end Graphical User Interface (GUI). We used HydroDS, a webservice that provides data preparation processing capability to support backend computations used by the app. Results are saved in HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. The TOPographic Kinematic APproximation and Integration (TOPKAPI) model served as the example for which we developed a complete hydrologic modeling service to demonstrate the approach. The final product is a complete modeling system accessible through the web to create input files, and run the TOPKAPI hydrologic model for a watershed of interest. We are investigating similar functionality for the preparation of input to Regional Hydro-Ecological Simulation System (RHESSys). Key Words: hydrologic modeling, web services, hydrologic information system, HydroShare, HydroDS, Tethys Platform

Elements of an integrated health monitoring framework

NASA Astrophysics Data System (ADS)

Fraser, Michael; Elgamal, Ahmed; Conte, Joel P.; Masri, Sami; Fountain, Tony; Gupta, Amarnath; Trivedi, Mohan; El Zarki, Magda

2003-07-01

Internet technologies are increasingly facilitating real-time monitoring of Bridges and Highways. The advances in wireless communications for instance, are allowing practical deployments for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds and more involved signal analysis techniques. Upon authentication, appropriate action may be authorized for maintenance, early warning, and/or emergency response. In such a strategy, data from thousands of sensors can be analyzed with near real-time and long-term assessment and decision-making implications. Addressing the above, a flexible and scalable (e.g., for an entire Highway system, or portfolio of Networked Civil Infrastructure) software architecture/framework is being developed and implemented. This framework will network and integrate real-time heterogeneous sensor data, database and archiving systems, computer vision, data analysis and interpretation, physics-based numerical simulation of complex structural systems, visualization, reliability & risk analysis, and rational statistical decision-making procedures. Thus, within this framework, data is converted into information, information into knowledge, and knowledge into decision at the end of the pipeline. Such a decision-support system contributes to the vitality of our economy, as rehabilitation, renewal, replacement, and/or maintenance of this infrastructure are estimated to require expenditures in the Trillion-dollar range nationwide, including issues of Homeland security and natural disaster mitigation. A pilot website (http://bridge.ucsd.edu/compositedeck.html) currently depicts some basic elements of the envisioned integrated health monitoring analysis framework.

Bio-inspired Autonomic Structures: a middleware for Telecommunications Ecosystems

NASA Astrophysics Data System (ADS)

Manzalini, Antonio; Minerva, Roberto; Moiso, Corrado

Today, people are making use of several devices for communications, for accessing multi-media content services, for data/information retrieving, for processing, computing, etc.: examples are laptops, PDAs, mobile phones, digital cameras, mp3 players, smart cards and smart appliances. One of the most attracting service scenarios for future Telecommunications and Internet is the one where people will be able to browse any object in the environment they live: communications, sensing and processing of data and services will be highly pervasive. In this vision, people, machines, artifacts and the surrounding space will create a kind of computational environment and, at the same time, the interfaces to the network resources. A challenging technological issue will be interconnection and management of heterogeneous systems and a huge amount of small devices tied together in networks of networks. Moreover, future network and service infrastructures should be able to provide Users and Application Developers (at different levels, e.g., residential Users but also SMEs, LEs, ASPs/Web2.0 Service roviders, ISPs, Content Providers, etc.) with the most appropriate "environment" according to their context and specific needs. Operators must be ready to manage such level of complication enabling their latforms with technological advanced allowing network and services self-supervision and self-adaptation capabilities. Autonomic software solutions, enhanced with innovative bio-inspired mechanisms and algorithms, are promising areas of long term research to face such challenges. This chapter proposes a bio-inspired autonomic middleware capable of leveraging the assets of the underlying network infrastructure whilst, at the same time, supporting the development of future Telecommunications and Internet Ecosystems.

New project to support scientific collaboration electronically

NASA Astrophysics Data System (ADS)

Clauer, C. R.; Rasmussen, C. E.; Niciejewski, R. J.; Killeen, T. L.; Kelly, J. D.; Zambre, Y.; Rosenberg, T. J.; Stauning, P.; Friis-Christensen, E.; Mende, S. B.; Weymouth, T. E.; Prakash, A.; McDaniel, S. E.; Olson, G. M.; Finholt, T. A.; Atkins, D. E.

A new multidisciplinary effort is linking research in the upper atmospheric and space, computer, and behavioral sciences to develop a prototype electronic environment for conducting team science worldwide. A real-world electronic collaboration testbed has been established to support scientific work centered around the experimental operations being conducted with instruments from the Sondrestrom Upper Atmospheric Research Facility in Kangerlussuaq, Greenland. Such group computing environments will become an important component of the National Information Infrastructure initiative, which is envisioned as the high-performance communications infrastructure to support national scientific research.

Managing competing elastic Grid and Cloud scientific computing applications using OpenNebula

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Berzano, D.; Lusso, S.; Masera, M.; Vallero, S.

2015-12-01

Elastic cloud computing applications, i.e. applications that automatically scale according to computing needs, work on the ideal assumption of infinite resources. While large public cloud infrastructures may be a reasonable approximation of this condition, scientific computing centres like WLCG Grid sites usually work in a saturated regime, in which applications compete for scarce resources through queues, priorities and scheduling policies, and keeping a fraction of the computing cores idle to allow for headroom is usually not an option. In our particular environment one of the applications (a WLCG Tier-2 Grid site) is much larger than all the others and cannot autoscale easily. Nevertheless, other smaller applications can benefit of automatic elasticity; the implementation of this property in our infrastructure, based on the OpenNebula cloud stack, will be described and the very first operational experiences with a small number of strategies for timely allocation and release of resources will be discussed.

ENFIN--A European network for integrative systems biology.

PubMed

Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan

2009-11-01

Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

Virtual Geophysics Laboratory: Exploiting the Cloud and Empowering Geophysicsts

NASA Astrophysics Data System (ADS)

Fraser, Ryan; Vote, Josh; Goh, Richard; Cox, Simon

2013-04-01

Over the last five decades geoscientists from Australian state and federal agencies have collected and assembled around 3 Petabytes of geoscience data sets under public funding. As a consequence of technological progress, data is now being acquired at exponential rates and in higher resolution than ever before. Effective use of these big data sets challenges the storage and computational infrastructure of most organizations. The Virtual Geophysics Laboratory (VGL) is a scientific workflow portal addresses some of the resulting issues by providing Australian geophysicists with access to a Web 2.0 or Rich Internet Application (RIA) based integrated environment that exploits eResearch tools and Cloud computing technology, and promotes collaboration between the user community. VGL simplifies and automates large portions of what were previously manually intensive scientific workflow processes, allowing scientists to focus on the natural science problems, rather than computer science and IT. A number of geophysical processing codes are incorporated to support multiple workflows. For example a gravity inversion can be performed by combining the Escript/Finley codes (from the University of Queensland) with the gravity data registered in VGL. Likewise, tectonic processes can also be modeled by combining the Underworld code (from Monash University) with one of the various 3D models available to VGL. Cloud services provide scalable and cost effective compute resources. VGL is built on top of mature standards-compliant information services, many deployed using the Spatial Information Services Stack (SISS), which provides direct access to geophysical data. A large number of data sets from Geoscience Australia assist users in data discovery. GeoNetwork provides a metadata catalog to store workflow results for future use, discovery and provenance tracking. VGL has been developed in collaboration with the research community using incremental software development practices and open source tools. While developed to provide the geophysics research community with a sustainable platform and scalable infrastructure; VGL has also developed a number of concepts, patterns and generic components of which have been reused for cases beyond geophysics, including natural hazards, satellite processing and other areas requiring spatial data discovery and processing. Future plans for VGL include a number of improvements in both functional and non-functional areas in response to its user community needs and advancement in information technologies. In particular, research is underway in the following areas (a) distributed and parallel workflow processing in the cloud, (b) seamless integration with various cloud providers, and (c) integration with virtual laboratories representing other science domains. Acknowledgements: VGL was developed by CSIRO in collaboration with Geoscience Australia, National Computational Infrastructure, Australia National University, Monash University and University of Queensland, and has been supported by the Australian Government's Education Investment Funds through NeCTAR.

Fabrication Infrastructure to Enable Efficient Exploration and Utilization of Space

NASA Technical Reports Server (NTRS)

Howell, Joe T.; Fikes, John C.; McLemore, Carole A.; Manning, Curtis W.; Good, Jim

2007-01-01

Unlike past one-at-a-time mission approaches, system-of-systems infrastructures will be needed to enable ambitious scenarios for sustainable future space exploration and utilization. Fabrication infrastructure will be needed to support habitat structure development, tools and mechanical part fabrication, as well as repair and replacement of ground support and space mission hardware such as life support items, vehicle components and crew systems. The fabrication infrastructure will need the In Situ Fabrication and Repair (ISFR) element, which is working in conjunction with the In Situ Resources Utilization (ISRU) element, to live off the land. The ISFR Element supports the entire life cycle of Exploration by: reducing downtime due to failed components; decreasing risk to crew by recovering quickly from degraded operation of equipment; improving system functionality with advanced geometry capabilities; and enhancing mission safety by reducing assembly part counts of original designs where possible. This paper addresses the fabrication infrastructures that support efficient, affordable, reliable infrastructures for both space exploration systems and logistics; these infrastructures allow sustained, affordable and highly effective operations on the Moon, Mars and beyond.

Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

PubMed

Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

2011-09-07

Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

A Human-Centered Approach to CV Care: Infrastructure Development in Uganda.

PubMed

Longenecker, Christopher T; Kalra, Ankur; Okello, Emmy; Lwabi, Peter; Omagino, John O; Kityo, Cissy; Kamya, Moses R; Webel, Allison R; Simon, Daniel I; Salata, Robert A; Costa, Marco A

2018-04-20

In this case study, we describe an ongoing approach to develop sustainable acute and chronic cardiovascular care infrastructure in Uganda that involves patient and provider participation. Leveraging strong infrastructure for HIV/AIDS care delivery, University Hospitals Harrington Heart and Vascular Institute and Case Western Reserve University have partnered with U.S. and Ugandan collaborators to improve cardiovascular capabilities. The collaboration has solicited innovative solutions from patients and providers focusing on education and advanced training, penicillin supply, diagnostic strategy (e.g., hand-held ultrasound), maternal health, and community awareness. Key outcomes of this approach have been the completion of formal training of the first interventional cardiologists and heart failure specialists in the country, establishment of 4 integrated regional centers of excellence in rheumatic heart disease care with a national rheumatic heart disease registry, a penicillin distribution and adherence support program focused on retention in care, access to imaging technology, and in-country capabilities to treat advanced rheumatic heart valve disease. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

NASA World Wind: Infrastructure for Spatial Data

NASA Technical Reports Server (NTRS)

Hogan, Patrick

2011-01-01

The world has great need for analysis of Earth observation data, be it climate change, carbon monitoring, disaster response, national defense or simply local resource management. To best provide for spatial and time-dependent information analysis, the world benefits from an open standards and open source infrastructure for spatial data. In the spirit of NASA's motto "for the benefit of all" NASA invites the world community to collaboratively advance this core technology. The World Wind infrastructure for spatial data both unites and challenges the world for innovative solutions analyzing spatial data while also allowing absolute command and control over any respective information exchange medium.

Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine

PubMed Central

2016-01-01

Advances in genomic medicine have the potential to change the way we treat human disease, but translating these advances into reality for improving healthcare outcomes depends essentially on our ability to discover disease- and/or drug-associated clinically actionable genetic mutations. Integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a big data infrastructure can provide an efficient and effective way to identify clinically actionable genetic variants for personalized treatments and reduce healthcare costs. We review bioinformatics processing of next-generation sequencing (NGS) data, bioinformatics infrastructures for implementing precision medicine, and bioinformatics approaches for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:27195526

Investigations into Gravitational Wave Emission from Compact Body Inspiral Into Massive Black Holes

NASA Technical Reports Server (NTRS)

Hughes, Scott A.

2004-01-01

Much of the grant's support (and associated time) was used in developmental activity, building infrastructure for the core of the work that the grant supports. Though infrastructure development was the bulk of the activity supported this year, important progress was made in research as well. The two most important "infrastructure" items were in computing hardware and personnel. Research activities were primarily focused on improving and extending. Hughes' Teukolsky-equation-based gravitational-wave generator. Several improvements have been incorporated into this generator.

X-ray-induced acoustic computed tomography of concrete infrastructure

NASA Astrophysics Data System (ADS)

Tang, Shanshan; Ramseyer, Chris; Samant, Pratik; Xiang, Liangzhong

2018-02-01

X-ray-induced Acoustic Computed Tomography (XACT) takes advantage of both X-ray absorption contrast and high ultrasonic resolution in a single imaging modality by making use of the thermoacoustic effect. In XACT, X-ray absorption by defects and other structures in concrete create thermally induced pressure jumps that launch ultrasonic waves, which are then received by acoustic detectors to form images. In this research, XACT imaging was used to non-destructively test and identify defects in concrete. For concrete structures, we conclude that XACT imaging allows multiscale imaging at depths ranging from centimeters to meters, with spatial resolutions from sub-millimeter to centimeters. XACT imaging also holds promise for single-side testing of concrete infrastructure and provides an optimal solution for nondestructive inspection of existing bridges, pavement, nuclear power plants, and other concrete infrastructure.

The Climate-G Portal: a Grid Enabled Scientifc Gateway for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Negro, Alessandro; Aloisio, Giovanni

2010-05-01

Grid portals are web gateways aiming at concealing the underlying infrastructure through a pervasive, transparent, user-friendly, ubiquitous and seamless access to heterogeneous and geographical spread resources (i.e. storage, computational facilities, services, sensors, network, databases). Definitively they provide an enhanced problem-solving environment able to deal with modern, large scale scientific and engineering problems. Scientific gateways are able to introduce a revolution in the way scientists and researchers organize and carry out their activities. Access to distributed resources, complex workflow capabilities, and community-oriented functionalities are just some of the features that can be provided by such a web-based environment. In the context of the EGEE NA4 Earth Science Cluster, Climate-G is a distributed testbed focusing on climate change research topics. The Euro-Mediterranean Center for Climate Change (CMCC) is actively participating in the testbed providing the scientific gateway (Climate-G Portal) to access to the entire infrastructure. The Climate-G Portal has to face important and critical challenges as well as has to satisfy and address key requirements. In the following, the most relevant ones are presented and discussed. Transparency: the portal has to provide a transparent access to the underlying infrastructure preventing users from dealing with low level details and the complexity of a distributed grid environment. Security: users must be authenticated and authorized on the portal to access and exploit portal functionalities. A wide set of roles is needed to clearly assign the proper one to each user. The access to the computational grid must be completely secured, since the target infrastructure to run jobs is a production grid environment. A security infrastructure (based on X509v3 digital certificates) is strongly needed. Pervasivity and ubiquity: the access to the system must be pervasive and ubiquitous. This is easily true due to the nature of the needed web approach. Usability and simplicity: the portal has to provide simple, high level and user friendly interfaces to ease the access and exploitation of the entire system. Coexistence of general purpose and domain oriented services: along with general purpose services (file transfer, job submission, etc.), the portal has to provide domain based services and functionalities. Subsetting of data, visualization of 2D maps around a virtual globe, delivery of maps through OGC compliant interfaces (i.e. Web Map Service - WMS) are just some examples. Since april 2009, about 70 users (85% coming from the climate change community) got access to the portal. A key challenge of this work is the idea to provide users with an integrated working environment, that is a place where scientists can find huge amount of data, complete metadata support, a wide set of data access services, data visualization and analysis tools, easy access to the underlying grid infrastructure and advanced monitoring interfaces.

Building a Cloud Infrastructure for a Virtual Environmental Observatory

NASA Astrophysics Data System (ADS)

El-khatib, Y.; Blair, G. S.; Gemmell, A. L.; Gurney, R. J.

2012-12-01

Environmental science is often fragmented: data is collected by different organizations using mismatched formats and conventions, and models are misaligned and run in isolation. Cloud computing offers a lot of potential in the way of resolving such issues by supporting data from different sources and at various scales, and integrating models to create more sophisticated and collaborative software services. The Environmental Virtual Observatory pilot (EVOp) project, funded by the UK Natural Environment Research Council, aims to demonstrate how cloud computing principles and technologies can be harnessed to develop more effective solutions to pressing environmental issues. The EVOp infrastructure is a tailored one constructed from resources in both private clouds (owned and managed by us) and public clouds (leased from third party providers). All system assets are accessible via a uniform web service interface in order to enable versatile and transparent resource management, and to support fundamental infrastructure properties such as reliability and elasticity. The abstraction that this 'everything as a service' principle brings also supports mashups, i.e. combining different web services (such as models) and data resources of different origins (in situ gauging stations, warehoused data stores, external sources, etc.). We adopt the RESTful style of web services in order to draw a clear line between client and server (i.e. cloud host) and also to keep the server completely stateless. This significantly improves the scalability of the infrastructure and enables easy infrastructure management. For instance, tasks such as load balancing and failure recovery are greatly simplified without the need for techniques such as advance resource reservation or shared block devices. Upon this infrastructure, we developed a web portal composed of a bespoke collection of web-based visualization tools to help bring out relationships or patterns within the data. The portal was designed for use without any programming prerequisites by stakeholders from different backgrounds such as scientists, policy makers, local communities, and the general public. The development of the portal was carried out using an iterative behaviour-driven approach. We have developed six distinct storyboards to determine the requirements of different users. From these, we identified two storyboards to implement during the pilot phase. The first explores flooding at a local catchment scale for farmers and the public. We simulate hydrological interactions to determine where saturated land-surface areas develop. Model parameter values resembling catchment characteristics could be specified either explicitly (for domain specialists) or indirectly using one of several predefined land use scenarios (for less familiar audiences). The second storyboard investigates the diffuse of agricultural pollution at a national level, with regulators as users. We study the flux of Nitrogen and Phosphorus from land to rivers and coastal regions at various scales of drainage and reporting units. This is particularly useful to uncover the impact of existing policy instruments or risk from future environmental changes on the levels of N and P flux.

The development of a cislunar space infrastructure

NASA Technical Reports Server (NTRS)

1988-01-01

The primary objective of the University of Colorado Advanced Mission Design Program is to define the characteristics and evolution of a near-Earth space infrastructure. The envisioned foundation includes a permanently manned, self-sustaining base on the lunar surface, an L1 space station, and a transportation system that anchors these elements to a low Earth orbit (LEO) station. The motivation of this project was based on the idea that a near-Earth space infrastructure is not an end but an important step in a larger plan to expand man's capabilities in space science and technology. The presence of a cislunar space infrastructure would greatly facilitate the staging of future planetary missions, as well as facilitating the full exploration of the potential for science and industry on the lunar surface. This paper will provide a sound rationale and a detailed scenario in support of the cislunar infrastructure design.

Women's health nursing in the context of the National Health Information Infrastructure.

PubMed

Jenkins, Melinda L; Hewitt, Caroline; Bakken, Suzanne

2006-01-01

Nurses must be prepared to participate in the evolving National Health Information Infrastructure and the changes that will consequently occur in health care practice and documentation. Informatics technologies will be used to develop electronic health records with integrated decision support features that will likely lead to enhanced health care quality and safety. This paper provides a summary of the National Health Information Infrastructure and highlights electronic health records and decision support systems within the context of evidence-based practice. Activities at the Columbia University School of Nursing designed to prepare nurses with the necessary informatics competencies to practice in a National Health Information Infrastructure-enabled health care system are described. Data are presented from electronic (personal digital assistant) encounter logs used in our Women's Health Nurse Practitioner program to support evidence-based advanced practice nursing care. Implications for nursing practice, education, and research in the evolving National Health Information Infrastructure are discussed.

Models of Educational Computing @ Home: New Frontiers for Research on Technology in Learning.

ERIC Educational Resources Information Center

Kafai, Yasmin B.; Fishman, Barry J.; Bruckman, Amy S.; Rockman, Saul

2002-01-01

Discusses models of home educational computing that are linked to learning in school and recommends the need for research that addresses the home as a computer-based learning environment. Topics include a history of research on educational computing at home; technological infrastructure, including software and compatibility; Internet access;…

TIGER: A data analysis pipeline for testing the strong-field dynamics of general relativity with gravitational wave signals from coalescing compact binaries

NASA Astrophysics Data System (ADS)

Agathos, M.; Del Pozzo, W.; Li, T. G. F.; Van Den Broeck, C.; Veitch, J.; Vitale, S.

2014-04-01

The direct detection of gravitational waves with upcoming second-generation gravitational wave observatories such as Advanced LIGO and Advanced Virgo will allow us to probe the genuinely strong-field dynamics of general relativity (GR) for the first time. We have developed a data analysis pipeline called TIGER (test infrastructure for general relativity), which uses signals from compact binary coalescences to perform a model-independent test of GR. In this paper we focus on signals from coalescing binary neutron stars, for which sufficiently accurate waveform models are already available which can be generated fast enough on a computer that they can be used in Bayesian inference. By performing numerical experiments in stationary, Gaussian noise, we show that for such systems, TIGER is robust against a number of unmodeled fundamental, astrophysical, and instrumental effects, such as differences between waveform approximants, a limited number of post-Newtonian phase contributions being known, the effects of neutron star tidal deformability on the orbital motion, neutron star spins, and instrumental calibration errors.

A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

NASA Astrophysics Data System (ADS)

Toor, S.; Osmani, L.; Eerola, P.; Kraemer, O.; Lindén, T.; Tarkoma, S.; White, J.

2014-06-01

The challenge of providing a resilient and scalable computational and data management solution for massive scale research environments requires continuous exploration of new technologies and techniques. In this project the aim has been to design a scalable and resilient infrastructure for CERN HEP data analysis. The infrastructure is based on OpenStack components for structuring a private Cloud with the Gluster File System. We integrate the state-of-the-art Cloud technologies with the traditional Grid middleware infrastructure. Our test results show that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability.

!CHAOS: A cloud of controls

NASA Astrophysics Data System (ADS)

Angius, S.; Bisegni, C.; Ciuffetti, P.; Di Pirro, G.; Foggetta, L. G.; Galletti, F.; Gargana, R.; Gioscio, E.; Maselli, D.; Mazzitelli, G.; Michelotti, A.; Orrù, R.; Pistoni, M.; Spagnoli, F.; Spigone, D.; Stecchi, A.; Tonto, T.; Tota, M. A.; Catani, L.; Di Giulio, C.; Salina, G.; Buzzi, P.; Checcucci, B.; Lubrano, P.; Piccini, M.; Fattibene, E.; Michelotto, M.; Cavallaro, S. R.; Diana, B. F.; Enrico, F.; Pulvirenti, S.

2016-01-01

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of aaabstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack.