A Study of Students' Learning Styles, Discipline Attitudes and Knowledge Acquisition in Technology-Enhanced Probability and Statistics Education

PubMed Central

Christou, Nicolas; Dinov, Ivo D.

2011-01-01

Many modern technological advances have direct impact on the format, style and efficacy of delivery and consumption of educational content. For example, various novel communication and information technology tools and resources enable efficient, timely, interactive and graphical demonstrations of diverse scientific concepts. In this manuscript, we report on a meta-study of 3 controlled experiments of using the Statistics Online Computational Resources in probability and statistics courses. Web-accessible SOCR applets, demonstrations, simulations and virtual experiments were used in different courses as treatment and compared to matched control classes utilizing traditional pedagogical approaches. Qualitative and quantitative data we collected for all courses included Felder-Silverman-Soloman index of learning styles, background assessment, pre and post surveys of attitude towards the subject, end-point satisfaction survey, and varieties of quiz, laboratory and test scores. Our findings indicate that students' learning styles and attitudes towards a discipline may be important confounds of their final quantitative performance. The observed positive effects of integrating information technology with established pedagogical techniques may be valid across disciplines within the broader spectrum courses in the science education curriculum. The two critical components of improving science education via blended instruction include instructor training, and development of appropriate activities, simulations and interactive resources. PMID:21603097

Web-based tools for modelling and analysis of multivariate data: California ozone pollution activity

PubMed Central

Dinov, Ivo D.; Christou, Nicolas

2014-01-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting and statistical inference on these data are presented. All components of this case study (data, tools, activity) are freely available online at: http://wiki.stat.ucla.edu/socr/index.php/SOCR_MotionCharts_CAOzoneData. Several types of exploratory (motion charts, box-and-whisker plots, spider charts) and quantitative (inference, regression, analysis of variance (ANOVA)) data analyses tools are demonstrated. Two specific human health related questions (temporal and geographic effects of ozone pollution) are discussed as motivational challenges. PMID:24465054

Web-based tools for modelling and analysis of multivariate data: California ozone pollution activity.

PubMed

Dinov, Ivo D; Christou, Nicolas

2011-09-01

This article presents a hands-on web-based activity motivated by the relation between human health and ozone pollution in California. This case study is based on multivariate data collected monthly at 20 locations in California between 1980 and 2006. Several strategies and tools for data interrogation and exploratory data analysis, model fitting and statistical inference on these data are presented. All components of this case study (data, tools, activity) are freely available online at: http://wiki.stat.ucla.edu/socr/index.php/SOCR_MotionCharts_CAOzoneData. Several types of exploratory (motion charts, box-and-whisker plots, spider charts) and quantitative (inference, regression, analysis of variance (ANOVA)) data analyses tools are demonstrated. Two specific human health related questions (temporal and geographic effects of ozone pollution) are discussed as motivational challenges.

SOCR data dashboard: an integrated big data archive mashing medicare, labor, census and econometric information.

PubMed

Husain, Syed S; Kalinin, Alexandr; Truong, Anh; Dinov, Ivo D

Intuitive formulation of informative and computationally-efficient queries on big and complex datasets present a number of challenges. As data collection is increasingly streamlined and ubiquitous, data exploration, discovery and analytics get considerably harder. Exploratory querying of heterogeneous and multi-source information is both difficult and necessary to advance our knowledge about the world around us. We developed a mechanism to integrate dispersed multi-source data and service the mashed information via human and machine interfaces in a secure, scalable manner. This process facilitates the exploration of subtle associations between variables, population strata, or clusters of data elements, which may be opaque to standard independent inspection of the individual sources. This a new platform includes a device agnostic tool (Dashboard webapp, http://socr.umich.edu/HTML5/Dashboard/) for graphical querying, navigating and exploring the multivariate associations in complex heterogeneous datasets. The paper illustrates this core functionality and serviceoriented infrastructure using healthcare data (e.g., US data from the 2010 Census, Demographic and Economic surveys, Bureau of Labor Statistics, and Center for Medicare Services) as well as Parkinson's Disease neuroimaging data. Both the back-end data archive and the front-end dashboard interfaces are continuously expanded to include additional data elements and new ways to customize the human and machine interactions. A client-side data import utility allows for easy and intuitive integration of user-supplied datasets. This completely open-science framework may be used for exploratory analytics, confirmatory analyses, meta-analyses, and education and training purposes in a wide variety of fields.

Pt–Mg, Pt–Ca, and Pt–Zn lantern complexes and metal-only donor–acceptor interactions [Pt-Mg Pt-Ca and Pt-Zn compounds with metal-only donor-acceptor interactions

DOE PAGES

Baddour, Frederick G.; Hyre, Ariel S.; Guillet, Jesse L.; ...

2016-12-12

Here, Pt-based heterobimetallic lantern complexes of the form [PtM(SOCR) 4(L)] have been shown previously to form intermolecular metallophilic interactions and engage in antiferromagnetic coupling between lanterns having M atoms with open shell configurations. In order to understand better the influence of the carboxylate bridge and terminal ligand on the electronic structure, as well as the metal–metal interactions within each lantern unit, a series of diamagnetic lantern complexes, [PtMg(SAc) 4(OH 2)] (1), [PtMg(tba) 4(OH 2)] (2), [PtCa(tba) 4(OH 2)] (3), [PtZn(tba) 4(OH 2)] (4), and a mononuclear control (Ph 4P) 2[Pt(SAc) 4] (5) have been synthesized. Crystallographic data show close Pt–Mmore » contacts enforced by the lantern structure in each dinuclear case. 195Pt-NMR spectroscopy of 1–4, (Ph 4P) 2[Pt(SAc) 4] (5), and several previously reported lanterns revealed a strong chemical shift dependence on the identity of the second metal (M), mild influence by the thiocarboxylate ligand (SOCR; R = CH 3 (thioacetate, SAc), C 6H 5 (thiobenzoate, tba)), and modest influence from the terminal ligand (L). Fluorescence spectroscopy has provided evidence for a Pt···Zn metallophilic interaction in [PtZn(SAc) 4(OH 2)], and computational studies demonstrate significant dative character. In all of 1–4, the short Pt–M distances suggest that metal-only Lewis donor (Pt)–Lewis acceptor (M) interactions could be present. DFT and NBO calculations, however, show that only the Zn examples have appreciable covalent character, whereas the Mg and Ca complexes are much more ionic.« less

Pt–Mg, Pt–Ca, and Pt–Zn lantern complexes and metal-only donor–acceptor interactions [Pt-Mg Pt-Ca and Pt-Zn compounds with metal-only donor-acceptor interactions

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

Baddour, Frederick G.; Hyre, Ariel S.; Guillet, Jesse L.

Here, Pt-based heterobimetallic lantern complexes of the form [PtM(SOCR) 4(L)] have been shown previously to form intermolecular metallophilic interactions and engage in antiferromagnetic coupling between lanterns having M atoms with open shell configurations. In order to understand better the influence of the carboxylate bridge and terminal ligand on the electronic structure, as well as the metal–metal interactions within each lantern unit, a series of diamagnetic lantern complexes, [PtMg(SAc) 4(OH 2)] (1), [PtMg(tba) 4(OH 2)] (2), [PtCa(tba) 4(OH 2)] (3), [PtZn(tba) 4(OH 2)] (4), and a mononuclear control (Ph 4P) 2[Pt(SAc) 4] (5) have been synthesized. Crystallographic data show close Pt–Mmore » contacts enforced by the lantern structure in each dinuclear case. 195Pt-NMR spectroscopy of 1–4, (Ph 4P) 2[Pt(SAc) 4] (5), and several previously reported lanterns revealed a strong chemical shift dependence on the identity of the second metal (M), mild influence by the thiocarboxylate ligand (SOCR; R = CH 3 (thioacetate, SAc), C 6H 5 (thiobenzoate, tba)), and modest influence from the terminal ligand (L). Fluorescence spectroscopy has provided evidence for a Pt···Zn metallophilic interaction in [PtZn(SAc) 4(OH 2)], and computational studies demonstrate significant dative character. In all of 1–4, the short Pt–M distances suggest that metal-only Lewis donor (Pt)–Lewis acceptor (M) interactions could be present. DFT and NBO calculations, however, show that only the Zn examples have appreciable covalent character, whereas the Mg and Ca complexes are much more ionic.« less

SOCR "Motion Charts": An Efficient, Open-Source, Interactive and Dynamic Applet for Visualizing Longitudinal Multivariate Data

ERIC Educational Resources Information Center

Al-Aziz, Jameel; Christou, Nicolas; Dinov, Ivo D.

2010-01-01

The amount, complexity and provenance of data have dramatically increased in the past five years. Visualization of observed and simulated data is a critical component of any social, environmental, biomedical or scientific quest. Dynamic, exploratory and interactive visualization of multivariate data, without preprocessing by dimensionality…

Sometimes-Competing Retrieval (SOCR): A Formalization of the Comparator Hypothesis

ERIC Educational Resources Information Center

Stout, Steven C.; Miller, Ralph R.

2007-01-01

Cue competition is one of the most studied phenomena in associative learning. However, a theoretical disagreement has long stood over whether it reflects a learning or performance deficit. The comparator hypothesis, a model of expression of Pavlovian associations, posits that learning is not subject to competition but that performance reflects a…

System on a Chip Real-Time Emulation (SOCRE)

DTIC Science & Technology

2006-09-01

code ) i Table of Contents Preface...emulation platform included LDPC decoders, A/V and radio applications Port BEE flow to Emulation Platforms, SOC Technologies One of the key tasks of the...Once the design has been described within Simulink, the designer runs the BEE design flow within Matlab using the bee_xps interface. At this point

Convergent evolution of Amadori opine catabolic systems in plasmids of Agrobacterium tumefaciens.

PubMed

Baek, Chang-Ho; Farrand, Stephen K; Lee, Ko-Eun; Park, Dae-Kyun; Lee, Jeong Kug; Kim, Kun-Soo

2003-01-01

Deoxyfructosyl glutamine (DFG, referred to elsewhere as dfg) is a naturally occurring Amadori compound found in rotting fruits and vegetables. DFG also is an opine and is found in tumors induced by chrysopine-type strains of Agrobacterium tumefaciens. Such strains catabolize this opine via a pathway coded for by their plasmids. NT1, a derivative of the nopaline-type A. tumefaciens strain C58 lacking pTiC58, can utilize DFG as the sole carbon source. Genes for utilization of DFG were mapped to the 543-kb accessory plasmid pAtC58. Two cosmid clones of pAtC58 allowed UIA5, a plasmid-free derivative of C58, harboring pSa-C that expresses MocC (mannopine [MOP] oxidoreductase that oxidizes MOP to DFG), to grow by using MOP as the sole carbon source. Genetic analysis of subclones indicated that the genes for utilization of DFG are located in a 6.2-kb BglII (Bg2) region adjacent to repABC-type genes probably responsible for the replication of pAtC58. This region contains five open reading frames organized into at least two transcriptional soc (santhopine catabolism) groups: socR and socABCD. Nucleotide sequence analysis and analyses of transposon-insertion mutations in the region showed that SocR negatively regulates the expression of socR itself and socABCD. SocA and SocB are responsible for transport of DFG and MOP. SocA is a homolog of known periplasmic amino acid binding proteins. The N-terminal half of SocB is a homolog of the transmembrane transporter proteins for several amino acids, and the C-terminal half is a homolog of the transporter-associated ATP-binding proteins. SocC and SocD could be responsible for the enzymatic degradation of DFG, being homologs of sugar oxidoreductases and an amadoriase from Corynebacterium sp., respectively. The protein products of socABCD are not related at the amino acid sequence level to those of the moc and mot genes of Ti plasmids responsible for utilization of DFG and MOP, indicating that these two sets of genes and their catabolic pathways have evolved convergently from independent origins.

Convergent Evolution of Amadori Opine Catabolic Systems in Plasmids of Agrobacterium tumefaciens

PubMed Central

Baek, Chang-Ho; Farrand, Stephen K.; Lee, Ko-Eun; Park, Dae-Kyun; Lee, Jeong Kug; Kim, Kun-Soo

2003-01-01

Deoxyfructosyl glutamine (DFG, referred to elsewhere as dfg) is a naturally occurring Amadori compound found in rotting fruits and vegetables. DFG also is an opine and is found in tumors induced by chrysopine-type strains of Agrobacterium tumefaciens. Such strains catabolize this opine via a pathway coded for by their plasmids. NT1, a derivative of the nopaline-type A. tumefaciens strain C58 lacking pTiC58, can utilize DFG as the sole carbon source. Genes for utilization of DFG were mapped to the 543-kb accessory plasmid pAtC58. Two cosmid clones of pAtC58 allowed UIA5, a plasmid-free derivative of C58, harboring pSa-C that expresses MocC (mannopine [MOP] oxidoreductase that oxidizes MOP to DFG), to grow by using MOP as the sole carbon source. Genetic analysis of subclones indicated that the genes for utilization of DFG are located in a 6.2-kb BglII (Bg2) region adjacent to repABC-type genes probably responsible for the replication of pAtC58. This region contains five open reading frames organized into at least two transcriptional soc (santhopine catabolism) groups: socR and socABCD. Nucleotide sequence analysis and analyses of transposon-insertion mutations in the region showed that SocR negatively regulates the expression of socR itself and socABCD. SocA and SocB are responsible for transport of DFG and MOP. SocA is a homolog of known periplasmic amino acid binding proteins. The N-terminal half of SocB is a homolog of the transmembrane transporter proteins for several amino acids, and the C-terminal half is a homolog of the transporter-associated ATP-binding proteins. SocC and SocD could be responsible for the enzymatic degradation of DFG, being homologs of sugar oxidoreductases and an amadoriase from Corynebacterium sp., respectively. The protein products of socABCD are not related at the amino acid sequence level to those of the moc and mot genes of Ti plasmids responsible for utilization of DFG and MOP, indicating that these two sets of genes and their catabolic pathways have evolved convergently from independent origins. PMID:12511498

Heterobimetallic Lantern Complexes and Their Novel Structural and Magnetic Properties.

PubMed

Beach, Stephanie A; Doerrer, Linda H

2018-05-15

As the scale of microelectronic circuit devices approaches the atomic limit, the study of molecular-based wires and magnets has become more prevalent. Compounds with quasi-1D geometries have been investigated for their electronic conductivity and magnetic properties with potential use as nanoscale circuit components and information storage devices. To increase the number of compositionally tailored molecular systems available to study, we have taken a building-block, bottom-up approach to the development of improved electronic structure and magnetic properties of quasi-1D arrays. Over the past decade, a large family of asymmetric complexes that can assemble into extended arrays has resulted. Lantern (or paddle-wheel) complexes with conventional {O, O} donor carboxylates are legion, but by the use of monothiocarboxylate ligands and hard-soft Lewis acid-base principles, dozens of new lantern complexes of the form [PtM(SOCR) 4 (L)] (M = Mg, Ca, Cr, Mn, Fe, Co, Ni, Zn; R = Ph (tba = thiobenzoate), CH 3 (SAc = thioacetate); L = neutral or anionic ligand) have been prepared. Depending on M and L, new intermolecular arrangements have resulted, and the magnetic properties have proven particularly interesting. In the solid state, the [PtM(SOCR) 4 (L)] building blocks are sometimes isolated, sometimes form dimers, and can be induced to form infinite chains. The versatility of the lantern motif was demonstrated with a range of axial ligands to form both terminal and bridged complexes with various 3d metals and two different substituted thiocarboxylate backbone ligands. Within the dozens of crystallographically characterized compounds that make up this family of lanterns, several different structural motifs of solid-state dimerization were observed and divided into four distinct categories on the basis of their Pt···Pt and Pt···S distances and relative monomer orientations. Among all of these compounds, three novel magnetic phenomena were observed. Initially, long-range antiferromagnetic coupling between two metals more than 8 Å apart was observed in solid-state dimers formed via metallophilic Pt···Pt interactions and could induced by choice of the terminal L group. An infinite chain was prepared in [PtCr(tba) 4 (NCS)] ∞ that displays ferromagnetic coupling between Cr centers with J/ k B = 1.7(4) K. Homobimetallic quasi-1D chains of the form [Ni 2 (SOCR) 4 (L)] ∞ (R = Ph, CH 3 ; L = DABCO, pyz) were also prepared with S = 1 {Ni 2 } building blocks in which the Ni centers have two different spin states with weak antiferromagnetic coupling along the chain, such that -0.18 > J/ k B > -0.24 K. In the [Ni 2 (tba) 4 (quin)] derivative, a solid-state dimer forms with a bridging square conformation by interlantern Ni 2 S 2 interactions and displays unusual S = 1 configurations on both Ni centers and weak antiferromagnetic coupling between them.

Expression of mucins in the mucosal surface of small intestines in 1 week-old pigs.

PubMed

Kim, Chung Hyun; Oh, Yeonsu; Ha, Yooncheol; Ahn, Qwein; Kim, Sung-Hoon; Cho, Kyung-Dong; Lee, Bog-Hieu; Chae, Chanhee

2010-02-01

The aim of this study was to determine the immunoexpression of mucins in jejunal and ileal villous epithelium using six antibodies against MUC1, MUC2, MUC4 MUC5AC, MUC5B and MUC6. The immunohistochemical score for MUC1 has significantly intense staining compared with MUC2 (P=0.008) and the immunohistochemical socre for MUC4 and MUC 6 has significantly intense staining compared with MUC2 (P=0.032) in ileal villous surface. The immunohistochemical score for MUC4 (P=0.008), MUC5AC (P=0.016) and MUC6 (P=0.016) in ileal villous surface has significantly intense staining compared with ileal cryptic surface. The results of this study demonstrated that six mucins gave distinctly different expression patterns throughout the 1 week-old porcine small intestinal tract.

The effect of modified potato flour substitution on the organoleptics characteristics of toddler biscuit

NASA Astrophysics Data System (ADS)

Cakrawati, Dewi; Rahmawati, Puji

2016-04-01

Toddler biscuit is complementary food given to infants to help meet their nutritional needs. This research was undertaken to develop toddler biscuit with subtitution of physically modified potato flour. There were two puposes of the research, first to know the characteristics of physically modification on potato flour; secondly to know biscuit characteristics with modified potato flour substitution. There were two factor analysis in the development of biscuit; first factor was pre heating mehods and substitution rate. The research was conducted with experimental method using split plot design. The functional properties on modified potato flour as swelling capacity, water absorption capacity, solubility and viscocity were analyzed. Organoleptic analysis using quality hedonic test showed no interaction between potato starch modification and concentration of modified potato flour. Quality hedonic test showed all toddler biscuit socred in the range of “slightly like” to “like moderately”. Modifying potato starch by boiling and steaming with flour concentration of 30% producing toddler biscuit with organoleptic characteristics acceptable according to the panelists.

Controlling user access to electronic resources without password

DOEpatents

Smith, Fred Hewitt

2015-06-16

Described herein are devices and techniques for remotely controlling user access to a restricted computer resource. The process includes pre-determining an association of the restricted computer resource and computer-resource-proximal environmental information. Indicia of user-proximal environmental information are received from a user requesting access to the restricted computer resource. Received indicia of user-proximal environmental information are compared to associated computer-resource-proximal environmental information. User access to the restricted computer resource is selectively granted responsive to a favorable comparison in which the user-proximal environmental information is sufficiently similar to the computer-resource proximal environmental information. In at least some embodiments, the process further includes comparing user-supplied biometric measure and comparing it with a predetermined association of at least one biometric measure of an authorized user. Access to the restricted computer resource is granted in response to a favorable comparison.

Laboratory Computing Resource Center

Science.gov Websites

Systems Computing and Data Resources Purchasing Resources Future Plans For Users Getting Started Using LCRC Software Best Practices and Policies Getting Help Support Laboratory Computing Resource Center Laboratory Computing Resource Center Latest Announcements See All April 27, 2018, Announcements, John Low

Research on elastic resource management for multi-queue under cloud computing environment

NASA Astrophysics Data System (ADS)

CHENG, Zhenjing; LI, Haibo; HUANG, Qiulan; Cheng, Yaodong; CHEN, Gang

2017-10-01

As a new approach to manage computing resource, virtualization technology is more and more widely applied in the high-energy physics field. A virtual computing cluster based on Openstack was built at IHEP, using HTCondor as the job queue management system. In a traditional static cluster, a fixed number of virtual machines are pre-allocated to the job queue of different experiments. However this method cannot be well adapted to the volatility of computing resource requirements. To solve this problem, an elastic computing resource management system under cloud computing environment has been designed. This system performs unified management of virtual computing nodes on the basis of job queue in HTCondor based on dual resource thresholds as well as the quota service. A two-stage pool is designed to improve the efficiency of resource pool expansion. This paper will present several use cases of the elastic resource management system in IHEPCloud. The practical run shows virtual computing resource dynamically expanded or shrunk while computing requirements change. Additionally, the CPU utilization ratio of computing resource was significantly increased when compared with traditional resource management. The system also has good performance when there are multiple condor schedulers and multiple job queues.

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

NASA Astrophysics Data System (ADS)

Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni

2012-09-01

Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

A study of computer graphics technology in application of communication resource management

NASA Astrophysics Data System (ADS)

Li, Jing; Zhou, Liang; Yang, Fei

2017-08-01

With the development of computer technology, computer graphics technology has been widely used. Especially, the success of object-oriented technology and multimedia technology promotes the development of graphics technology in the computer software system. Therefore, the computer graphics theory and application technology have become an important topic in the field of computer, while the computer graphics technology becomes more and more extensive in various fields of application. In recent years, with the development of social economy, especially the rapid development of information technology, the traditional way of communication resource management cannot effectively meet the needs of resource management. In this case, the current communication resource management is still using the original management tools and management methods, resource management equipment management and maintenance, which brought a lot of problems. It is very difficult for non-professionals to understand the equipment and the situation in communication resource management. Resource utilization is relatively low, and managers cannot quickly and accurately understand the resource conditions. Aimed at the above problems, this paper proposes to introduce computer graphics technology into the communication resource management. The introduction of computer graphics not only makes communication resource management more vivid, but also reduces the cost of resource management and improves work efficiency.

A resource management architecture based on complex network theory in cloud computing federation

NASA Astrophysics Data System (ADS)

Zhang, Zehua; Zhang, Xuejie

2011-10-01

Cloud Computing Federation is a main trend of Cloud Computing. Resource Management has significant effect on the design, realization, and efficiency of Cloud Computing Federation. Cloud Computing Federation has the typical characteristic of the Complex System, therefore, we propose a resource management architecture based on complex network theory for Cloud Computing Federation (abbreviated as RMABC) in this paper, with the detailed design of the resource discovery and resource announcement mechanisms. Compare with the existing resource management mechanisms in distributed computing systems, a Task Manager in RMABC can use the historical information and current state data get from other Task Managers for the evolution of the complex network which is composed of Task Managers, thus has the advantages in resource discovery speed, fault tolerance and adaptive ability. The result of the model experiment confirmed the advantage of RMABC in resource discovery performance.

A resource-sharing model based on a repeated game in fog computing.

PubMed

Sun, Yan; Zhang, Nan

2017-03-01

With the rapid development of cloud computing techniques, the number of users is undergoing exponential growth. It is difficult for traditional data centers to perform many tasks in real time because of the limited bandwidth of resources. The concept of fog computing is proposed to support traditional cloud computing and to provide cloud services. In fog computing, the resource pool is composed of sporadic distributed resources that are more flexible and movable than a traditional data center. In this paper, we propose a fog computing structure and present a crowd-funding algorithm to integrate spare resources in the network. Furthermore, to encourage more resource owners to share their resources with the resource pool and to supervise the resource supporters as they actively perform their tasks, we propose an incentive mechanism in our algorithm. Simulation results show that our proposed incentive mechanism can effectively reduce the SLA violation rate and accelerate the completion of tasks.

A review of Computer Science resources for learning and teaching with K-12 computing curricula: an Australian case study

NASA Astrophysics Data System (ADS)

Falkner, Katrina; Vivian, Rebecca

2015-10-01

To support teachers to implement Computer Science curricula into classrooms from the very first year of school, teachers, schools and organisations seek quality curriculum resources to support implementation and teacher professional development. Until now, many Computer Science resources and outreach initiatives have targeted K-12 school-age children, with the intention to engage children and increase interest, rather than to formally teach concepts and skills. What is the educational quality of existing Computer Science resources and to what extent are they suitable for classroom learning and teaching? In this paper, an assessment framework is presented to evaluate the quality of online Computer Science resources. Further, a semi-systematic review of available online Computer Science resources was conducted to evaluate resources available for classroom learning and teaching and to identify gaps in resource availability, using the Australian curriculum as a case study analysis. The findings reveal a predominance of quality resources, however, a number of critical gaps were identified. This paper provides recommendations and guidance for the development of new and supplementary resources and future research.

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.

Provider-Independent Use of the Cloud

NASA Astrophysics Data System (ADS)

Harmer, Terence; Wright, Peter; Cunningham, Christina; Perrott, Ron

Utility computing offers researchers and businesses the potential of significant cost-savings, making it possible for them to match the cost of their computing and storage to their demand for such resources. A utility compute provider enables the purchase of compute infrastructures on-demand; when a user requires computing resources a provider will provision a resource for them and charge them only for their period of use of that resource. There has been a significant growth in the number of cloud computing resource providers and each has a different resource usage model, application process and application programming interface (API)-developing generic multi-resource provider applications is thus difficult and time consuming. We have developed an abstraction layer that provides a single resource usage model, user authentication model and API for compute providers that enables cloud-provider neutral applications to be developed. In this paper we outline the issues in using external resource providers, give examples of using a number of the most popular cloud providers and provide examples of developing provider neutral applications. In addition, we discuss the development of the API to create a generic provisioning model based on a common architecture for cloud computing providers.

dV/dt - Accelerating the Rate of Progress towards Extreme Scale Collaborative Science

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

Livny, Miron

This report introduces publications that report the results of a project that aimed to design a computational framework that enables computational experimentation at scale while supporting the model of “submit locally, compute globally”. The project focuses on estimating application resource needs, finding the appropriate computing resources, acquiring those resources,deploying the applications and data on the resources, managing applications and resources during run.

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

TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

NASA Astrophysics Data System (ADS)

Nelson, J.; Jones, N.; Ames, D. P.

2015-12-01

Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

Using Amazon's Elastic Compute Cloud to dynamically scale CMS computational resources

NASA Astrophysics Data System (ADS)

Evans, D.; Fisk, I.; Holzman, B.; Melo, A.; Metson, S.; Pordes, R.; Sheldon, P.; Tiradani, A.

2011-12-01

Large international scientific collaborations such as the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider have traditionally addressed their data reduction and analysis needs by building and maintaining dedicated computational infrastructure. Emerging cloud computing services such as Amazon's Elastic Compute Cloud (EC2) offer short-term CPU and storage resources with costs based on usage. These services allow experiments to purchase computing resources as needed, without significant prior planning and without long term investments in facilities and their management. We have demonstrated that services such as EC2 can successfully be integrated into the production-computing model of CMS, and find that they work very well as worker nodes. The cost-structure and transient nature of EC2 services makes them inappropriate for some CMS production services and functions. We also found that the resources are not truely "on-demand" as limits and caps on usage are imposed. Our trial workflows allow us to make a cost comparison between EC2 resources and dedicated CMS resources at a University, and conclude that it is most cost effective to purchase dedicated resources for the "base-line" needs of experiments such as CMS. However, if the ability to use cloud computing resources is built into an experiment's software framework before demand requires their use, cloud computing resources make sense for bursting during times when spikes in usage are required.

An Architecture for Cross-Cloud System Management

NASA Astrophysics Data System (ADS)

Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad

The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.

Quantum Computing: Selected Internet Resources for Librarians, Researchers, and the Casually Curious

ERIC Educational Resources Information Center

Cirasella, Jill

2009-01-01

This article presents an annotated selection of the most important and informative Internet resources for learning about quantum computing, finding quantum computing literature, and tracking quantum computing news. All of the quantum computing resources described in this article are freely available, English-language web sites that fall into one…

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.

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

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

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

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

Enabling opportunistic resources for CMS Computing Operations

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

Hufnagel, Dirk

With the increased pressure on computing brought by the higher energy and luminosity from the LHC in Run 2, CMS Computing Operations expects to require the ability to utilize opportunistic resources resources not owned by, or a priori configured for CMS to meet peak demands. In addition to our dedicated resources we look to add computing resources from non CMS grids, cloud resources, and national supercomputing centers. CMS uses the HTCondor/glideinWMS job submission infrastructure for all its batch processing, so such resources will need to be transparently integrated into its glideinWMS pool. Bosco and parrot wrappers are used to enablemore » access and bring the CMS environment into these non CMS resources. Finally, we describe our strategy to supplement our native capabilities with opportunistic resources and our experience so far using them.« less

Enabling opportunistic resources for CMS Computing Operations

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

Hufnagel, Dick

With the increased pressure on computing brought by the higher energy and luminosity from the LHC in Run 2, CMS Computing Operations expects to require the ability to utilize “opportunistic” resources — resources not owned by, or a priori configured for CMS — to meet peak demands. In addition to our dedicated resources we look to add computing resources from non CMS grids, cloud resources, and national supercomputing centers. CMS uses the HTCondor/glideinWMS job submission infrastructure for all its batch processing, so such resources will need to be transparently integrated into its glideinWMS pool. Bosco and parrot wrappers are usedmore » to enable access and bring the CMS environment into these non CMS resources. Here we describe our strategy to supplement our native capabilities with opportunistic resources and our experience so far using them.« less

Enabling opportunistic resources for CMS Computing Operations

DOE PAGES

Hufnagel, Dirk

2015-12-23

With the increased pressure on computing brought by the higher energy and luminosity from the LHC in Run 2, CMS Computing Operations expects to require the ability to utilize opportunistic resources resources not owned by, or a priori configured for CMS to meet peak demands. In addition to our dedicated resources we look to add computing resources from non CMS grids, cloud resources, and national supercomputing centers. CMS uses the HTCondor/glideinWMS job submission infrastructure for all its batch processing, so such resources will need to be transparently integrated into its glideinWMS pool. Bosco and parrot wrappers are used to enablemore » access and bring the CMS environment into these non CMS resources. Finally, we describe our strategy to supplement our native capabilities with opportunistic resources and our experience so far using them.« less

Interoperability of GADU in using heterogeneous Grid resources for bioinformatics applications.

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

Sulakhe, D.; Rodriguez, A.; Wilde, M.

2008-03-01

Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual datamore » system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.« less

Using Mosix for Wide-Area Compuational Resources

USGS Publications Warehouse

Maddox, Brian G.

2004-01-01

One of the problems with using traditional Beowulf-type distributed processing clusters is that they require an investment in dedicated computer resources. These resources are usually needed in addition to pre-existing ones such as desktop computers and file servers. Mosix is a series of modifications to the Linux kernel that creates a virtual computer, featuring automatic load balancing by migrating processes from heavily loaded nodes to less used ones. An extension of the Beowulf concept is to run a Mosixenabled Linux kernel on a large number of computer resources in an organization. This configuration would provide a very large amount of computational resources based on pre-existing equipment. The advantage of this method is that it provides much more processing power than a traditional Beowulf cluster without the added costs of dedicating resources.

Contextuality as a Resource for Models of Quantum Computation with Qubits

NASA Astrophysics Data System (ADS)

Bermejo-Vega, Juan; Delfosse, Nicolas; Browne, Dan E.; Okay, Cihan; Raussendorf, Robert

2017-09-01

A central question in quantum computation is to identify the resources that are responsible for quantum speed-up. Quantum contextuality has been recently shown to be a resource for quantum computation with magic states for odd-prime dimensional qudits and two-dimensional systems with real wave functions. The phenomenon of state-independent contextuality poses a priori an obstruction to characterizing the case of regular qubits, the fundamental building block of quantum computation. Here, we establish contextuality of magic states as a necessary resource for a large class of quantum computation schemes on qubits. We illustrate our result with a concrete scheme related to measurement-based quantum computation.

Computing arrival times of firefighting resources for initial attack

Treesearch

Romain M. Mees

1978-01-01

Dispatching of firefighting resources requires instantaneous or precalculated decisions. A FORTRAN computer program has been developed that can provide a list of resources in order of computed arrival time for initial attack on a fire. The program requires an accurate description of the existing road system and a list of all resources available on a planning unit....

A Review of Computer Science Resources for Learning and Teaching with K-12 Computing Curricula: An Australian Case Study

ERIC Educational Resources Information Center

Falkner, Katrina; Vivian, Rebecca

2015-01-01

To support teachers to implement Computer Science curricula into classrooms from the very first year of school, teachers, schools and organisations seek quality curriculum resources to support implementation and teacher professional development. Until now, many Computer Science resources and outreach initiatives have targeted K-12 school-age…

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Operating Dedicated Data Centers - Is It Cost-Effective?

NASA Astrophysics Data System (ADS)

Ernst, M.; Hogue, R.; Hollowell, C.; Strecker-Kellog, W.; Wong, A.; Zaytsev, A.

2014-06-01

The advent of cloud computing centres such as Amazon's EC2 and Google's Computing Engine has elicited comparisons with dedicated computing clusters. Discussions on appropriate usage of cloud resources (both academic and commercial) and costs have ensued. This presentation discusses a detailed analysis of the costs of operating and maintaining the RACF (RHIC and ATLAS Computing Facility) compute cluster at Brookhaven National Lab and compares them with the cost of cloud computing resources under various usage scenarios. An extrapolation of likely future cost effectiveness of dedicated computing resources is also presented.

Computing the Envelope for Stepwise-Constant Resource Allocations

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Clancy, Daniel (Technical Monitor)

2002-01-01

Computing tight resource-level bounds is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with nodes equal to the events and edges equal to the necessary predecessor links between events. A staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. Each stage has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible and promising for use in the inner loop of flexible-time scheduling algorithms.

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.

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

DTIC Science & Technology

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Experience in using commercial clouds in CMS

NASA Astrophysics Data System (ADS)

Bauerdick, L.; Bockelman, B.; Dykstra, D.; Fuess, S.; Garzoglio, G.; Girone, M.; Gutsche, O.; Holzman, B.; Hufnagel, D.; Kim, H.; Kennedy, R.; Mason, D.; Spentzouris, P.; Timm, S.; Tiradani, A.; Vaandering, E.; CMS Collaboration

2017-10-01

Historically high energy physics computing has been performed on large purpose-built computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.

Experience in using commercial clouds in CMS

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

Bauerdick, L.; Bockelman, B.; Dykstra, D.

Historically high energy physics computing has been performed on large purposebuilt computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is amore » growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.« less

Study on the application of mobile internet cloud computing platform

NASA Astrophysics Data System (ADS)

Gong, Songchun; Fu, Songyin; Chen, Zheng

2012-04-01

The innovative development of computer technology promotes the application of the cloud computing platform, which actually is the substitution and exchange of a sort of resource service models and meets the needs of users on the utilization of different resources after changes and adjustments of multiple aspects. "Cloud computing" owns advantages in many aspects which not merely reduce the difficulties to apply the operating system and also make it easy for users to search, acquire and process the resources. In accordance with this point, the author takes the management of digital libraries as the research focus in this paper, and analyzes the key technologies of the mobile internet cloud computing platform in the operation process. The popularization and promotion of computer technology drive people to create the digital library models, and its core idea is to strengthen the optimal management of the library resource information through computers and construct an inquiry and search platform with high performance, allowing the users to access to the necessary information resources at any time. However, the cloud computing is able to promote the computations within the computers to distribute in a large number of distributed computers, and hence implement the connection service of multiple computers. The digital libraries, as a typical representative of the applications of the cloud computing, can be used to carry out an analysis on the key technologies of the cloud computing.

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

Computer-Based Resource Accounting Model for Automobile Technology Impact Assessment

DOT National Transportation Integrated Search

1976-10-01

A computer-implemented resource accounting model has been developed for assessing resource impacts of future automobile technology options. The resources tracked are materials, energy, capital, and labor. The model has been used in support of the Int...

System Resource Allocations | High-Performance Computing | NREL

Science.gov Websites

Allocations System Resource Allocations To use NREL's high-performance computing (HPC) resources : Compute hours on NREL HPC Systems including Peregrine and Eagle Storage space (in Terabytes) on Peregrine , Eagle and Gyrfalcon. Allocations are principally done in response to an annual call for allocation

Computers as learning resources in the health sciences: impact and issues.

PubMed Central

Ellis, L B; Hannigan, G G

1986-01-01

Starting with two computer terminals in 1972, the Health Sciences Learning Resources Center of the University of Minnesota Bio-Medical Library expanded its instructional facilities to ten terminals and thirty-five microcomputers by 1985. Computer use accounted for 28% of total center circulation. The impact of these resources on health sciences curricula is described and issues related to use, support, and planning are raised and discussed. Judged by their acceptance and educational value, computers are successful health sciences learning resources at the University of Minnesota. PMID:3518843

An emulator for minimizing finite element analysis implementation resources

NASA Technical Reports Server (NTRS)

Melosh, R. J.; Utku, S.; Salama, M.; Islam, M.

1982-01-01

A finite element analysis emulator providing a basis for efficiently establishing an optimum computer implementation strategy when many calculations are involved is described. The SCOPE emulator determines computer resources required as a function of the structural model, structural load-deflection equation characteristics, the storage allocation plan, and computer hardware capabilities. Thereby, it provides data for trading analysis implementation options to arrive at a best strategy. The models contained in SCOPE lead to micro-operation computer counts of each finite element operation as well as overall computer resource cost estimates. Application of SCOPE to the Memphis-Arkansas bridge analysis provides measures of the accuracy of resource assessments. Data indicate that predictions are within 17.3 percent for calculation times and within 3.2 percent for peripheral storage resources for the ELAS code.

Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim

NASA Astrophysics Data System (ADS)

Aneri, Parikh; Sumathy, S.

2017-11-01

Cloud computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the Cloud Computing is consumer provider model. Cloud provider provides resources which consumer can access using cloud computing model in order to build their application based on their demand. Cloud data center is a bulk of resources on shared pool architecture for cloud user to access. Virtualization is the heart of the Cloud computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this cloud computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase cloud resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. CloudSim used in this proposal is an extensible toolkit and it simulates cloud computing environment.

SCEAPI: A unified Restful Web API for High-Performance Computing

NASA Astrophysics Data System (ADS)

Rongqiang, Cao; Haili, Xiao; Shasha, Lu; Yining, Zhao; Xiaoning, Wang; Xuebin, Chi

2017-10-01

The development of scientific computing is increasingly moving to collaborative web and mobile applications. All these applications need high-quality programming interface for accessing heterogeneous computing resources consisting of clusters, grid computing or cloud computing. In this paper, we introduce our high-performance computing environment that integrates computing resources from 16 HPC centers across China. Then we present a bundle of web services called SCEAPI and describe how it can be used to access HPC resources with HTTP or HTTPs protocols. We discuss SCEAPI from several aspects including architecture, implementation and security, and address specific challenges in designing compatible interfaces and protecting sensitive data. We describe the functions of SCEAPI including authentication, file transfer and job management for creating, submitting and monitoring, and how to use SCEAPI in an easy-to-use way. Finally, we discuss how to exploit more HPC resources quickly for the ATLAS experiment by implementing the custom ARC compute element based on SCEAPI, and our work shows that SCEAPI is an easy-to-use and effective solution to extend opportunistic HPC resources.

Software and resources for computational medicinal chemistry

PubMed Central

Liao, Chenzhong; Sitzmann, Markus; Pugliese, Angelo; Nicklaus, Marc C

2011-01-01

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools. PMID:21707404

Exploiting opportunistic resources for ATLAS with ARC CE and the Event Service

NASA Astrophysics Data System (ADS)

Cameron, D.; Filipčič, A.; Guan, W.; Tsulaia, V.; Walker, R.; Wenaus, T.; ATLAS Collaboration

2017-10-01

With ever-greater computing needs and fixed budgets, big scientific experiments are turning to opportunistic resources as a means to add much-needed extra computing power. These resources can be very different in design from those that comprise the Grid computing of most experiments, therefore exploiting them requires a change in strategy for the experiment. They may be highly restrictive in what can be run or in connections to the outside world, or tolerate opportunistic usage only on condition that tasks may be terminated without warning. The Advanced Resource Connector Computing Element (ARC CE) with its nonintrusive architecture is designed to integrate resources such as High Performance Computing (HPC) systems into a computing Grid. The ATLAS experiment developed the ATLAS Event Service (AES) primarily to address the issue of jobs that can be terminated at any point when opportunistic computing capacity is needed by someone else. This paper describes the integration of these two systems in order to exploit opportunistic resources for ATLAS in a restrictive environment. In addition to the technical details, results from deployment of this solution in the SuperMUC HPC centre in Munich are shown.

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.

Design & implementation of distributed spatial computing node based on WPS

NASA Astrophysics Data System (ADS)

Liu, Liping; Li, Guoqing; Xie, Jibo

2014-03-01

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

Economic models for management of resources in peer-to-peer and grid computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Stockinger, Heinz; Giddy, Jonathan; Abramson, David

2001-07-01

The accelerated development in Peer-to-Peer (P2P) and Grid computing has positioned them as promising next generation computing platforms. They enable the creation of Virtual Enterprises (VE) for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. The framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price for goods based on supply-and-demand and their value to the user. They include commodity market, posted price, tenders and auctions. In this paper, we discuss the use of these models for interaction between Grid components in deciding resource value and the necessary infrastructure to realize them. In addition to normal services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. Furthermore, we demonstrate the usage of some of these economic models in resource brokering through Nimrod/G deadline and cost-based scheduling for two different optimization strategies on the World Wide Grid (WWG) testbed that contains peer-to-peer resources located on five continents: Asia, Australia, Europe, North America, and South America.

A cross-sectional evaluation of computer literacy among medical students at a tertiary care teaching hospital in Mumbai, Bombay.

PubMed

Panchabhai, T S; Dangayach, N S; Mehta, V S; Patankar, C V; Rege, N N

2011-01-01

Computer usage capabilities of medical students for introduction of computer-aided learning have not been adequately assessed. Cross-sectional study to evaluate computer literacy among medical students. Tertiary care teaching hospital in Mumbai, India. Participants were administered a 52-question questionnaire, designed to study their background, computer resources, computer usage, activities enhancing computer skills, and attitudes toward computer-aided learning (CAL). The data was classified on the basis of sex, native place, and year of medical school, and the computer resources were compared. The computer usage and attitudes toward computer-based learning were assessed on a five-point Likert scale, to calculate Computer usage score (CUS - maximum 55, minimum 11) and Attitude score (AS - maximum 60, minimum 12). The quartile distribution among the groups with respect to the CUS and AS was compared by chi-squared tests. The correlation between CUS and AS was then tested. Eight hundred and seventy-five students agreed to participate in the study and 832 completed the questionnaire. One hundred and twenty eight questionnaires were excluded and 704 were analyzed. Outstation students had significantly lesser computer resources as compared to local students (P<0.0001). The mean CUS for local students (27.0±9.2, Mean±SD) was significantly higher than outstation students (23.2±9.05). No such difference was observed for the AS. The means of CUS and AS did not differ between males and females. The CUS and AS had positive, but weak correlations for all subgroups. The weak correlation between AS and CUS for all students could be explained by the lack of computer resources or inadequate training to use computers for learning. Providing additional resources would benefit the subset of outstation students with lesser computer resources. This weak correlation between the attitudes and practices of all students needs to be investigated. We believe that this gap can be bridged with a structured computer learning program.

Associative Accounts of Recovery-from-Extinction Effects

PubMed Central

McConnell, Bridget L.; Miller, Ralph R.

2014-01-01

Recovery-from-extinction effects (e.g., spontaneous recovery, renewal, reinstatement, and facilitated reacquisition) have become the focus of much research in recent years. However, despite a great deal of empirical data, there are few theoretical explanations for these effects. This paucity poses a severe limitation on our understanding of these behavioral effects, impedes advances in uncovering neural mechanisms of response recovery, and reduces our potential to prevent relapse after exposure therapy. Towards correcting this oversight, this review takes prominent models of associative learning that have been used in the past and continue to be used today to explain Pavlovian conditioning and extinction, and assesses how each model can be applied to account for recovery-from-extinction effects. The models include the Rescorla-Wagner (1972) model, Mackintosh's (1975) attentional model, Pearce and Hall's (1980) attentional model, Wagner's (1981) SOP model, Pearce's (1987) configural model, McLaren and Mackintosh's (2002) elemental model, and Stout and Miller's (2007) SOCR (comparator hypothesis) model. Each model is assessed for how well it explains or does not explain the various recovery-from-extinction phenomena. We offer some suggestions for how the models might be modified to account for these effects in those instances in which they initially fail. PMID:24707062

Impact of remote sensing upon the planning, management, and development of water resources

NASA Technical Reports Server (NTRS)

Loats, H. L.; Fowler, T. R.; Frech, S. L.

1974-01-01

A survey of the principal water resource users was conducted to determine the impact of new remote data streams on hydrologic computer models. The analysis of the responses and direct contact demonstrated that: (1) the majority of water resource effort of the type suitable to remote sensing inputs is conducted by major federal water resources agencies or through federally stimulated research, (2) the federal government develops most of the hydrologic models used in this effort; and (3) federal computer power is extensive. The computers, computer power, and hydrologic models in current use were determined.

Resource Provisioning in SLA-Based Cluster Computing

NASA Astrophysics Data System (ADS)

Xiong, Kaiqi; Suh, Sang

Cluster computing is excellent for parallel computation. It has become increasingly popular. In cluster computing, a service level agreement (SLA) is a set of quality of services (QoS) and a fee agreed between a customer and an application service provider. It plays an important role in an e-business application. An application service provider uses a set of cluster computing resources to support e-business applications subject to an SLA. In this paper, the QoS includes percentile response time and cluster utilization. We present an approach for resource provisioning in such an environment that minimizes the total cost of cluster computing resources used by an application service provider for an e-business application that often requires parallel computation for high service performance, availability, and reliability while satisfying a QoS and a fee negotiated between a customer and the application service provider. Simulation experiments demonstrate the applicability of the approach.

Acausal measurement-based quantum computing

NASA Astrophysics Data System (ADS)

Morimae, Tomoyuki

2014-07-01

In measurement-based quantum computing, there is a natural "causal cone" among qubits of the resource state, since the measurement angle on a qubit has to depend on previous measurement results in order to correct the effect of by-product operators. If we respect the no-signaling principle, by-product operators cannot be avoided. Here we study the possibility of acausal measurement-based quantum computing by using the process matrix framework [Oreshkov, Costa, and Brukner, Nat. Commun. 3, 1092 (2012), 10.1038/ncomms2076]. We construct a resource process matrix for acausal measurement-based quantum computing restricting local operations to projective measurements. The resource process matrix is an analog of the resource state of the standard causal measurement-based quantum computing. We find that if we restrict local operations to projective measurements the resource process matrix is (up to a normalization factor and trivial ancilla qubits) equivalent to the decorated graph state created from the graph state of the corresponding causal measurement-based quantum computing. We also show that it is possible to consider a causal game whose causal inequality is violated by acausal measurement-based quantum computing.

Step-by-step magic state encoding for efficient fault-tolerant quantum computation

PubMed Central

Goto, Hayato

2014-01-01

Quantum error correction allows one to make quantum computers fault-tolerant against unavoidable errors due to decoherence and imperfect physical gate operations. However, the fault-tolerant quantum computation requires impractically large computational resources for useful applications. This is a current major obstacle to the realization of a quantum computer. In particular, magic state distillation, which is a standard approach to universality, consumes the most resources in fault-tolerant quantum computation. For the resource problem, here we propose step-by-step magic state encoding for concatenated quantum codes, where magic states are encoded step by step from the physical level to the logical one. To manage errors during the encoding, we carefully use error detection. Since the sizes of intermediate codes are small, it is expected that the resource overheads will become lower than previous approaches based on the distillation at the logical level. Our simulation results suggest that the resource requirements for a logical magic state will become comparable to those for a single logical controlled-NOT gate. Thus, the present method opens a new possibility for efficient fault-tolerant quantum computation. PMID:25511387

Step-by-step magic state encoding for efficient fault-tolerant quantum computation.

PubMed

Goto, Hayato

2014-12-16

Quantum error correction allows one to make quantum computers fault-tolerant against unavoidable errors due to decoherence and imperfect physical gate operations. However, the fault-tolerant quantum computation requires impractically large computational resources for useful applications. This is a current major obstacle to the realization of a quantum computer. In particular, magic state distillation, which is a standard approach to universality, consumes the most resources in fault-tolerant quantum computation. For the resource problem, here we propose step-by-step magic state encoding for concatenated quantum codes, where magic states are encoded step by step from the physical level to the logical one. To manage errors during the encoding, we carefully use error detection. Since the sizes of intermediate codes are small, it is expected that the resource overheads will become lower than previous approaches based on the distillation at the logical level. Our simulation results suggest that the resource requirements for a logical magic state will become comparable to those for a single logical controlled-NOT gate. Thus, the present method opens a new possibility for efficient fault-tolerant quantum computation.

A Review of Resources for Evaluating K-12 Computer Science Education Programs

ERIC Educational Resources Information Center

Randolph, Justus J.; Hartikainen, Elina

2004-01-01

Since computer science education is a key to preparing students for a technologically-oriented future, it makes sense to have high quality resources for conducting summative and formative evaluation of those programs. This paper describes the results of a critical analysis of the resources for evaluating K-12 computer science education projects.…

Computing the Envelope for Stepwise Constant Resource Allocations

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Clancy, Daniel (Technical Monitor)

2001-01-01

Estimating tight resource level is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with noises equal to the events and edges equal to the necessary predecessor links between events. The incremental solution of a staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. The staged algorithm has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible for use in the inner loop of search-based scheduling algorithms.

A lightweight distributed framework for computational offloading in mobile cloud computing.

PubMed

Shiraz, Muhammad; Gani, Abdullah; Ahmad, Raja Wasim; Adeel Ali Shah, Syed; Karim, Ahmad; Rahman, Zulkanain Abdul

2014-01-01

The latest developments in mobile computing technology have enabled intensive applications on the modern Smartphones. However, such applications are still constrained by limitations in processing potentials, storage capacity and battery lifetime of the Smart Mobile Devices (SMDs). Therefore, Mobile Cloud Computing (MCC) leverages the application processing services of computational clouds for mitigating resources limitations in SMDs. Currently, a number of computational offloading frameworks are proposed for MCC wherein the intensive components of the application are outsourced to computational clouds. Nevertheless, such frameworks focus on runtime partitioning of the application for computational offloading, which is time consuming and resources intensive. The resource constraint nature of SMDs require lightweight procedures for leveraging computational clouds. Therefore, this paper presents a lightweight framework which focuses on minimizing additional resources utilization in computational offloading for MCC. The framework employs features of centralized monitoring, high availability and on demand access services of computational clouds for computational offloading. As a result, the turnaround time and execution cost of the application are reduced. The framework is evaluated by testing prototype application in the real MCC environment. The lightweight nature of the proposed framework is validated by employing computational offloading for the proposed framework and the latest existing frameworks. Analysis shows that by employing the proposed framework for computational offloading, the size of data transmission is reduced by 91%, energy consumption cost is minimized by 81% and turnaround time of the application is decreased by 83.5% as compared to the existing offloading frameworks. Hence, the proposed framework minimizes additional resources utilization and therefore offers lightweight solution for computational offloading in MCC.

A Lightweight Distributed Framework for Computational Offloading in Mobile Cloud Computing

PubMed Central

Shiraz, Muhammad; Gani, Abdullah; Ahmad, Raja Wasim; Adeel Ali Shah, Syed; Karim, Ahmad; Rahman, Zulkanain Abdul

2014-01-01

The latest developments in mobile computing technology have enabled intensive applications on the modern Smartphones. However, such applications are still constrained by limitations in processing potentials, storage capacity and battery lifetime of the Smart Mobile Devices (SMDs). Therefore, Mobile Cloud Computing (MCC) leverages the application processing services of computational clouds for mitigating resources limitations in SMDs. Currently, a number of computational offloading frameworks are proposed for MCC wherein the intensive components of the application are outsourced to computational clouds. Nevertheless, such frameworks focus on runtime partitioning of the application for computational offloading, which is time consuming and resources intensive. The resource constraint nature of SMDs require lightweight procedures for leveraging computational clouds. Therefore, this paper presents a lightweight framework which focuses on minimizing additional resources utilization in computational offloading for MCC. The framework employs features of centralized monitoring, high availability and on demand access services of computational clouds for computational offloading. As a result, the turnaround time and execution cost of the application are reduced. The framework is evaluated by testing prototype application in the real MCC environment. The lightweight nature of the proposed framework is validated by employing computational offloading for the proposed framework and the latest existing frameworks. Analysis shows that by employing the proposed framework for computational offloading, the size of data transmission is reduced by 91%, energy consumption cost is minimized by 81% and turnaround time of the application is decreased by 83.5% as compared to the existing offloading frameworks. Hence, the proposed framework minimizes additional resources utilization and therefore offers lightweight solution for computational offloading in MCC. PMID:25127245

COMPUTATIONAL TOXICOLOGY-WHERE IS THE DATA? ...

EPA Pesticide Factsheets

This talk will briefly describe the state of the data world for computational toxicology and one approach to improve the situation, called ACToR (Aggregated Computational Toxicology Resource). This talk will briefly describe the state of the data world for computational toxicology and one approach to improve the situation, called ACToR (Aggregated Computational Toxicology Resource).

LaRC local area networks to support distributed computing

NASA Technical Reports Server (NTRS)

Riddle, E. P.

1984-01-01

The Langley Research Center's (LaRC) Local Area Network (LAN) effort is discussed. LaRC initiated the development of a LAN to support a growing distributed computing environment at the Center. The purpose of the network is to provide an improved capability (over inteactive and RJE terminal access) for sharing multivendor computer resources. Specifically, the network will provide a data highway for the transfer of files between mainframe computers, minicomputers, work stations, and personal computers. An important influence on the overall network design was the vital need of LaRC researchers to efficiently utilize the large CDC mainframe computers in the central scientific computing facility. Although there was a steady migration from a centralized to a distributed computing environment at LaRC in recent years, the work load on the central resources increased. Major emphasis in the network design was on communication with the central resources within the distributed environment. The network to be implemented will allow researchers to utilize the central resources, distributed minicomputers, work stations, and personal computers to obtain the proper level of computing power to efficiently perform their jobs.

An approach for heterogeneous and loosely coupled geospatial data distributed computing

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Fengru; Fang, Yu; Huang, Zhou; Lin, Hui

2010-07-01

Most GIS (Geographic Information System) applications tend to have heterogeneous and autonomous geospatial information resources, and the availability of these local resources is unpredictable and dynamic under a distributed computing environment. In order to make use of these local resources together to solve larger geospatial information processing problems that are related to an overall situation, in this paper, with the support of peer-to-peer computing technologies, we propose a geospatial data distributed computing mechanism that involves loosely coupled geospatial resource directories and a term named as Equivalent Distributed Program of global geospatial queries to solve geospatial distributed computing problems under heterogeneous GIS environments. First, a geospatial query process schema for distributed computing as well as a method for equivalent transformation from a global geospatial query to distributed local queries at SQL (Structured Query Language) level to solve the coordinating problem among heterogeneous resources are presented. Second, peer-to-peer technologies are used to maintain a loosely coupled network environment that consists of autonomous geospatial information resources, thus to achieve decentralized and consistent synchronization among global geospatial resource directories, and to carry out distributed transaction management of local queries. Finally, based on the developed prototype system, example applications of simple and complex geospatial data distributed queries are presented to illustrate the procedure of global geospatial information processing.

NASA Center for Computational Sciences: History and Resources

NASA Technical Reports Server (NTRS)

2000-01-01

The Nasa Center for Computational Sciences (NCCS) has been a leading capacity computing facility, providing a production environment and support resources to address the challenges facing the Earth and space sciences research community.

Now and next-generation sequencing techniques: future of sequence analysis using cloud computing.

PubMed

Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

2012-01-01

Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed "cloud computing") has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows.

30 CFR 1206.154 - Determination of quantities and qualities for computing royalties.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Determination of quantities and qualities for computing royalties. 1206.154 Section 1206.154 Mineral Resources OFFICE OF NATURAL RESOURCES REVENUE, DEPARTMENT OF THE INTERIOR NATURAL RESOURCES REVENUE PRODUCT VALUATION Federal Gas § 1206.154 Determination...

30 CFR 1206.154 - Determination of quantities and qualities for computing royalties.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Determination of quantities and qualities for computing royalties. 1206.154 Section 1206.154 Mineral Resources OFFICE OF NATURAL RESOURCES REVENUE, DEPARTMENT OF THE INTERIOR NATURAL RESOURCES REVENUE PRODUCT VALUATION Federal Gas § 1206.154 Determination...

30 CFR 1206.154 - Determination of quantities and qualities for computing royalties.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Determination of quantities and qualities for computing royalties. 1206.154 Section 1206.154 Mineral Resources OFFICE OF NATURAL RESOURCES REVENUE, DEPARTMENT OF THE INTERIOR NATURAL RESOURCES REVENUE PRODUCT VALUATION Federal Gas § 1206.154 Determination...

Tools and Techniques for Measuring and Improving Grid Performance

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Frumkin, M.; Smith, W.; VanderWijngaart, R.; Wong, P.; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation provides information on NASA's geographically dispersed computing resources, and the various methods by which the disparate technologies are integrated within a nationwide computational grid. Many large-scale science and engineering projects are accomplished through the interaction of people, heterogeneous computing resources, information systems and instruments at different locations. The overall goal is to facilitate the routine interactions of these resources to reduce the time spent in design cycles, particularly for NASA's mission critical projects. The IPG (Information Power Grid) seeks to implement NASA's diverse computing resources in a fashion similar to the way in which electric power is made available.

SaaS enabled admission control for MCMC simulation in cloud computing infrastructures

NASA Astrophysics Data System (ADS)

Vázquez-Poletti, J. L.; Moreno-Vozmediano, R.; Han, R.; Wang, W.; Llorente, I. M.

2017-02-01

Markov Chain Monte Carlo (MCMC) methods are widely used in the field of simulation and modelling of materials, producing applications that require a great amount of computational resources. Cloud computing represents a seamless source for these resources in the form of HPC. However, resource over-consumption can be an important drawback, specially if the cloud provision process is not appropriately optimized. In the present contribution we propose a two-level solution that, on one hand, takes advantage of approximate computing for reducing the resource demand and on the other, uses admission control policies for guaranteeing an optimal provision to running applications.

Functional requirements of computer systems for the U.S. Geological Survey, Water Resources Division, 1988-97

USGS Publications Warehouse

Hathaway, R.M.; McNellis, J.M.

1989-01-01

Investigating the occurrence, quantity, quality, distribution, and movement of the Nation 's water resources is the principal mission of the U.S. Geological Survey 's Water Resources Division. Reports of these investigations are published and available to the public. To accomplish this mission, the Division requires substantial computer technology to process, store, and analyze data from more than 57,000 hydrologic sites. The Division 's computer resources are organized through the Distributed Information System Program Office that manages the nationwide network of computers. The contract that provides the major computer components for the Water Resources Division 's Distributed information System expires in 1991. Five work groups were organized to collect the information needed to procure a new generation of computer systems for the U. S. Geological Survey, Water Resources Division. Each group was assigned a major Division activity and asked to describe its functional requirements of computer systems for the next decade. The work groups and major activities are: (1) hydrologic information; (2) hydrologic applications; (3) geographic information systems; (4) reports and electronic publishing; and (5) administrative. The work groups identified 42 functions and described their functional requirements for 1988, 1992, and 1997. A few new functions such as Decision Support Systems and Executive Information Systems, were identified, but most are the same as performed today. Although the number of functions will remain about the same, steady growth in the size, complexity, and frequency of many functions is predicted for the next decade. No compensating increase in the Division 's staff is anticipated during this period. To handle the increased workload and perform these functions, new approaches will be developed that use advanced computer technology. The advanced technology is required in a unified, tightly coupled system that will support all functions simultaneously. The new approaches and expanded use of computers will require substantial increases in the quantity and sophistication of the Division 's computer resources. The requirements presented in this report will be used to develop technical specifications that describe the computer resources needed during the 1990's. (USGS)

Setting Up a Grid-CERT: Experiences of an Academic CSIRT

ERIC Educational Resources Information Center

Moller, Klaus

2007-01-01

Purpose: Grid computing has often been heralded as the next logical step after the worldwide web. Users of grids can access dynamic resources such as computer storage and use the computing resources of computers under the umbrella of a virtual organisation. Although grid computing is often compared to the worldwide web, it is vastly more complex…

A Novel Resource Management Method of Providing Operating System as a Service for Mobile Transparent Computing

PubMed Central

Huang, Suzhen; Wu, Min; Zhang, Yaoxue; She, Jinhua

2014-01-01

This paper presents a framework for mobile transparent computing. It extends the PC transparent computing to mobile terminals. Since resources contain different kinds of operating systems and user data that are stored in a remote server, how to manage the network resources is essential. In this paper, we apply the technologies of quick emulator (QEMU) virtualization and mobile agent for mobile transparent computing (MTC) to devise a method of managing shared resources and services management (SRSM). It has three layers: a user layer, a manage layer, and a resource layer. A mobile virtual terminal in the user layer and virtual resource management in the manage layer cooperate to maintain the SRSM function accurately according to the user's requirements. An example of SRSM is used to validate this method. Experiment results show that the strategy is effective and stable. PMID:24883353

A novel resource management method of providing operating system as a service for mobile transparent computing.

PubMed

Xiong, Yonghua; Huang, Suzhen; Wu, Min; Zhang, Yaoxue; She, Jinhua

2014-01-01

This paper presents a framework for mobile transparent computing. It extends the PC transparent computing to mobile terminals. Since resources contain different kinds of operating systems and user data that are stored in a remote server, how to manage the network resources is essential. In this paper, we apply the technologies of quick emulator (QEMU) virtualization and mobile agent for mobile transparent computing (MTC) to devise a method of managing shared resources and services management (SRSM). It has three layers: a user layer, a manage layer, and a resource layer. A mobile virtual terminal in the user layer and virtual resource management in the manage layer cooperate to maintain the SRSM function accurately according to the user's requirements. An example of SRSM is used to validate this method. Experiment results show that the strategy is effective and stable.

Networking Micro-Processors for Effective Computer Utilization in Nursing

PubMed Central

Mangaroo, Jewellean; Smith, Bob; Glasser, Jay; Littell, Arthur; Saba, Virginia

1982-01-01

Networking as a social entity has important implications for maximizing computer resources for improved utilization in nursing. This paper describes the one process of networking of complementary resources at three institutions. Prairie View A&M University, Texas A&M University and the University of Texas School of Public Health, which has effected greater utilization of computers at the college. The results achieved in this project should have implications for nurses, users, and consumers in the development of computer resources.

Assessing attitudes toward computers and the use of Internet resources among undergraduate microbiology students

NASA Astrophysics Data System (ADS)

Anderson, Delia Marie Castro

Computer literacy and use have become commonplace in our colleges and universities. In an environment that demands the use of technology, educators should be knowledgeable of the components that make up the overall computer attitude of students and be willing to investigate the processes and techniques of effective teaching and learning that can take place with computer technology. The purpose of this study is two fold. First, it investigates the relationship between computer attitudes and gender, ethnicity, and computer experience. Second, it addresses the question of whether, and to what extent, students' attitudes toward computers change over a 16 week period in an undergraduate microbiology course that supplements the traditional lecture with computer-driven assignments. Multiple regression analyses, using data from the Computer Attitudes Scale (Loyd & Loyd, 1985), showed that, in the experimental group, no significant relationships were found between computer anxiety and gender or ethnicity or between computer confidence and gender or ethnicity. However, students who used computers the longest (p = .001) and who were self-taught (p = .046) had the lowest computer anxiety levels. Likewise students who used computers the longest (p = .001) and who were self-taught (p = .041) had the highest confidence levels. No significant relationships between computer liking, usefulness, or the use of Internet resources and gender, ethnicity, or computer experience were found. Dependent T-tests were performed to determine whether computer attitude scores (pretest and posttest) increased over a 16-week period for students who had been exposed to computer-driven assignments and other Internet resources. Results showed that students in the experimental group were less anxious about working with computers and considered computers to be more useful. In the control group, no significant changes in computer anxiety, confidence, liking, or usefulness were noted. Overall, students in the experimental group, who responded to the use of Internet Resources Survey, were positive (mean of 3.4 on the 4-point scale) toward their use of Internet resources which included the online courseware developed by the researcher. Findings from this study suggest that (1) the digital divide with respect to gender and ethnicity may be narrowing, and (2) students who are exposed to a course that augments computer-driven courseware with traditional teaching methods appear to have less anxiety, have a clearer perception of computer usefulness, and feel that online resources enhance their learning.

Desktop Computing Integration Project

NASA Technical Reports Server (NTRS)

Tureman, Robert L., Jr.

1992-01-01

The Desktop Computing Integration Project for the Human Resources Management Division (HRMD) of LaRC was designed to help division personnel use personal computing resources to perform job tasks. The three goals of the project were to involve HRMD personnel in desktop computing, link mainframe data to desktop capabilities, and to estimate training needs for the division. The project resulted in increased usage of personal computers by Awards specialists, an increased awareness of LaRC resources to help perform tasks, and personal computer output that was used in presentation of information to center personnel. In addition, the necessary skills for HRMD personal computer users were identified. The Awards Office was chosen for the project because of the consistency of their data requests and the desire of employees in that area to use the personal computer.

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

DOE PAGES

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian; ...

2017-09-29

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

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

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

The Relative Effectiveness of Computer-Based and Traditional Resources for Education in Anatomy

ERIC Educational Resources Information Center

Khot, Zaid; Quinlan, Kaitlyn; Norman, Geoffrey R.; Wainman, Bruce

2013-01-01

There is increasing use of computer-based resources to teach anatomy, although no study has compared computer-based learning to traditional. In this study, we examine the effectiveness of three formats of anatomy learning: (1) a virtual reality (VR) computer-based module, (2) a static computer-based module providing Key Views (KV), (3) a plastic…

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.

Now and Next-Generation Sequencing Techniques: Future of Sequence Analysis Using Cloud Computing

PubMed Central

Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

2012-01-01

Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed “cloud computing”) has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows. PMID:23248640

Consolidating WLCG topology and configuration in the Computing Resource Information Catalogue

DOE PAGES

Alandes, Maria; Andreeva, Julia; Anisenkov, Alexey; ...

2017-10-01

Here, the Worldwide LHC Computing Grid infrastructure links about 200 participating computing centres affiliated with several partner projects. It is built by integrating heterogeneous computer and storage resources in diverse data centres all over the world and provides CPU and storage capacity to the LHC experiments to perform data processing and physics analysis. In order to be used by the experiments, these distributed resources should be well described, which implies easy service discovery and detailed description of service configuration. Currently this information is scattered over multiple generic information sources like GOCDB, OIM, BDII and experiment-specific information systems. Such a modelmore » does not allow to validate topology and configuration information easily. Moreover, information in various sources is not always consistent. Finally, the evolution of computing technologies introduces new challenges. Experiments are more and more relying on opportunistic resources, which by their nature are more dynamic and should also be well described in the WLCG information system. This contribution describes the new WLCG configuration service CRIC (Computing Resource Information Catalogue) which collects information from various information providers, performs validation and provides a consistent set of UIs and APIs to the LHC VOs for service discovery and usage configuration. The main requirements for CRIC are simplicity, agility and robustness. CRIC should be able to be quickly adapted to new types of computing resources, new information sources, and allow for new data structures to be implemented easily following the evolution of the computing models and operations of the experiments.« less

Consolidating WLCG topology and configuration in the Computing Resource Information Catalogue

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

Alandes, Maria; Andreeva, Julia; Anisenkov, Alexey

Here, the Worldwide LHC Computing Grid infrastructure links about 200 participating computing centres affiliated with several partner projects. It is built by integrating heterogeneous computer and storage resources in diverse data centres all over the world and provides CPU and storage capacity to the LHC experiments to perform data processing and physics analysis. In order to be used by the experiments, these distributed resources should be well described, which implies easy service discovery and detailed description of service configuration. Currently this information is scattered over multiple generic information sources like GOCDB, OIM, BDII and experiment-specific information systems. Such a modelmore » does not allow to validate topology and configuration information easily. Moreover, information in various sources is not always consistent. Finally, the evolution of computing technologies introduces new challenges. Experiments are more and more relying on opportunistic resources, which by their nature are more dynamic and should also be well described in the WLCG information system. This contribution describes the new WLCG configuration service CRIC (Computing Resource Information Catalogue) which collects information from various information providers, performs validation and provides a consistent set of UIs and APIs to the LHC VOs for service discovery and usage configuration. The main requirements for CRIC are simplicity, agility and robustness. CRIC should be able to be quickly adapted to new types of computing resources, new information sources, and allow for new data structures to be implemented easily following the evolution of the computing models and operations of the experiments.« less

Consolidating WLCG topology and configuration in the Computing Resource Information Catalogue

NASA Astrophysics Data System (ADS)

Alandes, Maria; Andreeva, Julia; Anisenkov, Alexey; Bagliesi, Giuseppe; Belforte, Stephano; Campana, Simone; Dimou, Maria; Flix, Jose; Forti, Alessandra; di Girolamo, A.; Karavakis, Edward; Lammel, Stephan; Litmaath, Maarten; Sciaba, Andrea; Valassi, Andrea

2017-10-01

The Worldwide LHC Computing Grid infrastructure links about 200 participating computing centres affiliated with several partner projects. It is built by integrating heterogeneous computer and storage resources in diverse data centres all over the world and provides CPU and storage capacity to the LHC experiments to perform data processing and physics analysis. In order to be used by the experiments, these distributed resources should be well described, which implies easy service discovery and detailed description of service configuration. Currently this information is scattered over multiple generic information sources like GOCDB, OIM, BDII and experiment-specific information systems. Such a model does not allow to validate topology and configuration information easily. Moreover, information in various sources is not always consistent. Finally, the evolution of computing technologies introduces new challenges. Experiments are more and more relying on opportunistic resources, which by their nature are more dynamic and should also be well described in the WLCG information system. This contribution describes the new WLCG configuration service CRIC (Computing Resource Information Catalogue) which collects information from various information providers, performs validation and provides a consistent set of UIs and APIs to the LHC VOs for service discovery and usage configuration. The main requirements for CRIC are simplicity, agility and robustness. CRIC should be able to be quickly adapted to new types of computing resources, new information sources, and allow for new data structures to be implemented easily following the evolution of the computing models and operations of the experiments.

Classical multiparty computation using quantum resources

NASA Astrophysics Data System (ADS)

Clementi, Marco; Pappa, Anna; Eckstein, Andreas; Walmsley, Ian A.; Kashefi, Elham; Barz, Stefanie

2017-12-01

In this work, we demonstrate a way to perform classical multiparty computing among parties with limited computational resources. Our method harnesses quantum resources to increase the computational power of the individual parties. We show how a set of clients restricted to linear classical processing are able to jointly compute a nonlinear multivariable function that lies beyond their individual capabilities. The clients are only allowed to perform classical xor gates and single-qubit gates on quantum states. We also examine the type of security that can be achieved in this limited setting. Finally, we provide a proof-of-concept implementation using photonic qubits that allows four clients to compute a specific example of a multiparty function, the pairwise and.

Computer Network Resources for Physical Geography Instruction.

ERIC Educational Resources Information Center

Bishop, Michael P.; And Others

1993-01-01

Asserts that the use of computer networks provides an important and effective resource for geography instruction. Describes the use of the Internet network in physical geography instruction. Provides an example of the use of Internet resources in a climatology/meteorology course. (CFR)

Self managing experiment resources

NASA Astrophysics Data System (ADS)

Stagni, F.; Ubeda, M.; Tsaregorodtsev, A.; Romanovskiy, V.; Roiser, S.; Charpentier, P.; Graciani, R.

2014-06-01

Within this paper we present an autonomic Computing resources management system, used by LHCb for assessing the status of their Grid resources. Virtual Organizations Grids include heterogeneous resources. For example, LHC experiments very often use resources not provided by WLCG, and Cloud Computing resources will soon provide a non-negligible fraction of their computing power. The lack of standards and procedures across experiments and sites generated the appearance of multiple information systems, monitoring tools, ticket portals, etc... which nowadays coexist and represent a very precious source of information for running HEP experiments Computing systems as well as sites. These two facts lead to many particular solutions for a general problem: managing the experiment resources. In this paper we present how LHCb, via the DIRAC interware, addressed such issues. With a renewed Central Information Schema hosting all resources metadata and a Status System (Resource Status System) delivering real time information, the system controls the resources topology, independently of the resource types. The Resource Status System applies data mining techniques against all possible information sources available and assesses the status changes, that are then propagated to the topology description. Obviously, giving full control to such an automated system is not risk-free. Therefore, in order to minimise the probability of misbehavior, a battery of tests has been developed in order to certify the correctness of its assessments. We will demonstrate the performance and efficiency of such a system in terms of cost reduction and reliability.

Cooperative fault-tolerant distributed computing U.S. Department of Energy Grant DE-FG02-02ER25537 Final Report

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

Sunderam, Vaidy S.

2007-01-09

The Harness project has developed novel software frameworks for the execution of high-end simulations in a fault-tolerant manner on distributed resources. The H2O subsystem comprises the kernel of the Harness framework, and controls the key functions of resource management across multiple administrative domains, especially issues of access and allocation. It is based on a “pluggable” architecture that enables the aggregated use of distributed heterogeneous resources for high performance computing. The major contributions of the Harness II project result in significantly enhancing the overall computational productivity of high-end scientific applications by enabling robust, failure-resilient computations on cooperatively pooled resource collections.

Construction and application of Red5 cluster based on OpenStack

NASA Astrophysics Data System (ADS)

Wang, Jiaqing; Song, Jianxin

2017-08-01

With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has also improved the expansibility and stability. In the traditional way, Red5 cluster resource utilization is low and the system stability is poor. This paper uses cloud computing to efficiently calculate the resource allocation ability, and builds a Red5 server cluster based on OpenStack. Multimedia applications can be published to the Red5 cloud server cluster. The system achieves the flexible construction of computing resources, but also greatly improves the stability of the cluster and service efficiency.

Using Personal Computers To Acquire Special Education Information. Revised. ERIC Digest #429.

ERIC Educational Resources Information Center

ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

This digest offers basic information about resources, available to users of personal computers, in the area of professional development in special education. Two types of resources are described: those that can be purchased on computer diskettes and those made available by linking personal computers through electronic telephone networks. Resources…

Research on the digital education resources of sharing pattern in independent colleges based on cloud computing environment

NASA Astrophysics Data System (ADS)

Xiong, Ting; He, Zhiwen

2017-06-01

Cloud computing was first proposed by Google Company in the United States, which was based on the Internet center, providing a standard and open network sharing service approach. With the rapid development of the higher education in China, the educational resources provided by colleges and universities had greatly gap in the actual needs of teaching resources. therefore, Cloud computing of using the Internet technology to provide shared methods liked the timely rain, which had become an important means of the Digital Education on sharing applications in the current higher education. Based on Cloud computing environment, the paper analyzed the existing problems about the sharing of digital educational resources in Jiangxi Province Independent Colleges. According to the sharing characteristics of mass storage, efficient operation and low input about Cloud computing, the author explored and studied the design of the sharing model about the digital educational resources of higher education in Independent College. Finally, the design of the shared model was put into the practical applications.

BelleII@home: Integrate volunteer computing resources into DIRAC in a secure way

NASA Astrophysics Data System (ADS)

Wu, Wenjing; Hara, Takanori; Miyake, Hideki; Ueda, Ikuo; Kan, Wenxiao; Urquijo, Phillip

2017-10-01

The exploitation of volunteer computing resources has become a popular practice in the HEP computing community as the huge amount of potential computing power it provides. In the recent HEP experiments, the grid middleware has been used to organize the services and the resources, however it relies heavily on the X.509 authentication, which is contradictory to the untrusted feature of volunteer computing resources, therefore one big challenge to utilize the volunteer computing resources is how to integrate them into the grid middleware in a secure way. The DIRAC interware which is commonly used as the major component of the grid computing infrastructure for several HEP experiments proposes an even bigger challenge to this paradox as its pilot is more closely coupled with operations requiring the X.509 authentication compared to the implementations of pilot in its peer grid interware. The Belle II experiment is a B-factory experiment at KEK, and it uses DIRAC for its distributed computing. In the project of BelleII@home, in order to integrate the volunteer computing resources into the Belle II distributed computing platform in a secure way, we adopted a new approach which detaches the payload running from the Belle II DIRAC pilot which is a customized pilot pulling and processing jobs from the Belle II distributed computing platform, so that the payload can run on volunteer computers without requiring any X.509 authentication. In this approach we developed a gateway service running on a trusted server which handles all the operations requiring the X.509 authentication. So far, we have developed and deployed the prototype of BelleII@home, and tested its full workflow which proves the feasibility of this approach. This approach can also be applied on HPC systems whose work nodes do not have outbound connectivity to interact with the DIRAC system in general.

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.

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.

An Overview of Cloud Computing in Distributed Systems

NASA Astrophysics Data System (ADS)

Divakarla, Usha; Kumari, Geetha

2010-11-01

Cloud computing is the emerging trend in the field of distributed computing. Cloud computing evolved from grid computing and distributed computing. Cloud plays an important role in huge organizations in maintaining huge data with limited resources. Cloud also helps in resource sharing through some specific virtual machines provided by the cloud service provider. This paper gives an overview of the cloud organization and some of the basic security issues pertaining to the cloud.

AGIS: Integration of new technologies used in ATLAS Distributed Computing

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Di Girolamo, Alessandro; Alandes Pradillo, Maria

2017-10-01

The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services. Being an intermediate middleware system between clients and external information sources (like central BDII, GOCDB, MyOSG), AGIS defines the relations between experiment specific used resources and physical distributed computing capabilities. Being in production during LHC Runl AGIS became the central information system for Distributed Computing in ATLAS and it is continuously evolving to fulfil new user requests, enable enhanced operations and follow the extension of the ATLAS Computing model. The ATLAS Computing model and data structures used by Distributed Computing applications and services are continuously evolving and trend to fit newer requirements from ADC community. In this note, we describe the evolution and the recent developments of AGIS functionalities, related to integration of new technologies recently become widely used in ATLAS Computing, like flexible computing utilization of opportunistic Cloud and HPC resources, ObjectStore services integration for Distributed Data Management (Rucio) and ATLAS workload management (PanDA) systems, unified storage protocols declaration required for PandDA Pilot site movers and others. The improvements of information model and general updates are also shown, in particular we explain how other collaborations outside ATLAS could benefit the system as a computing resources information catalogue. AGIS is evolving towards a common information system, not coupled to a specific experiment.

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

PubMed Central

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

PubMed

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

43 CFR 11.40 - What are type A procedures?

Code of Federal Regulations, 2010 CFR

2010-10-01

... 11.40 Public Lands: Interior Office of the Secretary of the Interior NATURAL RESOURCE DAMAGE... marine environments incorporates a computer model called the Natural Resource Damage Assessment Model for... environments incorporates a computer model called the Natural Resource Damage Assessment Model for Great Lakes...

43 CFR 11.40 - What are type A procedures?

Code of Federal Regulations, 2011 CFR

2011-10-01

... 11.40 Public Lands: Interior Office of the Secretary of the Interior NATURAL RESOURCE DAMAGE... marine environments incorporates a computer model called the Natural Resource Damage Assessment Model for... environments incorporates a computer model called the Natural Resource Damage Assessment Model for Great Lakes...

An emulator for minimizing computer resources for finite element analysis

NASA Technical Reports Server (NTRS)

Melosh, R.; Utku, S.; Islam, M.; Salama, M.

1984-01-01

A computer code, SCOPE, has been developed for predicting the computer resources required for a given analysis code, computer hardware, and structural problem. The cost of running the code is a small fraction (about 3 percent) of the cost of performing the actual analysis. However, its accuracy in predicting the CPU and I/O resources depends intrinsically on the accuracy of calibration data that must be developed once for the computer hardware and the finite element analysis code of interest. Testing of the SCOPE code on the AMDAHL 470 V/8 computer and the ELAS finite element analysis program indicated small I/O errors (3.2 percent), larger CPU errors (17.8 percent), and negligible total errors (1.5 percent).

Experience in Implementing Resource-Based Learning in Agrarian College of Management and Law Poltava State Agrarian Academy

ERIC Educational Resources Information Center

Kononets, Natalia

2015-01-01

The introduction of resource-based learning disciplines of computer cycles in Agrarian College. The article focused on the issue of implementation of resource-based learning courses in the agricultural cycle computer college. Tested approach to creating elearning resources through free hosting and their further use in the classroom. Noted that the…

ACToR A Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology. We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

ACToR A Aggregated Computational Toxicology Resource (S) ...

EPA Pesticide Factsheets

We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology. We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

Aviation & Space Education: A Teacher's Resource Guide.

ERIC Educational Resources Information Center

Texas State Dept. of Aviation, Austin.

This resource guide contains information on curriculum guides, resources for teachers, computer software and computer related programs, audio/visual presentations, model aircraft and demonstration aids, training seminars and career education, and an aerospace bibliography for primary grades. Each entry includes all or some of the following items:…

Campus Computing Environment: University of Kentucky.

ERIC Educational Resources Information Center

CAUSE/EFFECT, 1989

1989-01-01

A dramatic growth in computing and communications was precipitated largely by the leadership of President David Roselle at the University of Kentucky. A new operational structure of information resource management includes not only computing (academic and administrative) and communications, instructional resources, and printing/mailing services,…

Teaching Computer Literacy with Freeware and Shareware.

ERIC Educational Resources Information Center

Hobart, R. Dale; And Others

1988-01-01

Describes workshops given at Ferris State University for faculty and staff who want to acquire computer skills. Considered are a computer literacy and a software toolkit distributed to participants made from public domain/shareware resources. Stresses the benefits of shareware as an educational resource. (CW)

Challenges in Securing the Interface Between the Cloud and Pervasive Systems

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

Lagesse, Brent J

2011-01-01

Cloud computing presents an opportunity for pervasive systems to leverage computational and storage resources to accomplish tasks that would not normally be possible on such resource-constrained devices. Cloud computing can enable hardware designers to build lighter systems that last longer and are more mobile. Despite the advantages cloud computing offers to the designers of pervasive systems, there are some limitations of leveraging cloud computing that must be addressed. We take the position that cloud-based pervasive system must be secured holistically and discuss ways this might be accomplished. In this paper, we discuss a pervasive system utilizing cloud computing resources andmore » issues that must be addressed in such a system. In this system, the user's mobile device cannot always have network access to leverage resources from the cloud, so it must make intelligent decisions about what data should be stored locally and what processes should be run locally. As a result of these decisions, the user becomes vulnerable to attacks while interfacing with the pervasive system.« less

Methods and systems for providing reconfigurable and recoverable computing resources

NASA Technical Reports Server (NTRS)

Stange, Kent (Inventor); Hess, Richard (Inventor); Kelley, Gerald B (Inventor); Rogers, Randy (Inventor)

2010-01-01

A method for optimizing the use of digital computing resources to achieve reliability and availability of the computing resources is disclosed. The method comprises providing one or more processors with a recovery mechanism, the one or more processors executing one or more applications. A determination is made whether the one or more processors needs to be reconfigured. A rapid recovery is employed to reconfigure the one or more processors when needed. A computing system that provides reconfigurable and recoverable computing resources is also disclosed. The system comprises one or more processors with a recovery mechanism, with the one or more processors configured to execute a first application, and an additional processor configured to execute a second application different than the first application. The additional processor is reconfigurable with rapid recovery such that the additional processor can execute the first application when one of the one more processors fails.

Polyphony: A Workflow Orchestration Framework for Cloud Computing

NASA Technical Reports Server (NTRS)

Shams, Khawaja S.; Powell, Mark W.; Crockett, Tom M.; Norris, Jeffrey S.; Rossi, Ryan; Soderstrom, Tom

2010-01-01

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

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.

Diversity in computing technologies and strategies for dynamic resource allocation

DOE PAGES

Garzoglio, G.; Gutsche, O.

2015-12-23

Here, High Energy Physics (HEP) is a very data intensive and trivially parallelizable science discipline. HEP is probing nature at increasingly finer details requiring ever increasing computational resources to process and analyze experimental data. In this paper, we discuss how HEP provisioned resources so far using Grid technologies, how HEP is starting to include new resource providers like commercial Clouds and HPC installations, and how HEP is transparently provisioning resources at these diverse providers.

A distributed computing approach to mission operations support. [for spacecraft

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1975-01-01

Computing mission operation support includes orbit determination, attitude processing, maneuver computation, resource scheduling, etc. The large-scale third-generation distributed computer network discussed is capable of fulfilling these dynamic requirements. It is shown that distribution of resources and control leads to increased reliability, and exhibits potential for incremental growth. Through functional specialization, a distributed system may be tuned to very specific operational requirements. Fundamental to the approach is the notion of process-to-process communication, which is effected through a high-bandwidth communications network. Both resource-sharing and load-sharing may be realized in the system.

Computer Technology Resources for Literacy Projects.

ERIC Educational Resources Information Center

Florida State Council on Aging, Tallahassee.

This resource booklet was prepared to assist literacy projects and community adult education programs in determining the technology they need to serve more older persons. Section 1 contains the following reprinted articles: "The Human Touch in the Computer Age: Seniors Learn Computer Skills from Schoolkids" (Suzanne Kashuba);…

The Computer Explosion: Implications for Educational Equity. Resource Notebook.

ERIC Educational Resources Information Center

Denbo, Sheryl, Comp.

This notebook was prepared to provide resources for educators interested in using computers to increase opportunities for all students. The notebook contains specially prepared materials and selected newspaper and journal articles. The first section reviews the issues related to computer equity (equal access, tracking through different…

Development of Computer-Based Resources for Textile Education.

ERIC Educational Resources Information Center

Hopkins, Teresa; Thomas, Andrew; Bailey, Mike

1998-01-01

Describes the production of computer-based resources for students of textiles and engineering in the United Kingdom. Highlights include funding by the Teaching and Learning Technology Programme (TLTP), courseware author/subject expert interaction, usage test and evaluation, authoring software, graphics, computer-aided design simulation, self-test…

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

Workflow Management Systems for Molecular Dynamics on Leadership Computers

NASA Astrophysics Data System (ADS)

Wells, Jack; Panitkin, Sergey; Oleynik, Danila; Jha, Shantenu

Molecular Dynamics (MD) simulations play an important role in a range of disciplines from Material Science to Biophysical systems and account for a large fraction of cycles consumed on computing resources. Increasingly science problems require the successful execution of ''many'' MD simulations as opposed to a single MD simulation. There is a need to provide scalable and flexible approaches to the execution of the workload. We present preliminary results on the Titan computer at the Oak Ridge Leadership Computing Facility that demonstrate a general capability to manage workload execution agnostic of a specific MD simulation kernel or execution pattern, and in a manner that integrates disparate grid-based and supercomputing resources. Our results build upon our extensive experience of distributed workload management in the high-energy physics ATLAS project using PanDA (Production and Distributed Analysis System), coupled with recent conceptual advances in our understanding of workload management on heterogeneous resources. We will discuss how we will generalize these initial capabilities towards a more production level service on DOE leadership resources. This research is sponsored by US DOE/ASCR and used resources of the OLCF computing facility.

A new taxonomy for distributed computer systems based upon operating system structure

NASA Technical Reports Server (NTRS)

Foudriat, E. C.

1985-01-01

Characteristics of the resource structure found in the operating system are considered as a mechanism for classifying distributed computer systems. Since the operating system resources, themselves, are too diversified to provide a consistent classification, the structure upon which resources are built and shared are examined. The location and control character of this indivisibility provides the taxonomy for separating uniprocessors, computer networks, network computers (fully distributed processing systems or decentralized computers) and algorithm and/or data control multiprocessors. The taxonomy is important because it divides machines into a classification that is relevant or important to the client and not the hardware architect. It also defines the character of the kernel O/S structure needed for future computer systems. What constitutes an operating system for a fully distributed processor is discussed in detail.

Discussing sexual and relationship health with young people in a children's hospital: evaluation of a computer-based resource.

PubMed

Bray, Lucy; Sanders, Caroline; McKenna, Jacqueline

2013-12-01

To investigate health professionals' evaluation of a computer-based resource designed to improve discussions about sexual and relationship health with young people. Evidence suggests that some health professionals can experience discomfort discussing sexual health and relationship issues with young people. Professionals within hospital settings should have the knowledge, competencies and skills to be able to ask young people sexual health questions and provide accurate sexual health education. Despite some educational material being available for community and adult services, there are no resources available, which are directly relevant to holding opportunistic discussions with young people within an acute children's hospital. A descriptive survey design. One hundred and fourteen health professionals from a children's hospital in the UK were involved in evaluating a computer-based resource. All completed an online questionnaire survey comprising of closed and open questions. The health professionals reported that the computer-based resource had a positive influence on their knowledge and clinical practice. The videos as well as the concise nature of the resource were evaluated highly. Learning was facilitated by professionals being able to control their learning through rerunning and accessing the resource on numerous occasions. An engaging, accessible computer-based resource has the capability to positively impact on health professionals' knowledge of, and skills in, starting and holding sexual health conversations with young people accessing a children's hospital. Health professionals working with children and young people value accessible, relevant and short computer-based training. This can facilitate knowledge and skill acquisition despite variation in working patterns. Improving the knowledge and skills of professionals working with young people to facilitate appropriate yet opportunistic sexual health discussions is important within the public health agenda. © 2013 John Wiley & Sons Ltd.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Learning with Computers. AECA Resource Book Series, Volume 3, Number 2.

ERIC Educational Resources Information Center

Elliott, Alison

1996-01-01

Research has supported the idea that the use of computers in the education of young children promotes social interaction and academic achievement. This resource booklet provides an introduction to computers in early childhood settings to enrich learning opportunities and provides guidance to teachers to find developmentally appropriate software…

On-demand provisioning of HEP compute resources on cloud sites and shared HPC centers

NASA Astrophysics Data System (ADS)

Erli, G.; Fischer, F.; Fleig, G.; Giffels, M.; Hauth, T.; Quast, G.; Schnepf, M.; Heese, J.; Leppert, K.; Arnaez de Pedro, J.; Sträter, R.

2017-10-01

This contribution reports on solutions, experiences and recent developments with the dynamic, on-demand provisioning of remote computing resources for analysis and simulation workflows. Local resources of a physics institute are extended by private and commercial cloud sites, ranging from the inclusion of desktop clusters over institute clusters to HPC centers. Rather than relying on dedicated HEP computing centers, it is nowadays more reasonable and flexible to utilize remote computing capacity via virtualization techniques or container concepts. We report on recent experience from incorporating a remote HPC center (NEMO Cluster, Freiburg University) and resources dynamically requested from the commercial provider 1&1 Internet SE into our intitute’s computing infrastructure. The Freiburg HPC resources are requested via the standard batch system, allowing HPC and HEP applications to be executed simultaneously, such that regular batch jobs run side by side to virtual machines managed via OpenStack [1]. For the inclusion of the 1&1 commercial resources, a Python API and SDK as well as the possibility to upload images were available. Large scale tests prove the capability to serve the scientific use case in the European 1&1 datacenters. The described environment at the Institute of Experimental Nuclear Physics (IEKP) at KIT serves the needs of researchers participating in the CMS and Belle II experiments. In total, resources exceeding half a million CPU hours have been provided by remote sites.

Crowd-Funding: A New Resource Cooperation Mode for Mobile Cloud Computing.

PubMed

Zhang, Nan; Yang, Xiaolong; Zhang, Min; Sun, Yan

2016-01-01

Mobile cloud computing, which integrates the cloud computing techniques into the mobile environment, is regarded as one of the enabler technologies for 5G mobile wireless networks. There are many sporadic spare resources distributed within various devices in the networks, which can be used to support mobile cloud applications. However, these devices, with only a few spare resources, cannot support some resource-intensive mobile applications alone. If some of them cooperate with each other and share their resources, then they can support many applications. In this paper, we propose a resource cooperative provision mode referred to as "Crowd-funding", which is designed to aggregate the distributed devices together as the resource provider of mobile applications. Moreover, to facilitate high-efficiency resource management via dynamic resource allocation, different resource providers should be selected to form a stable resource coalition for different requirements. Thus, considering different requirements, we propose two different resource aggregation models for coalition formation. Finally, we may allocate the revenues based on their attributions according to the concept of the "Shapley value" to enable a more impartial revenue share among the cooperators. It is shown that a dynamic and flexible resource-management method can be developed based on the proposed Crowd-funding model, relying on the spare resources in the network.

Crowd-Funding: A New Resource Cooperation Mode for Mobile Cloud Computing

PubMed Central

Zhang, Min; Sun, Yan

2016-01-01

Mobile cloud computing, which integrates the cloud computing techniques into the mobile environment, is regarded as one of the enabler technologies for 5G mobile wireless networks. There are many sporadic spare resources distributed within various devices in the networks, which can be used to support mobile cloud applications. However, these devices, with only a few spare resources, cannot support some resource-intensive mobile applications alone. If some of them cooperate with each other and share their resources, then they can support many applications. In this paper, we propose a resource cooperative provision mode referred to as "Crowd-funding", which is designed to aggregate the distributed devices together as the resource provider of mobile applications. Moreover, to facilitate high-efficiency resource management via dynamic resource allocation, different resource providers should be selected to form a stable resource coalition for different requirements. Thus, considering different requirements, we propose two different resource aggregation models for coalition formation. Finally, we may allocate the revenues based on their attributions according to the concept of the "Shapley value" to enable a more impartial revenue share among the cooperators. It is shown that a dynamic and flexible resource-management method can be developed based on the proposed Crowd-funding model, relying on the spare resources in the network. PMID:28030553

Research on Key Technologies of Cloud Computing

NASA Astrophysics Data System (ADS)

Zhang, Shufen; Yan, Hongcan; Chen, Xuebin

With the development of multi-core processors, virtualization, distributed storage, broadband Internet and automatic management, a new type of computing mode named cloud computing is produced. It distributes computation task on the resource pool which consists of massive computers, so the application systems can obtain the computing power, the storage space and software service according to its demand. It can concentrate all the computing resources and manage them automatically by the software without intervene. This makes application offers not to annoy for tedious details and more absorbed in his business. It will be advantageous to innovation and reduce cost. It's the ultimate goal of cloud computing to provide calculation, services and applications as a public facility for the public, So that people can use the computer resources just like using water, electricity, gas and telephone. Currently, the understanding of cloud computing is developing and changing constantly, cloud computing still has no unanimous definition. This paper describes three main service forms of cloud computing: SAAS, PAAS, IAAS, compared the definition of cloud computing which is given by Google, Amazon, IBM and other companies, summarized the basic characteristics of cloud computing, and emphasized on the key technologies such as data storage, data management, virtualization and programming model.

Hard-real-time resource management for autonomous spacecraft

NASA Technical Reports Server (NTRS)

Gat, E.

2000-01-01

This paper describes tickets, a computational mechanism for hard-real-time autonomous resource management. Autonomous spacecraftcontrol can be considered abstractly as a computational process whose outputs are spacecraft commands.

Synchronization of Finite State Shared Resources

DTIC Science & Technology

1976-03-01

IMHI uiw mmm " AFOSR -TR- 70- 0^8 3 QC o SYNCHRONIZATION OF FINITE STATE SHARED RESOURCES Edward A Sei neide.- DEPARTMENT of COMPUTER...34" ■ ■ ^ I I. i. . : ,1 . i-i SYNCHRONIZATION OF FINITE STATE SHARED RESOURCES Edward A Schneider Department of Computer...SIGNIFICANT NUMBER OF PAGES WHICH DO NOT REPRODUCE LEGIBLY. ABSTRACT The problem of synchronizing a set of operations defined on a shared resource

Radar Control Optimal Resource Allocation

DTIC Science & Technology

2015-07-13

other tunable parameters of radars [17, 18]. Such radar resource scheduling usually demands massive computation. Even myopic 14 Distribution A: Approved...reduced validity of the optimal choice of radar resource. In the non- myopic context, the computational problem becomes exponentially more difficult...computed as t? = ασ2 q + σ r √ α q (σ + r + α q) α q2 r − 1ασ q2 + q r2 . (19) We are only interested in t? > 1 and solving the inequality we obtain the

Performance Evaluation of Resource Management in Cloud Computing Environments.

PubMed

Batista, Bruno Guazzelli; Estrella, Julio Cezar; Ferreira, Carlos Henrique Gomes; Filho, Dionisio Machado Leite; Nakamura, Luis Hideo Vasconcelos; Reiff-Marganiec, Stephan; Santana, Marcos José; Santana, Regina Helena Carlucci

2015-01-01

Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price.

Performance Evaluation of Resource Management in Cloud Computing Environments

PubMed Central

Batista, Bruno Guazzelli; Estrella, Julio Cezar; Ferreira, Carlos Henrique Gomes; Filho, Dionisio Machado Leite; Nakamura, Luis Hideo Vasconcelos; Reiff-Marganiec, Stephan; Santana, Marcos José; Santana, Regina Helena Carlucci

2015-01-01

Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price. PMID:26555730

Eurogrid: a new glideinWMS based portal for CDF data analysis

NASA Astrophysics Data System (ADS)

Amerio, S.; Benjamin, D.; Dost, J.; Compostella, G.; Lucchesi, D.; Sfiligoi, I.

2012-12-01

The CDF experiment at Fermilab ended its Run-II phase on September 2011 after 11 years of operations and 10 fb-1 of collected data. CDF computing model is based on a Central Analysis Farm (CAF) consisting of local computing and storage resources, supported by OSG and LCG resources accessed through dedicated portals. At the beginning of 2011 a new portal, Eurogrid, has been developed to effectively exploit computing and disk resources in Europe: a dedicated farm and storage area at the TIER-1 CNAF computing center in Italy, and additional LCG computing resources at different TIER-2 sites in Italy, Spain, Germany and France, are accessed through a common interface. The goal of this project is to develop a portal easy to integrate in the existing CDF computing model, completely transparent to the user and requiring a minimum amount of maintenance support by the CDF collaboration. In this paper we will review the implementation of this new portal, and its performance in the first months of usage. Eurogrid is based on the glideinWMS software, a glidein based Workload Management System (WMS) that works on top of Condor. As CDF CAF is based on Condor, the choice of the glideinWMS software was natural and the implementation seamless. Thanks to the pilot jobs, user-specific requirements and site resources are matched in a very efficient way, completely transparent to the users. Official since June 2011, Eurogrid effectively complements and supports CDF computing resources offering an optimal solution for the future in terms of required manpower for administration, support and development.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Dynamic partitioning as a way to exploit new computing paradigms: the cloud use case.

NASA Astrophysics Data System (ADS)

Ciaschini, Vincenzo; Dal Pra, Stefano; dell'Agnello, Luca

2015-12-01

The WLCG community and many groups in the HEP community have based their computing strategy on the Grid paradigm, which proved successful and still ensures its goals. However, Grid technology has not spread much over other communities; in the commercial world, the cloud paradigm is the emerging way to provide computing services. WLCG experiments aim to achieve integration of their existing current computing model with cloud deployments and take advantage of the so-called opportunistic resources (including HPC facilities) which are usually not Grid compliant. One missing feature in the most common cloud frameworks, is the concept of job scheduler, which plays a key role in a traditional computing centre, by enabling a fairshare based access at the resources to the experiments in a scenario where demand greatly outstrips availability. At CNAF we are investigating the possibility to access the Tier-1 computing resources as an OpenStack based cloud service. The system, exploiting the dynamic partitioning mechanism already being used to enable Multicore computing, allowed us to avoid a static splitting of the computing resources in the Tier-1 farm, while permitting a share friendly approach. The hosts in a dynamically partitioned farm may be moved to or from the partition, according to suitable policies for request and release of computing resources. Nodes being requested in the partition switch their role and become available to play a different one. In the cloud use case hosts may switch from acting as Worker Node in the Batch system farm to cloud compute node member, made available to tenants. In this paper we describe the dynamic partitioning concept, its implementation and integration with our current batch system, LSF.

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

Computing Bounds on Resource Levels for Flexible Plans

NASA Technical Reports Server (NTRS)

Muscvettola, Nicola; Rijsman, David

2009-01-01

A new algorithm efficiently computes the tightest exact bound on the levels of resources induced by a flexible activity plan (see figure). Tightness of bounds is extremely important for computations involved in planning because tight bounds can save potentially exponential amounts of search (through early backtracking and detection of solutions), relative to looser bounds. The bound computed by the new algorithm, denoted the resource-level envelope, constitutes the measure of maximum and minimum consumption of resources at any time for all fixed-time schedules in the flexible plan. At each time, the envelope guarantees that there are two fixed-time instantiations one that produces the minimum level and one that produces the maximum level. Therefore, the resource-level envelope is the tightest possible resource-level bound for a flexible plan because any tighter bound would exclude the contribution of at least one fixed-time schedule. If the resource- level envelope can be computed efficiently, one could substitute looser bounds that are currently used in the inner cores of constraint-posting scheduling algorithms, with the potential for great improvements in performance. What is needed to reduce the cost of computation is an algorithm, the measure of complexity of which is no greater than a low-degree polynomial in N (where N is the number of activities). The new algorithm satisfies this need. In this algorithm, the computation of resource-level envelopes is based on a novel combination of (1) the theory of shortest paths in the temporal-constraint network for the flexible plan and (2) the theory of maximum flows for a flow network derived from the temporal and resource constraints. The measure of asymptotic complexity of the algorithm is O(N O(maxflow(N)), where O(x) denotes an amount of computing time or a number of arithmetic operations proportional to a number of the order of x and O(maxflow(N)) is the measure of complexity (and thus of cost) of a maximumflow algorithm applied to an auxiliary flow network of 2N nodes. The algorithm is believed to be efficient in practice; experimental analysis shows the practical cost of maxflow to be as low as O(N1.5). The algorithm could be enhanced following at least two approaches. In the first approach, incremental subalgorithms for the computation of the envelope could be developed. By use of temporal scanning of the events in the temporal network, it may be possible to significantly reduce the size of the networks on which it is necessary to run the maximum-flow subalgorithm, thereby significantly reducing the time required for envelope calculation. In the second approach, the practical effectiveness of resource envelopes in the inner loops of search algorithms could be tested for multi-capacity resource scheduling. This testing would include inner-loop backtracking and termination tests and variable and value-ordering heuristics that exploit the properties of resource envelopes more directly.

Cloudbus Toolkit for Market-Oriented Cloud Computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Pandey, Suraj; Vecchiola, Christian

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.

Focus issue: series on computational and systems biology.

PubMed

Gough, Nancy R

2011-09-06

The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.

Applications of computer-aided text analysis in natural resources.

Treesearch

David N. Bengston

2000-01-01

Ten contributed papers describe the use of a variety of approaches to computer-aided text analysis and their application to a wide range of research questions related to natural resources and the environment. Taken together, these papers paint a picture of a growing and vital area of research on the human dimensions of natural resource management.

SCANIT: centralized digitizing of forest resource maps or photographs

Treesearch

Elliot L. Amidon; E. Joyce Dye

1981-01-01

Spatial data on wildland resource maps and aerial photographs can be analyzed by computer after digitizing. SCANIT is a computerized system for encoding such data in digital form. The system, consisting of a collection of computer programs and subroutines, provides a powerful and versatile tool for a variety of resource analyses. SCANIT also may be converted easily to...

The DoD's High Performance Computing Modernization Program - Ensuing the National Earth Systems Prediction Capability Becomes Operational

NASA Astrophysics Data System (ADS)

Burnett, W.

2016-12-01

The Department of Defense's (DoD) High Performance Computing Modernization Program (HPCMP) provides high performance computing to address the most significant challenges in computational resources, software application support and nationwide research and engineering networks. Today, the HPCMP has a critical role in ensuring the National Earth System Prediction Capability (N-ESPC) achieves initial operational status in 2019. A 2015 study commissioned by the HPCMP found that N-ESPC computational requirements will exceed interconnect bandwidth capacity due to the additional load from data assimilation and passing connecting data between ensemble codes. Memory bandwidth and I/O bandwidth will continue to be significant bottlenecks for the Navy's Hybrid Coordinate Ocean Model (HYCOM) scalability - by far the major driver of computing resource requirements in the N-ESPC. The study also found that few of the N-ESPC model developers have detailed plans to ensure their respective codes scale through 2024. Three HPCMP initiatives are designed to directly address and support these issues: Productivity Enhancement, Technology, Transfer and Training (PETTT), the HPCMP Applications Software Initiative (HASI), and Frontier Projects. PETTT supports code conversion by providing assistance, expertise and training in scalable and high-end computing architectures. HASI addresses the continuing need for modern application software that executes effectively and efficiently on next-generation high-performance computers. Frontier Projects enable research and development that could not be achieved using typical HPCMP resources by providing multi-disciplinary teams access to exceptional amounts of high performance computing resources. Finally, the Navy's DoD Supercomputing Resource Center (DSRC) currently operates a 6 Petabyte system, of which Naval Oceanography receives 15% of operational computational system use, or approximately 1 Petabyte of the processing capability. The DSRC will provide the DoD with future computing assets to initially operate the N-ESPC in 2019. This talk will further describe how DoD's HPCMP will ensure N-ESPC becomes operational, efficiently and effectively, using next-generation high performance computing.

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

PubMed Central

2011-01-01

Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105

Justification of Filter Selection for Robot Balancing in Conditions of Limited Computational Resources

NASA Astrophysics Data System (ADS)

Momot, M. V.; Politsinskaia, E. V.; Sushko, A. V.; Semerenko, I. A.

2016-08-01

The paper considers the problem of mathematical filter selection, used for balancing of wheeled robot in conditions of limited computational resources. The solution based on complementary filter is proposed.

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

Shared-resource computing for small research labs.

PubMed

Ackerman, M J

1982-04-01

A real time laboratory computer network is described. This network is composed of four real-time laboratory minicomputers located in each of four division laboratories and a larger minicomputer in a centrally located computer room. Off the shelf hardware and software were used with no customization. The network is configured for resource sharing using DECnet communications software and the RSX-11-M multi-user real-time operating system. The cost effectiveness of the shared resource network and multiple real-time processing using priority scheduling is discussed. Examples of utilization within a medical research department are given.

Examining Effects of Virtual Machine Settings on Voice over Internet Protocol in a Private Cloud Environment

ERIC Educational Resources Information Center

Liao, Yuan

2011-01-01

The virtualization of computing resources, as represented by the sustained growth of cloud computing, continues to thrive. Information Technology departments are building their private clouds due to the perception of significant cost savings by managing all physical computing resources from a single point and assigning them to applications or…

Dynamic provisioning of local and remote compute resources with OpenStack

NASA Astrophysics Data System (ADS)

Giffels, M.; Hauth, T.; Polgart, F.; Quast, G.

2015-12-01

Modern high-energy physics experiments rely on the extensive usage of computing resources, both for the reconstruction of measured events as well as for Monte-Carlo simulation. The Institut fur Experimentelle Kernphysik (EKP) at KIT is participating in both the CMS and Belle experiments with computing and storage resources. In the upcoming years, these requirements are expected to increase due to growing amount of recorded data and the rise in complexity of the simulated events. It is therefore essential to increase the available computing capabilities by tapping into all resource pools. At the EKP institute, powerful desktop machines are available to users. Due to the multi-core nature of modern CPUs, vast amounts of CPU time are not utilized by common desktop usage patterns. Other important providers of compute capabilities are classical HPC data centers at universities or national research centers. Due to the shared nature of these installations, the standardized software stack required by HEP applications cannot be installed. A viable way to overcome this constraint and offer a standardized software environment in a transparent manner is the usage of virtualization technologies. The OpenStack project has become a widely adopted solution to virtualize hardware and offer additional services like storage and virtual machine management. This contribution will report on the incorporation of the institute's desktop machines into a private OpenStack Cloud. The additional compute resources provisioned via the virtual machines have been used for Monte-Carlo simulation and data analysis. Furthermore, a concept to integrate shared, remote HPC centers into regular HEP job workflows will be presented. In this approach, local and remote resources are merged to form a uniform, virtual compute cluster with a single point-of-entry for the user. Evaluations of the performance and stability of this setup and operational experiences will be discussed.

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.

WE-B-BRD-01: Innovation in Radiation Therapy Planning II: Cloud Computing in RT

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

Moore, K; Kagadis, G; Xing, L

As defined by the National Institute of Standards and Technology, cloud computing is “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” Despite the omnipresent role of computers in radiotherapy, cloud computing has yet to achieve widespread adoption in clinical or research applications, though the transition to such “on-demand” access is underway. As this transition proceeds, new opportunities for aggregate studies and efficient use of computational resources are set againstmore » new challenges in patient privacy protection, data integrity, and management of clinical informatics systems. In this Session, current and future applications of cloud computing and distributed computational resources will be discussed in the context of medical imaging, radiotherapy research, and clinical radiation oncology applications. Learning Objectives: Understand basic concepts of cloud computing. Understand how cloud computing could be used for medical imaging applications. Understand how cloud computing could be employed for radiotherapy research.4. Understand how clinical radiotherapy software applications would function in the cloud.« less

Mixing HTC and HPC Workloads with HTCondor and Slurm

NASA Astrophysics Data System (ADS)

Hollowell, C.; Barnett, J.; Caramarcu, C.; Strecker-Kellogg, W.; Wong, A.; Zaytsev, A.

2017-10-01

Traditionally, the RHIC/ATLAS Computing Facility (RACF) at Brookhaven National Laboratory (BNL) has only maintained High Throughput Computing (HTC) resources for our HEP/NP user community. We’ve been using HTCondor as our batch system for many years, as this software is particularly well suited for managing HTC processor farm resources. Recently, the RACF has also begun to design/administrate some High Performance Computing (HPC) systems for a multidisciplinary user community at BNL. In this paper, we’ll discuss our experiences using HTCondor and Slurm in an HPC context, and our facility’s attempts to allow our HTC and HPC processing farms/clusters to make opportunistic use of each other’s computing resources.

ACToR A Aggregated Computational Toxicology Resource

EPA Science Inventory

We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

ACToR A Aggregated Computational Toxicology Resource (S)

EPA Science Inventory

We are developing the ACToR system (Aggregated Computational Toxicology Resource) to serve as a repository for a variety of types of chemical, biological and toxicological data that can be used for predictive modeling of chemical toxicology.

Computational resources for ribosome profiling: from database to Web server and software.

PubMed

Wang, Hongwei; Wang, Yan; Xie, Zhi

2017-08-14

Ribosome profiling is emerging as a powerful technique that enables genome-wide investigation of in vivo translation at sub-codon resolution. The increasing application of ribosome profiling in recent years has achieved remarkable progress toward understanding the composition, regulation and mechanism of translation. This benefits from not only the awesome power of ribosome profiling but also an extensive range of computational resources available for ribosome profiling. At present, however, a comprehensive review on these resources is still lacking. Here, we survey the recent computational advances guided by ribosome profiling, with a focus on databases, Web servers and software tools for storing, visualizing and analyzing ribosome profiling data. This review is intended to provide experimental and computational biologists with a reference to make appropriate choices among existing resources for the question at hand. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

INDIVIDUALIZING UNIVERSITY INSTRUCTION, EXPLORING COMPUTER POTENTIAL TO AID COLLEGE TEACHERS BY DIRECTING THE LEARNING PROCESS. INTER-UNIVERSITY PROJECT ONE, PUBLICATIONS SERIES.

ERIC Educational Resources Information Center

FALL, CHARLES R.

THIS DOCUMENT CONCLUDES THAT INSTRUCTION BY COMPUTER-BASED RESOURCE UNITS CAN FACILITATE LEARNING AND PROVIDE THE INSTRUCTOR WITH VALUABLE ASSISTANCE. BY PRE-PLANNING THE TEACHING-LEARNING SITUATION, RESOURCE UNITS CAN FREE THE INSTRUCTOR FOR DECISION-MAKING TASKS. RESOURCE UNITS CAN ALSO PROVIDE APPROPRIATE LEARNING GOALS AND STUDY GUIDES TO EACH…

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

Habte, A.; Sengupta, M.; Wilcox, S.

This report was part of a multiyear collaboration with the University of Wisconsin and the National Oceanic and Atmospheric Administration (NOAA) to produce high-quality, satellite-based, solar resource datasets for the United States. High-quality, solar resource assessment accelerates technology deployment by making a positive impact on decision making and reducing uncertainty in investment decisions. Satellite-based solar resource datasets are used as a primary source in solar resource assessment. This is mainly because satellites provide larger areal coverage and longer periods of record than ground-based measurements. With the advent of newer satellites with increased information content and faster computers that can processmore » increasingly higher data volumes, methods that were considered too computationally intensive are now feasible. One class of sophisticated methods for retrieving solar resource information from satellites is a two-step, physics-based method that computes cloud properties and uses the information in a radiative transfer model to compute solar radiation. This method has the advantage of adding additional information as satellites with newer channels come on board. This report evaluates the two-step method developed at NOAA and adapted for solar resource assessment for renewable energy with the goal of identifying areas that can be improved in the future.« less

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

PubMed

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

The Gain of Resource Delegation in Distributed Computing Environments

NASA Astrophysics Data System (ADS)

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator's viewpoint of load-dependent resource reconfiguration. In case of a site's over-utilization, the scheduling system is able to lease resources from other sites to keep up service quality for its local user community. Contrary, the granting of idle resources can increase utilization in times of low local workload and thus ensure higher efficiency. The evaluation considers real workload data and is done with respect to common service quality indicators. For two simple resource exchange policies and three basic setups we show the possible gain of this approach and analyze the dynamics in workload-adaptive reconfiguration behavior.

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.

Dynamically allocating sets of fine-grained processors to running computations

NASA Technical Reports Server (NTRS)

Middleton, David

1988-01-01

Researchers explore an approach to using general purpose parallel computers which involves mapping hardware resources onto computations instead of mapping computations onto hardware. Problems such as processor allocation, task scheduling and load balancing, which have traditionally proven to be challenging, change significantly under this approach and may become amenable to new attacks. Researchers describe the implementation of this approach used by the FFP Machine whose computation and communication resources are repeatedly partitioned into disjoint groups that match the needs of available tasks from moment to moment. Several consequences of this system are examined.

Process for selecting NEAMS applications for access to Idaho National Laboratory high performance computing resources

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

Michael Pernice

2010-09-01

INL has agreed to provide participants in the Nuclear Energy Advanced Mod- eling and Simulation (NEAMS) program with access to its high performance computing (HPC) resources under sponsorship of the Enabling Computational Technologies (ECT) program element. This report documents the process used to select applications and the software stack in place at INL.

Scaling predictive modeling in drug development with cloud computing.

PubMed

Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

2015-01-26

Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

Self-guaranteed measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Hayashi, Masahito; Hajdušek, Michal

2018-05-01

In order to guarantee the output of a quantum computation, we usually assume that the component devices are trusted. However, when the total computation process is large, it is not easy to guarantee the whole system when we have scaling effects, unexpected noise, or unaccounted for correlations between several subsystems. If we do not trust the measurement basis or the prepared entangled state, we do need to be worried about such uncertainties. To this end, we propose a self-guaranteed protocol for verification of quantum computation under the scheme of measurement-based quantum computation where no prior-trusted devices (measurement basis or entangled state) are needed. The approach we present enables the implementation of verifiable quantum computation using the measurement-based model in the context of a particular instance of delegated quantum computation where the server prepares the initial computational resource and sends it to the client, who drives the computation by single-qubit measurements. Applying self-testing procedures, we are able to verify the initial resource as well as the operation of the quantum devices and hence the computation itself. The overhead of our protocol scales with the size of the initial resource state to the power of 4 times the natural logarithm of the initial state's size.

Functional requirements document for the Earth Observing System Data and Information System (EOSDIS) Scientific Computing Facilities (SCF) of the NASA/MSFC Earth Science and Applications Division, 1992

NASA Technical Reports Server (NTRS)

Botts, Michael E.; Phillips, Ron J.; Parker, John V.; Wright, Patrick D.

1992-01-01

Five scientists at MSFC/ESAD have EOS SCF investigator status. Each SCF has unique tasks which require the establishment of a computing facility dedicated to accomplishing those tasks. A SCF Working Group was established at ESAD with the charter of defining the computing requirements of the individual SCFs and recommending options for meeting these requirements. The primary goal of the working group was to determine which computing needs can be satisfied using either shared resources or separate but compatible resources, and which needs require unique individual resources. The requirements investigated included CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A review of computer industry directions and a market survey of computing hardware provided information regarding important industry standards and candidate computing platforms. It was determined that the total SCF computing requirements might be most effectively met using a hierarchy consisting of shared and individual resources. This hierarchy is composed of five major system types: (1) a supercomputer class vector processor; (2) a high-end scalar multiprocessor workstation; (3) a file server; (4) a few medium- to high-end visualization workstations; and (5) several low- to medium-range personal graphics workstations. Specific recommendations for meeting the needs of each of these types are presented.

Climate@Home: Crowdsourcing Climate Change Research

NASA Astrophysics Data System (ADS)

Xu, C.; Yang, C.; Li, J.; Sun, M.; Bambacus, M.

2011-12-01

Climate change deeply impacts human wellbeing. Significant amounts of resources have been invested in building super-computers that are capable of running advanced climate models, which help scientists understand climate change mechanisms, and predict its trend. Although climate change influences all human beings, the general public is largely excluded from the research. On the other hand, scientists are eagerly seeking communication mediums for effectively enlightening the public on climate change and its consequences. The Climate@Home project is devoted to connect the two ends with an innovative solution: crowdsourcing climate computing to the general public by harvesting volunteered computing resources from the participants. A distributed web-based computing platform will be built to support climate computing, and the general public can 'plug-in' their personal computers to participate in the research. People contribute the spare computing power of their computers to run a computer model, which is used by scientists to predict climate change. Traditionally, only super-computers could handle such a large computing processing load. By orchestrating massive amounts of personal computers to perform atomized data processing tasks, investments on new super-computers, energy consumed by super-computers, and carbon release from super-computers are reduced. Meanwhile, the platform forms a social network of climate researchers and the general public, which may be leveraged to raise climate awareness among the participants. A portal is to be built as the gateway to the climate@home project. Three types of roles and the corresponding functionalities are designed and supported. The end users include the citizen participants, climate scientists, and project managers. Citizen participants connect their computing resources to the platform by downloading and installing a computing engine on their personal computers. Computer climate models are defined at the server side. Climate scientists configure computer model parameters through the portal user interface. After model configuration, scientists then launch the computing task. Next, data is atomized and distributed to computing engines that are running on citizen participants' computers. Scientists will receive notifications on the completion of computing tasks, and examine modeling results via visualization modules of the portal. Computing tasks, computing resources, and participants are managed by project managers via portal tools. A portal prototype has been built for proof of concept. Three forums have been setup for different groups of users to share information on science aspect, technology aspect, and educational outreach aspect. A facebook account has been setup to distribute messages via the most popular social networking platform. New treads are synchronized from the forums to facebook. A mapping tool displays geographic locations of the participants and the status of tasks on each client node. A group of users have been invited to test functions such as forums, blogs, and computing resource monitoring.

Impact of remote sensing upon the planning, management, and development of water resources

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L.; Fowler, T. R.; Frech, S. L.

1975-01-01

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

A System for Monitoring and Management of Computational Grids

NASA Technical Reports Server (NTRS)

Smith, Warren; Biegel, Bryan (Technical Monitor)

2002-01-01

As organizations begin to deploy large computational grids, it has become apparent that systems for observation and control of the resources, services, and applications that make up such grids are needed. Administrators must observe the operation of resources and services to ensure that they are operating correctly and they must control the resources and services to ensure that their operation meets the needs of users. Users are also interested in the operation of resources and services so that they can choose the most appropriate ones to use. In this paper we describe a prototype system to monitor and manage computational grids and describe the general software framework for control and observation in distributed environments that it is based on.

Communication, Control, and Computer Access for Disabled and Elderly Individuals. ResourceBook 2: Switches and Environmental Controls. Rehab/Education Technology ResourceBook Series.

ERIC Educational Resources Information Center

Brandenburg, Sara A., Ed.; Vanderheiden, Gregg C., Ed.

One of a series of three resource guides concerned with communication, control, and computer access for disabled and elderly individuals, the directory focuses on switches and environmental controls. The book's three chapters each cover products with the same primary function. Cross reference indexes allow access to listings of products by…

Communication, Control, and Computer Access for Disabled and Elderly Individuals. ResourceBook 1: Communication Aids. Rehab/Education Technology ResourceBook Series.

ERIC Educational Resources Information Center

Brandenburg, Sara A., Ed.; Vanderheiden, Gregg C., Ed.

One of a series of three resource guides concerned with communication, control, and computer access for disabled and elderly individuals, the directory focuses on communication aids. The book's six chapters each cover products with the same primary function. Cross reference indexes allow access to listings of products by function, input/output…

Surfer: An Extensible Pull-Based Framework for Resource Selection and Ranking

NASA Technical Reports Server (NTRS)

Zolano, Paul Z.

2004-01-01

Grid computing aims to connect large numbers of geographically and organizationally distributed resources to increase computational power; resource utilization, and resource accessibility. In order to effectively utilize grids, users need to be connected to the best available resources at any given time. As grids are in constant flux, users cannot be expected to keep up with the configuration and status of the grid, thus they must be provided with automatic resource brokering for selecting and ranking resources meeting constraints and preferences they specify. This paper presents a new OGSI-compliant resource selection and ranking framework called Surfer that has been implemented as part of NASA's Information Power Grid (IPG) project. Surfer is highly extensible and may be integrated into any grid environment by adding information providers knowledgeable about that environment.

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

Hybrid quantum-classical hierarchy for mitigation of decoherence and determination of excited states

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

McClean, Jarrod R.; Kimchi-Schwartz, Mollie E.; Carter, Jonathan

Using quantum devices supported by classical computational resources is a promising approach to quantum-enabled computation. One powerful example of such a hybrid quantum-classical approach optimized for classically intractable eigenvalue problems is the variational quantum eigensolver, built to utilize quantum resources for the solution of eigenvalue problems and optimizations with minimal coherence time requirements by leveraging classical computational resources. These algorithms have been placed as leaders among the candidates for the first to achieve supremacy over classical computation. Here, we provide evidence for the conjecture that variational approaches can automatically suppress even nonsystematic decoherence errors by introducing an exactly solvable channelmore » model of variational state preparation. Moreover, we develop a more general hierarchy of measurement and classical computation that allows one to obtain increasingly accurate solutions by leveraging additional measurements and classical resources. In conclusion, we demonstrate numerically on a sample electronic system that this method both allows for the accurate determination of excited electronic states as well as reduces the impact of decoherence, without using any additional quantum coherence time or formal error-correction codes.« less

Measuring the impact of computer resource quality on the software development process and product

NASA Technical Reports Server (NTRS)

Mcgarry, Frank; Valett, Jon; Hall, Dana

1985-01-01

The availability and quality of computer resources during the software development process was speculated to have measurable, significant impact on the efficiency of the development process and the quality of the resulting product. Environment components such as the types of tools, machine responsiveness, and quantity of direct access storage may play a major role in the effort to produce the product and in its subsequent quality as measured by factors such as reliability and ease of maintenance. During the past six years, the NASA Goddard Space Flight Center has conducted experiments with software projects in an attempt to better understand the impact of software development methodologies, environments, and general technologies on the software process and product. Data was extracted and examined from nearly 50 software development projects. All were related to support of satellite flight dynamics ground-based computations. The relationship between computer resources and the software development process and product as exemplified by the subject NASA data was examined. Based upon the results, a number of computer resource-related implications are provided.

Performance of distributed multiscale simulations

PubMed Central

Borgdorff, J.; Ben Belgacem, M.; Bona-Casas, C.; Fazendeiro, L.; Groen, D.; Hoenen, O.; Mizeranschi, A.; Suter, J. L.; Coster, D.; Coveney, P. V.; Dubitzky, W.; Hoekstra, A. G.; Strand, P.; Chopard, B.

2014-01-01

Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption. PMID:24982258

Computation in Physics: Resources and Support

NASA Astrophysics Data System (ADS)

Engelhardt, Larry; Caballero, Marcos; Chonacky, Norman; Hilborn, Robert; Lopez Del Puerto, Marie; Roos, Kelly

We will describe exciting new resources and support opportunities that have been developed by ``PICUP'' to help faculty to integrate computation into their physics courses. (``PICUP'' is the ``Partnership for Integration of Computation into Undergraduate Physics''). These resources include editable curricular materials that can be downloaded from the PICUP Collection of the ComPADRE Digital Library: www.compadre.org/PICUP. Support opportunities include week-long workshops during the summer and single-day workshops at national AAPT and APS meetings. This project is funded by the National Science Foundation under DUE IUSE Grants 1524128, 1524493, 1524963, 1525062, and 1525525.

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.

Reconfigurable Computing Concepts for Space Missions: Universal Modular Spares

NASA Technical Reports Server (NTRS)

Patrick, M. Clinton

2007-01-01

Computing hardware for control, data collection, and other purposes will prove many times over crucial resources in NASA's upcoming space missions. Ability to provide these resources within mission payload requirements, with the hardiness to operate for extended periods under potentially harsh conditions in off-World environments, is daunting enough without considering the possibility of doing so with conventional electronics. This paper examines some ideas and options, and proposes some initial approaches, for logical design of reconfigurable computing resources offering true modularity, universal compatibility, and unprecedented flexibility to service all forms and needs of mission infrastructure.

An element search ant colony technique for solving virtual machine placement problem

NASA Astrophysics Data System (ADS)

Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

2017-09-01

The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing.

PubMed

Hari, Pradip; Ko, Kevin; Koukoumidis, Emmanouil; Kremer, Ulrich; Martonosi, Margaret; Ottoni, Desiree; Peh, Li-Shiuan; Zhang, Pei

2008-10-28

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

An integrated system for land resources supervision based on the IoT and cloud computing

NASA Astrophysics Data System (ADS)

Fang, Shifeng; Zhu, Yunqiang; Xu, Lida; Zhang, Jinqu; Zhou, Peiji; Luo, Kan; Yang, Jie

2017-01-01

Integrated information systems are important safeguards for the utilisation and development of land resources. Information technologies, including the Internet of Things (IoT) and cloud computing, are inevitable requirements for the quality and efficiency of land resources supervision tasks. In this study, an economical and highly efficient supervision system for land resources has been established based on IoT and cloud computing technologies; a novel online and offline integrated system with synchronised internal and field data that includes the entire process of 'discovering breaches, analysing problems, verifying fieldwork and investigating cases' was constructed. The system integrates key technologies, such as the automatic extraction of high-precision information based on remote sensing, semantic ontology-based technology to excavate and discriminate public sentiment on the Internet that is related to illegal incidents, high-performance parallel computing based on MapReduce, uniform storing and compressing (bitwise) technology, global positioning system data communication and data synchronisation mode, intelligent recognition and four-level ('device, transfer, system and data') safety control technology. The integrated system based on a 'One Map' platform has been officially implemented by the Department of Land and Resources of Guizhou Province, China, and was found to significantly increase the efficiency and level of land resources supervision. The system promoted the overall development of informatisation in fields related to land resource management.

A Novel College Network Resource Management Method using Cloud Computing

NASA Astrophysics Data System (ADS)

Lin, Chen

At present information construction of college mainly has construction of college networks and management information system; there are many problems during the process of information. Cloud computing is development of distributed processing, parallel processing and grid computing, which make data stored on the cloud, make software and services placed in the cloud and build on top of various standards and protocols, you can get it through all kinds of equipments. This article introduces cloud computing and function of cloud computing, then analyzes the exiting problems of college network resource management, the cloud computing technology and methods are applied in the construction of college information sharing platform.

Computer Engineers.

ERIC Educational Resources Information Center

Moncarz, Roger

2000-01-01

Looks at computer engineers and describes their job, employment outlook, earnings, and training and qualifications. Provides a list of resources related to computer engineering careers and the computer industry. (JOW)

Graphic analysis of resources by numerical evaluation techniques (Garnet)

USGS Publications Warehouse

Olson, A.C.

1977-01-01

An interactive computer program for graphical analysis has been developed by the U.S. Geological Survey. The program embodies five goals, (1) economical use of computer resources, (2) simplicity for user applications, (3) interactive on-line use, (4) minimal core requirements, and (5) portability. It is designed to aid (1) the rapid analysis of point-located data, (2) structural mapping, and (3) estimation of area resources. ?? 1977.

Virtual pools for interactive analysis and software development through an integrated Cloud environment

NASA Astrophysics Data System (ADS)

Grandi, C.; Italiano, A.; Salomoni, D.; Calabrese Melcarne, A. K.

2011-12-01

WNoDeS, an acronym for Worker Nodes on Demand Service, is software developed at CNAF-Tier1, the National Computing Centre of the Italian Institute for Nuclear Physics (INFN) located in Bologna. WNoDeS provides on demand, integrated access to both Grid and Cloud resources through virtualization technologies. Besides the traditional use of computing resources in batch mode, users need to have interactive and local access to a number of systems. WNoDeS can dynamically select these computers instantiating Virtual Machines, according to the requirements (computing, storage and network resources) of users through either the Open Cloud Computing Interface API, or through a web console. An interactive use is usually limited to activities in user space, i.e. where the machine configuration is not modified. In some other instances the activity concerns development and testing of services and thus implies the modification of the system configuration (and, therefore, root-access to the resource). The former use case is a simple extension of the WNoDeS approach, where the resource is provided in interactive mode. The latter implies saving the virtual image at the end of each user session so that it can be presented to the user at subsequent requests. This work describes how the LHC experiments at INFN-Bologna are testing and making use of these dynamically created ad-hoc machines via WNoDeS to support flexible, interactive analysis and software development at the INFN Tier-1 Computing Centre.

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.

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.

Computing with a single qubit faster than the computation quantum speed limit

NASA Astrophysics Data System (ADS)

Sinitsyn, Nikolai A.

2018-02-01

The possibility to save and process information in fundamentally indistinguishable states is the quantum mechanical resource that is not encountered in classical computing. I demonstrate that, if energy constraints are imposed, this resource can be used to accelerate information-processing without relying on entanglement or any other type of quantum correlations. In fact, there are computational problems that can be solved much faster, in comparison to currently used classical schemes, by saving intermediate information in nonorthogonal states of just a single qubit. There are also error correction strategies that protect such computations.

Framework Resources Multiply Computing Power

NASA Technical Reports Server (NTRS)

2010-01-01

As an early proponent of grid computing, Ames Research Center awarded Small Business Innovation Research (SBIR) funding to 3DGeo Development Inc., of Santa Clara, California, (now FusionGeo Inc., of The Woodlands, Texas) to demonstrate a virtual computer environment that linked geographically dispersed computer systems over the Internet to help solve large computational problems. By adding to an existing product, FusionGeo enabled access to resources for calculation- or data-intensive applications whenever and wherever they were needed. Commercially available as Accelerated Imaging and Modeling, the product is used by oil companies and seismic service companies, which require large processing and data storage capacities.

Integration of Openstack cloud resources in BES III computing cluster

NASA Astrophysics Data System (ADS)

Li, Haibo; Cheng, Yaodong; Huang, Qiulan; Cheng, Zhenjing; Shi, Jingyan

2017-10-01

Cloud computing provides a new technical means for data processing of high energy physics experiment. However, the resource of each queue is fixed and the usage of the resource is static in traditional job management system. In order to make it simple and transparent for physicist to use, we developed a virtual cluster system (vpmanager) to integrate IHEPCloud and different batch systems such as Torque and HTCondor. Vpmanager provides dynamic virtual machines scheduling according to the job queue. The BES III use case results show that resource efficiency is greatly improved.

Modified stretched exponential model of computer system resources management limitations-The case of cache memory

NASA Astrophysics Data System (ADS)

Strzałka, Dominik; Dymora, Paweł; Mazurek, Mirosław

2018-02-01

In this paper we present some preliminary results in the field of computer systems management with relation to Tsallis thermostatistics and the ubiquitous problem of hardware limited resources. In the case of systems with non-deterministic behaviour, management of their resources is a key point that guarantees theirs acceptable performance and proper working. This is very wide problem that stands for many challenges in financial, transport, water and food, health, etc. areas. We focus on computer systems with attention paid to cache memory and propose to use an analytical model that is able to connect non-extensive entropy formalism, long-range dependencies, management of system resources and queuing theory. Obtained analytical results are related to the practical experiment showing interesting and valuable results.

Dynamic Extension of a Virtualized Cluster by using Cloud Resources

NASA Astrophysics Data System (ADS)

Oberst, Oliver; Hauth, Thomas; Kernert, David; Riedel, Stephan; Quast, Günter

2012-12-01

The specific requirements concerning the software environment within the HEP community constrain the choice of resource providers for the outsourcing of computing infrastructure. The use of virtualization in HPC clusters and in the context of cloud resources is therefore a subject of recent developments in scientific computing. The dynamic virtualization of worker nodes in common batch systems provided by ViBatch serves each user with a dynamically virtualized subset of worker nodes on a local cluster. Now it can be transparently extended by the use of common open source cloud interfaces like OpenNebula or Eucalyptus, launching a subset of the virtual worker nodes within the cloud. This paper demonstrates how a dynamically virtualized computing cluster is combined with cloud resources by attaching remotely started virtual worker nodes to the local batch system.

Accounting utility for determining individual usage of production level software systems

NASA Technical Reports Server (NTRS)

Garber, S. C.

1984-01-01

An accounting package was developed which determines the computer resources utilized by a user during the execution of a particular program and updates a file containing accumulated resource totals. The accounting package is divided into two separate programs. The first program determines the total amount of computer resources utilized by a user during the execution of a particular program. The second program uses these totals to update a file containing accumulated totals of computer resources utilized by a user for a particular program. This package is useful to those persons who have several other users continually accessing and running programs from their accounts. The package provides the ability to determine which users are accessing and running specified programs along with their total level of usage.

The HEPCloud Facility: elastic computing for High Energy Physics - The NOvA Use Case

NASA Astrophysics Data System (ADS)

Fuess, S.; Garzoglio, G.; Holzman, B.; Kennedy, R.; Norman, A.; Timm, S.; Tiradani, A.

2017-10-01

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 38 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

From sequencer to supercomputer: an automatic pipeline for managing and processing next generation sequencing data.

PubMed

Camerlengo, Terry; Ozer, Hatice Gulcin; Onti-Srinivasan, Raghuram; Yan, Pearlly; Huang, Tim; Parvin, Jeffrey; Huang, Kun

2012-01-01

Next Generation Sequencing is highly resource intensive. NGS Tasks related to data processing, management and analysis require high-end computing servers or even clusters. Additionally, processing NGS experiments requires suitable storage space and significant manual interaction. At The Ohio State University's Biomedical Informatics Shared Resource, we designed and implemented a scalable architecture to address the challenges associated with the resource intensive nature of NGS secondary analysis built around Illumina Genome Analyzer II sequencers and Illumina's Gerald data processing pipeline. The software infrastructure includes a distributed computing platform consisting of a LIMS called QUEST (http://bisr.osumc.edu), an Automation Server, a computer cluster for processing NGS pipelines, and a network attached storage device expandable up to 40TB. The system has been architected to scale to multiple sequencers without requiring additional computing or labor resources. This platform provides demonstrates how to manage and automate NGS experiments in an institutional or core facility setting.

Contextuality supplies the 'magic' for quantum computation.

PubMed

Howard, Mark; Wallman, Joel; Veitch, Victor; Emerson, Joseph

2014-06-19

Quantum computers promise dramatic advantages over their classical counterparts, but the source of the power in quantum computing has remained elusive. Here we prove a remarkable equivalence between the onset of contextuality and the possibility of universal quantum computation via 'magic state' distillation, which is the leading model for experimentally realizing a fault-tolerant quantum computer. This is a conceptually satisfying link, because contextuality, which precludes a simple 'hidden variable' model of quantum mechanics, provides one of the fundamental characterizations of uniquely quantum phenomena. Furthermore, this connection suggests a unifying paradigm for the resources of quantum information: the non-locality of quantum theory is a particular kind of contextuality, and non-locality is already known to be a critical resource for achieving advantages with quantum communication. In addition to clarifying these fundamental issues, this work advances the resource framework for quantum computation, which has a number of practical applications, such as characterizing the efficiency and trade-offs between distinct theoretical and experimental schemes for achieving robust quantum computation, and putting bounds on the overhead cost for the classical simulation of quantum algorithms.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

The OSG Open Facility: an on-ramp for opportunistic scientific computing

NASA Astrophysics Data System (ADS)

Jayatilaka, B.; Levshina, T.; Sehgal, C.; Gardner, R.; Rynge, M.; Würthwein, F.

2017-10-01

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

The OSG Open Facility: An On-Ramp for Opportunistic Scientific Computing

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

Jayatilaka, B.; Levshina, T.; Sehgal, C.

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource ownersmore » and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.« less

Use of Emerging Grid Computing Technologies for the Analysis of LIGO Data

NASA Astrophysics Data System (ADS)

Koranda, Scott

2004-03-01

The LIGO Scientific Collaboration (LSC) today faces the challenge of enabling analysis of terabytes of LIGO data by hundreds of scientists from institutions all around the world. To meet this challenge the LSC is developing tools, infrastructure, applications, and expertise leveraging Grid Computing technologies available today, and making available to LSC scientists compute resources at sites across the United States and Europe. We use digital credentials for strong and secure authentication and authorization to compute resources and data. Building on top of products from the Globus project for high-speed data transfer and information discovery we have created the Lightweight Data Replicator (LDR) to securely and robustly replicate data to resource sites. We have deployed at our computing sites the Virtual Data Toolkit (VDT) Server and Client packages, developed in collaboration with our partners in the GriPhyN and iVDGL projects, providing uniform access to distributed resources for users and their applications. Taken together these Grid Computing technologies and infrastructure have formed the LSC DataGrid--a coherent and uniform environment across two continents for the analysis of gravitational-wave detector data. Much work, however, remains in order to scale current analyses and recent lessons learned need to be integrated into the next generation of Grid middleware.

An expert fitness diagnosis system based on elastic cloud computing.

PubMed

Tseng, Kevin C; Wu, Chia-Chuan

2014-01-01

This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service.

Satellite on-board processing for earth resources data

NASA Technical Reports Server (NTRS)

Bodenheimer, R. E.; Gonzalez, R. C.; Gupta, J. N.; Hwang, K.; Rochelle, R. W.; Wilson, J. B.; Wintz, P. A.

1975-01-01

Results of a survey of earth resources user applications and their data requirements, earth resources multispectral scanner sensor technology, and preprocessing algorithms for correcting the sensor outputs and for data bulk reduction are presented along with a candidate data format. Computational requirements required to implement the data analysis algorithms are included along with a review of computer architectures and organizations. Computer architectures capable of handling the algorithm computational requirements are suggested and the environmental effects of an on-board processor discussed. By relating performance parameters to the system requirements of each of the user requirements the feasibility of on-board processing is determined for each user. A tradeoff analysis is performed to determine the sensitivity of results to each of the system parameters. Significant results and conclusions are discussed, and recommendations are presented.

Large Scale Computing and Storage Requirements for High Energy Physics

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

Gerber, Richard A.; Wasserman, Harvey

2010-11-24

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility for the Department of Energy's Office of Science, providing high-performance computing (HPC) resources to more than 3,000 researchers working on about 400 projects. NERSC provides large-scale computing resources and, crucially, the support and expertise needed for scientists to make effective use of them. In November 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of High Energy Physics (HEP) held a workshop to characterize the HPC resources needed at NERSC to support HEP research through the next three to five years. Themore » effort is part of NERSC's legacy of anticipating users needs and deploying resources to meet those demands. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. The chief findings: (1) Science teams need access to a significant increase in computational resources to meet their research goals; (2) Research teams need to be able to read, write, transfer, store online, archive, analyze, and share huge volumes of data; (3) Science teams need guidance and support to implement their codes on future architectures; and (4) Projects need predictable, rapid turnaround of their computational jobs to meet mission-critical time constraints. This report expands upon these key points and includes others. It also presents a number of case studies as representative of the research conducted within HEP. Workshop participants were asked to codify their requirements in this case study format, summarizing their science goals, methods of solution, current and three-to-five year computing requirements, and software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, multi-core environment that is expected to dominate HPC architectures over the next few years. The report includes a section that describes efforts already underway or planned at NERSC that address requirements collected at the workshop. NERSC has many initiatives in progress that address key workshop findings and are aligned with NERSC's strategic plans.« less

Online production validation in a HEP environment

NASA Astrophysics Data System (ADS)

Harenberg, T.; Kuhl, T.; Lang, N.; Mättig, P.; Sandhoff, M.; Schwanenberger, C.; Volkmer, F.

2017-03-01

In high energy physics (HEP) event simulations, petabytes of data are processed and stored requiring millions of CPU-years. This enormous demand for computing resources is handled by centers distributed worldwide, which form part of the LHC computing grid. The consumption of such an important amount of resources demands for an efficient production of simulation and for the early detection of potential errors. In this article we present a new monitoring framework for grid environments, which polls a measure of data quality during job execution. This online monitoring facilitates the early detection of configuration errors (specially in simulation parameters), and may thus contribute to significant savings in computing resources.

Secure key storage and distribution

DOEpatents

Agrawal, Punit

2015-06-02

This disclosure describes a distributed, fault-tolerant security system that enables the secure storage and distribution of private keys. In one implementation, the security system includes a plurality of computing resources that independently store private keys provided by publishers and encrypted using a single security system public key. To protect against malicious activity, the security system private key necessary to decrypt the publication private keys is not stored at any of the computing resources. Rather portions, or shares of the security system private key are stored at each of the computing resources within the security system and multiple security systems must communicate and share partial decryptions in order to decrypt the stored private key.

Changing from computing grid to knowledge grid in life-science grid.

PubMed

Talukdar, Veera; Konar, Amit; Datta, Ayan; Choudhury, Anamika Roy

2009-09-01

Grid computing has a great potential to become a standard cyber infrastructure for life sciences that often require high-performance computing and large data handling, which exceeds the computing capacity of a single institution. Grid computer applies the resources of many computers in a network to a single problem at the same time. It is useful to scientific problems that require a great number of computer processing cycles or access to a large amount of data.As biologists,we are constantly discovering millions of genes and genome features, which are assembled in a library and distributed on computers around the world.This means that new, innovative methods must be developed that exploit the re-sources available for extensive calculations - for example grid computing.This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing a "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. By extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

Grid site availability evaluation and monitoring at CMS

DOE PAGES

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; ...

2017-10-01

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

Grid site availability evaluation and monitoring at CMS

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

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

Grid site availability evaluation and monitoring at CMS

NASA Astrophysics Data System (ADS)

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; Lammel, Stephan; Sciabà, Andrea

2017-10-01

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impact data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.

Bounding the Resource Availability of Partially Ordered Events with Constant Resource Impact

NASA Technical Reports Server (NTRS)

Frank, Jeremy

2004-01-01

We compare existing techniques to bound the resource availability of partially ordered events. We first show that, contrary to intuition, two existing techniques, one due to Laborie and one due to Muscettola, are not strictly comparable in terms of the size of the search trees generated under chronological search with a fixed heuristic. We describe a generalization of these techniques called the Flow Balance Constraint to tightly bound the amount of available resource for a set of partially ordered events with piecewise constant resource impact We prove that the new technique generates smaller proof trees under chronological search with a fixed heuristic, at little increase in computational expense. We then show how to construct tighter resource bounds but at increased computational cost.

ACToR: Aggregated Computational Toxicology Resource (T)

EPA Science Inventory

The EPA Aggregated Computational Toxicology Resource (ACToR) is a set of databases compiling information on chemicals in the environment from a large number of public and in-house EPA sources. ACToR has 3 main goals: (1) The serve as a repository of public toxicology information ...

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.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

2014-06-01

ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

A Cost-Benefit Study of Doing Astrophysics On The Cloud: Production of Image Mosaics

NASA Astrophysics Data System (ADS)

Berriman, G. B.; Good, J. C. Deelman, E.; Singh, G. Livny, M.

2009-09-01

Utility grids such as the Amazon EC2 and Amazon S3 clouds offer computational and storage resources that can be used on-demand for a fee by compute- and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. We studied via simulation the cost performance trade-offs of different execution and resource provisioning plans by creating, under the Amazon cloud fee structure, mosaics with the Montage image mosaic engine, a widely used data- and compute-intensive application. Specifically, we studied the cost of building mosaics of 2MASS data that have sizes of 1, 2 and 4 square degrees, and a 2MASS all-sky mosaic. These are examples of mosaics commonly generated by astronomers. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archiving. Our results show that by provisioning the right amount of storage and compute resources cost can be significantly reduced with no significant impact on application performance.

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems

PubMed Central

Idris, Hajara; Junaidu, Sahalu B.; Adewumi, Aderemi O.

2017-01-01

The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time. PMID:28545075

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

30 CFR 206.154 - Determination of quantities and qualities for computing royalties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Determination of quantities and qualities for computing royalties. 206.154 Section 206.154 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR MINERALS REVENUE MANAGEMENT PRODUCT VALUATION Federal Gas § 206.154 Determination of...

Resource Guide for Persons with Speech or Language Impairments.

ERIC Educational Resources Information Center

IBM, Atlanta, GA. National Support Center for Persons with Disabilities.

The resource guide identifies products which assist speech or language impaired individuals in accessing IBM (International Business Machine) Personal Computers or the IBM Personal System/2 family of products. An introduction provides a general overview of ways computers can help persons with speech or language handicaps. The document then…

Adolescents, Health Education, and Computers: The Body Awareness Resource Network (BARN).

ERIC Educational Resources Information Center

Bosworth, Kris; And Others

1983-01-01

The Body Awareness Resource Network (BARN) is a computer-based system designed as a confidential, nonjudgmental source of health information for adolescents. Topics include alcohol and other drugs, diet and activity, family communication, human sexuality, smoking, and stress management; programs are available for high school and middle school…

The Ever-Present Demand for Public Computing Resources. CDS Spotlight

ERIC Educational Resources Information Center

Pirani, Judith A.

2014-01-01

This Core Data Service (CDS) Spotlight focuses on public computing resources, including lab/cluster workstations in buildings, virtual lab/cluster workstations, kiosks, laptop and tablet checkout programs, and workstation access in unscheduled classrooms. The findings are derived from 758 CDS 2012 participating institutions. A dataset of 529…

Ontology-Driven Discovery of Scientific Computational Entities

ERIC Educational Resources Information Center

Brazier, Pearl W.

2010-01-01

Many geoscientists use modern computational resources, such as software applications, Web services, scientific workflows and datasets that are readily available on the Internet, to support their research and many common tasks. These resources are often shared via human contact and sometimes stored in data portals; however, they are not necessarily…

Junior High Computer Studies: Teacher Resource Manual.

ERIC Educational Resources Information Center

Alberta Dept. of Education, Edmonton. Curriculum Branch.

This manual is designed to help classroom teachers in Alberta, Canada implement the Junior High Computer Studies Program. The first eight sections cover the following material: (1) introduction to the teacher resource manual; (2) program rationale and philosophy; (3) general learner expectations; (4) program framework and flexibility; (5) program…

KAPEAN: Understanding Affective States of Children with ADHD

ERIC Educational Resources Information Center

Martínez, Fernando; Barraza, Claudia; González, Nimrod; González, Juan

2016-01-01

Affective computing seeks to create computational systems that adapt content and resources according to the affective states of the users. However, the detection of the user's affection such as motivation and emotion is challenging especially when an attention problem is present. An approach to convey learning resources to children with learning…

Guidelines for Developing Computer Based Resource Units. Revised.

ERIC Educational Resources Information Center

State Univ. of New York, Buffalo. Coll. at Buffalo. Educational Research and Development Complex.

Presented for use with normal and handicapped children are guidelines for the development of computer based resource units organized into two operations: one of which is the production of software which includes the writing of instructional objectives, content, activities, materials, and measuring devices; and the other the coding of the software…

Lambda Data Grid: Communications Architecture in Support of Grid Computing

DTIC Science & Technology

2006-12-21

number of paradigm shifts in the 20th century, including the growth of large geographically dispersed teams and the use of simulations and computational...get results. The work in this thesis automates the orchestration of networks with other resources, better utilizing all resources in a time efficient...domains, over transatlantic links in around minute. The main goal of this thesis is to build a new grid-computing paradigm that fully harnesses the

Exploiting multicore compute resources in the CMS experiment

NASA Astrophysics Data System (ADS)

Ramírez, J. E.; Pérez-Calero Yzquierdo, A.; Hernández, J. M.; CMS Collaboration

2016-10-01

CMS has developed a strategy to efficiently exploit the multicore architecture of the compute resources accessible to the experiment. A coherent use of the multiple cores available in a compute node yields substantial gains in terms of resource utilization. The implemented approach makes use of the multithreading support of the event processing framework and the multicore scheduling capabilities of the resource provisioning system. Multicore slots are acquired and provisioned by means of multicore pilot agents which internally schedule and execute single and multicore payloads. Multicore scheduling and multithreaded processing are currently used in production for online event selection and prompt data reconstruction. More workflows are being adapted to run in multicore mode. This paper presents a review of the experience gained in the deployment and operation of the multicore scheduling and processing system, the current status and future plans.

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.

ATLAS Cloud R&D

NASA Astrophysics Data System (ADS)

Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration

2014-06-01

The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

Computed Tomography (CT) - Spine

MedlinePlus

... Resources Professions Site Index A-Z Computed Tomography (CT) - Spine Computed tomography (CT) of the spine is ... of CT Scanning of the Spine? What is CT Scanning of the Spine? Computed tomography, more commonly ...

Hybrid architecture for encoded measurement-based quantum computation

PubMed Central

Zwerger, M.; Briegel, H. J.; Dür, W.

2014-01-01

We present a hybrid scheme for quantum computation that combines the modular structure of elementary building blocks used in the circuit model with the advantages of a measurement-based approach to quantum computation. We show how to construct optimal resource states of minimal size to implement elementary building blocks for encoded quantum computation in a measurement-based way, including states for error correction and encoded gates. The performance of the scheme is determined by the quality of the resource states, where within the considered error model a threshold of the order of 10% local noise per particle for fault-tolerant quantum computation and quantum communication. PMID:24946906

Quantum computation over the butterfly network

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

Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.

2011-07-15

In order to investigate distributed quantum computation under restricted network resources, we introduce a quantum computation task over the butterfly network where both quantum and classical communications are limited. We consider deterministically performing a two-qubit global unitary operation on two unknown inputs given at different nodes, with outputs at two distinct nodes. By using a particular resource setting introduced by M. Hayashi [Phys. Rev. A 76, 040301(R) (2007)], which is capable of performing a swap operation by adding two maximally entangled qubits (ebits) between the two input nodes, we show that unitary operations can be performed without adding any entanglementmore » resource, if and only if the unitary operations are locally unitary equivalent to controlled unitary operations. Our protocol is optimal in the sense that the unitary operations cannot be implemented if we relax the specifications of any of the channels. We also construct protocols for performing controlled traceless unitary operations with a 1-ebit resource and for performing global Clifford operations with a 2-ebit resource.« less

Consolidation of cloud computing in ATLAS

NASA Astrophysics Data System (ADS)

Taylor, Ryan P.; Domingues Cordeiro, Cristovao Jose; Giordano, Domenico; Hover, John; Kouba, Tomas; Love, Peter; McNab, Andrew; Schovancova, Jaroslava; Sobie, Randall; ATLAS Collaboration

2017-10-01

Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems.

Applications of the pipeline environment for visual informatics and genomics computations

PubMed Central

2011-01-01

Background Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols. Results This paper reports on the applications of the LONI Pipeline environment to address two informatics challenges - graphical management of diverse genomics tools, and the interoperability of informatics software. Specifically, this manuscript presents the concrete details of deploying general informatics suites and individual software tools to new hardware infrastructures, the design, validation and execution of new visual analysis protocols via the Pipeline graphical interface, and integration of diverse informatics tools via the Pipeline eXtensible Markup Language syntax. We demonstrate each of these processes using several established informatics packages (e.g., miBLAST, EMBOSS, mrFAST, GWASS, MAQ, SAMtools, Bowtie) for basic local sequence alignment and search, molecular biology data analysis, and genome-wide association studies. These examples demonstrate the power of the Pipeline graphical workflow environment to enable integration of bioinformatics resources which provide a well-defined syntax for dynamic specification of the input/output parameters and the run-time execution controls. Conclusions The LONI Pipeline environment http://pipeline.loni.ucla.edu provides a flexible graphical infrastructure for efficient biomedical computing and distributed informatics research. The interactive Pipeline resource manager enables the utilization and interoperability of diverse types of informatics resources. The Pipeline client-server model provides computational power to a broad spectrum of informatics investigators - experienced developers and novice users, user with or without access to advanced computational-resources (e.g., Grid, data), as well as basic and translational scientists. The open development, validation and dissemination of computational networks (pipeline workflows) facilitates the sharing of knowledge, tools, protocols and best practices, and enables the unbiased validation and replication of scientific findings by the entire community. PMID:21791102

Using OSG Computing Resources with (iLC)Dirac

NASA Astrophysics Data System (ADS)

Sailer, A.; Petric, M.; CLICdp Collaboration

2017-10-01

CPU cycles for small experiments and projects can be scarce, thus making use of all available resources, whether dedicated or opportunistic, is mandatory. While enabling uniform access to the LCG computing elements (ARC, CREAM), the DIRAC grid interware was not able to use OSG computing elements (GlobusCE, HTCondor-CE) without dedicated support at the grid site through so called ‘SiteDirectors’, which directly submit to the local batch system. This in turn requires additional dedicated effort for small experiments on the grid site. Adding interfaces to the OSG CEs through the respective grid middleware is therefore allowing accessing them within the DIRAC software without additional site-specific infrastructure. This enables greater use of opportunistic resources for experiments and projects without dedicated clusters or an established computing infrastructure with the DIRAC software. To allow sending jobs to HTCondor-CE and legacy Globus computing elements inside DIRAC the required wrapper classes were developed. Not only is the usage of these types of computing elements now completely transparent for all DIRAC instances, which makes DIRAC a flexible solution for OSG based virtual organisations, but it also allows LCG Grid Sites to move to the HTCondor-CE software, without shutting DIRAC based VOs out of their site. In these proceedings we detail how we interfaced the DIRAC system to the HTCondor-CE and Globus computing elements and explain the encountered obstacles and solutions developed, and how the linear collider community uses resources in the OSG.

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

NASA Technical Reports Server (NTRS)

Rutishauser, David

2006-01-01

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Elucidating reaction mechanisms on quantum computers.

PubMed

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M; Wecker, Dave; Troyer, Matthias

2017-07-18

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

Elucidating reaction mechanisms on quantum computers

PubMed Central

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

2017-01-01

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources. PMID:28674011

Elucidating reaction mechanisms on quantum computers

NASA Astrophysics Data System (ADS)

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

2017-07-01

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

LINCS: Livermore's network architecture. [Octopus computing network

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

Fletcher, J.G.

1982-01-01

Octopus, a local computing network that has been evolving at the Lawrence Livermore National Laboratory for over fifteen years, is currently undergoing a major revision. The primary purpose of the revision is to consolidate and redefine the variety of conventions and formats, which have grown up over the years, into a single standard family of protocols, the Livermore Interactive Network Communication Standard (LINCS). This standard treats the entire network as a single distributed operating system such that access to a computing resource is obtained in a single way, whether that resource is local (on the same computer as the accessingmore » process) or remote (on another computer). LINCS encompasses not only communication but also such issues as the relationship of customer to server processes and the structure, naming, and protection of resources. The discussion includes: an overview of the Livermore user community and computing hardware, the functions and structure of each of the seven layers of LINCS protocol, the reasons why we have designed our own protocols and why we are dissatisfied by the directions that current protocol standards are taking.« less

Transformation of OODT CAS to Perform Larger Tasks

NASA Technical Reports Server (NTRS)

Mattmann, Chris; Freeborn, Dana; Crichton, Daniel; Hughes, John; Ramirez, Paul; Hardman, Sean; Woollard, David; Kelly, Sean

2008-01-01

A computer program denoted OODT CAS has been transformed to enable performance of larger tasks that involve greatly increased data volumes and increasingly intensive processing of data on heterogeneous, geographically dispersed computers. Prior to the transformation, OODT CAS (also alternatively denoted, simply, 'CAS') [wherein 'OODT' signifies 'Object-Oriented Data Technology' and 'CAS' signifies 'Catalog and Archive Service'] was a proven software component used to manage scientific data from spaceflight missions. In the transformation, CAS was split into two separate components representing its canonical capabilities: file management and workflow management. In addition, CAS was augmented by addition of a resource-management component. This third component enables CAS to manage heterogeneous computing by use of diverse resources, including high-performance clusters of computers, commodity computing hardware, and grid computing infrastructures. CAS is now more easily maintainable, evolvable, and reusable. These components can be used separately or, taking advantage of synergies, can be used together. Other elements of the transformation included addition of a separate Web presentation layer that supports distribution of data products via Really Simple Syndication (RSS) feeds, and provision for full Resource Description Framework (RDF) exports of metadata.

Critical phenomena in communication/computation networks with various topologies and suboptimal to optimal resource allocation

NASA Astrophysics Data System (ADS)

Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi

2015-01-01

We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.

A Review of High-Performance Computational Strategies for Modeling and Imaging of Electromagnetic Induction Data

NASA Astrophysics Data System (ADS)

Newman, Gregory A.

2014-01-01

Many geoscientific applications exploit electrostatic and electromagnetic fields to interrogate and map subsurface electrical resistivity—an important geophysical attribute for characterizing mineral, energy, and water resources. In complex three-dimensional geologies, where many of these resources remain to be found, resistivity mapping requires large-scale modeling and imaging capabilities, as well as the ability to treat significant data volumes, which can easily overwhelm single-core and modest multicore computing hardware. To treat such problems requires large-scale parallel computational resources, necessary for reducing the time to solution to a time frame acceptable to the exploration process. The recognition that significant parallel computing processes must be brought to bear on these problems gives rise to choices that must be made in parallel computing hardware and software. In this review, some of these choices are presented, along with the resulting trade-offs. We also discuss future trends in high-performance computing and the anticipated impact on electromagnetic (EM) geophysics. Topics discussed in this review article include a survey of parallel computing platforms, graphics processing units to multicore CPUs with a fast interconnect, along with effective parallel solvers and associated solver libraries effective for inductive EM modeling and imaging.

Optimisation of the usage of LHC and local computing resources in a multidisciplinary physics department hosting a WLCG Tier-2 centre

NASA Astrophysics Data System (ADS)

Barberis, Stefano; Carminati, Leonardo; Leveraro, Franco; Mazza, Simone Michele; Perini, Laura; Perlz, Francesco; Rebatto, David; Tura, Ruggero; Vaccarossa, Luca; Villaplana, Miguel

2015-12-01

We present the approach of the University of Milan Physics Department and the local unit of INFN to allow and encourage the sharing among different research areas of computing, storage and networking resources (the largest ones being those composing the Milan WLCG Tier-2 centre and tailored to the needs of the ATLAS experiment). Computing resources are organised as independent HTCondor pools, with a global master in charge of monitoring them and optimising their usage. The configuration has to provide satisfactory throughput for both serial and parallel (multicore, MPI) jobs. A combination of local, remote and cloud storage options are available. The experience of users from different research areas operating on this shared infrastructure is discussed. The promising direction of improving scientific computing throughput by federating access to distributed computing and storage also seems to fit very well with the objectives listed in the European Horizon 2020 framework for research and development.

Human face recognition using eigenface in cloud computing environment

NASA Astrophysics Data System (ADS)

Siregar, S. T. M.; Syahputra, M. F.; Rahmat, R. F.

2018-02-01

Doing a face recognition for one single face does not take a long time to process, but if we implement attendance system or security system on companies that have many faces to be recognized, it will take a long time. Cloud computing is a computing service that is done not on a local device, but on an internet connected to a data center infrastructure. The system of cloud computing also provides a scalability solution where cloud computing can increase the resources needed when doing larger data processing. This research is done by applying eigenface while collecting data as training data is also done by using REST concept to provide resource, then server can process the data according to existing stages. After doing research and development of this application, it can be concluded by implementing Eigenface, recognizing face by applying REST concept as endpoint in giving or receiving related information to be used as a resource in doing model formation to do face recognition.

NASA CORE (Central Operation of Resources for Educators) Educational Materials Catalog

NASA Technical Reports Server (NTRS)

1998-01-01

This educational materials catalog presents NASA CORE (Central Operation of Resources for Educators). The topics include: 1) Videocassettes (Aeronautics, Earth Resources, Weather, Space Exploration/Satellites, Life Sciences, Careers); 2) Slide Programs; 3) Computer Materials; 4) NASA Memorabilia/Miscellaneous; 5) NASA Educator Resource Centers; 6) and NASA Resources.

Cyber Foraging for Improving Survivability of Mobile Systems

DTIC Science & Technology

2016-02-10

environments—such as dynamic context, limited computing resources, disconnected- intermittent - limited (DIL) network connectivity, and high levels of stress...environments, such as dynamic context, limited computing resources, disconnected- intermittent -limited (DIL) network connectivity, and high levels of...Table 1: Mapping of Cloudlet Features to Survivability Requirements Threats Intermittent Cloudlet- Enterprise Connectivity Mobility Limited

Natural Resource Information System. Volume I. Overall Description.

ERIC Educational Resources Information Center

Boeing Computer Services, Inc., Seattle, WA.

Recognizing the need for the development of a computer based information system which would handle remote sensing as well as conventional mapping data, the Bureau of Indian Affairs and the Bureau of Land Management contracted with Boeing Computer Services for the design and construction of a prototype Natural Resource Information System. The…

Selecting, Evaluating and Creating Policies for Computer-Based Resources in the Behavioral Sciences and Education.

ERIC Educational Resources Information Center

Richardson, Linda B., Comp.; And Others

This collection includes four handouts: (1) "Selection Critria Considerations for Computer-Based Resources" (Linda B. Richardson); (2) "Software Collection Policies in Academic Libraries" (a 24-item bibliography, Jane W. Johnson); (3) "Circulation and Security of Software" (a 19-item bibliography, Sara Elizabeth Williams); and (4) "Bibliography of…

Instructional Technology Comes of Age. Research Center Update.

ERIC Educational Resources Information Center

Clery, Suzanne; Lee, John

This report reviews the perceptions of the chief academic computing officer on campus of how well prepared faculty members in various academic departments were to use technology as a resource, which were the most important academic and instructional computing policies, procedures, and resources on campus, and what institutions saw as the most…

WRIS: a resource information system for wildland management

Treesearch

Robert M. Russell; David A. Sharpnack; Elliot Amidon

1975-01-01

WRIS (Wildland Resource Information System) is a computer system for processing, storing, retrieving, updating, and displaying geographic data. The polygon, representing a land area boundary, forms the building block of WRIS. Polygons form a map. Maps are digitized manually or by automatic scanning. Computer programs can extract and produce polygon maps and can overlay...

Resource Manual on the Use of Computers in Schooling.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Bureau of Technology Applications.

This resource manual is designed to provide educators with timely information on the use of computers and related technology in schools. Section one includes a review of the new Bureau of Technology Applications' goal, functions, and major programs and activities; a description of the Model Schools Program, which has been conceptually derived from…

Developing Online Learning Resources: Big Data, Social Networks, and Cloud Computing to Support Pervasive Knowledge

ERIC Educational Resources Information Center

Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

2016-01-01

Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of…

Pupil Science Learning in Resource-Based e-Learning Environments

ERIC Educational Resources Information Center

So, Wing-mui Winnie; Ching, Ngai-ying Fiona

2011-01-01

With the rapid expansion of broadband Internet connection and availability of high performance yet low priced computers, many countries around the world are advocating the adoption of e-learning, the use of computer technology to improve learning and teaching. The trend of e-learning has urged many teachers to incorporate online resources in their…

Training | High-Performance Computing | NREL

Science.gov Websites

Training Training Find training resources for using NREL's high-performance computing (HPC) systems as well as related online tutorials. Upcoming Training HPC User Workshop - June 12th We will be Conference, a group meets to discuss Best Practices in HPC Training. This group developed a list of resources

Realizing the Potential of Information Resources: Information, Technology, and Services. Track 8: Academic Computing and Libraries.

ERIC Educational Resources Information Center

CAUSE, Boulder, CO.

Eight papers are presented from the 1995 CAUSE conference track on academic computing and library issues faced by managers of information technology at colleges and universities. The papers include: (1) "Where's the Beef?: Implementation of Discipline-Specific Training on Internet Resources" (Priscilla Hancock and others); (2)…

Smoke and Air Resource Management-Peering Through the Haze

Treesearch

A. R. Fox Riebau

1987-01-01

This paper presents a vision of the future rooted in consideration of the past 20 years in the smoke and air resource management field. This future is characterized by rapid technological development of computers for computation, communications, and remote sensing capabilities and of the possible societal responses to these advances. We discuss intellectual...

18 CFR 281.304 - Computation of alternative fuel volume.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 1 2013-04-01 2013-04-01 false Computation of alternative fuel volume. 281.304 Section 281.304 Conservation of Power and Water Resources FEDERAL ENERGY... not a diesel engine or turbine designed to use distillate fuels as the only substitute for natural gas...

18 CFR 281.304 - Computation of alternative fuel volume.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 1 2014-04-01 2014-04-01 false Computation of alternative fuel volume. 281.304 Section 281.304 Conservation of Power and Water Resources FEDERAL ENERGY... not a diesel engine or turbine designed to use distillate fuels as the only substitute for natural gas...

18 CFR 281.304 - Computation of alternative fuel volume.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Computation of alternative fuel volume. 281.304 Section 281.304 Conservation of Power and Water Resources FEDERAL ENERGY... not a diesel engine or turbine designed to use distillate fuels as the only substitute for natural gas...

18 CFR 281.304 - Computation of alternative fuel volume.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Computation of alternative fuel volume. 281.304 Section 281.304 Conservation of Power and Water Resources FEDERAL ENERGY... not a diesel engine or turbine designed to use distillate fuels as the only substitute for natural gas...

18 CFR 281.304 - Computation of alternative fuel volume.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 1 2012-04-01 2012-04-01 false Computation of alternative fuel volume. 281.304 Section 281.304 Conservation of Power and Water Resources FEDERAL ENERGY... not a diesel engine or turbine designed to use distillate fuels as the only substitute for natural gas...

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

Ali, Amjad Majid; Albert, Don; Andersson, Par

SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work 9normally a parallel job) on the set of allocated nodes. Finally, it arbitrates conflicting requests for resources by managing a queue of pending work.

Controlling user access to electronic resources without password

DOEpatents

Smith, Fred Hewitt

2017-08-22

Described herein are devices and techniques for remotely controlling user access to a restricted computer resource. The process includes obtaining an image from a communication device of a user. An individual and a landmark are identified within the image. Determinations are made that the individual is the user and that the landmark is a predetermined landmark. Access to a restricted computing resource is granted based on the determining that the individual is the user and that the landmark is the predetermined landmark. Other embodiments are disclosed.

Computer Aided Software Engineering (CASE) Environment Issues.

DTIC Science & Technology

1987-06-01

tasks tend to be error prone and slowv when done by humans . Ti-.c,. are e’.el nt anidates for automation using a computer. (MacLennan. 10S1. p. 51 2...CASE r,’sourCcs; * human resources. Lonsisting of the people who use and facilitate utilization in !:1e case of manual resource, of the environment...engineering process in a given er,%irent rnizthe nature of rnanua! and human resources. CA.SU_ -esources should provide the softwvare enizincerin2 team

Future Approach to tier-0 extension

NASA Astrophysics Data System (ADS)

Jones, B.; McCance, G.; Cordeiro, C.; Giordano, D.; Traylen, S.; Moreno García, D.

2017-10-01

The current tier-0 processing at CERN is done on two managed sites, the CERN computer centre and the Wigner computer centre. With the proliferation of public cloud resources at increasingly competitive prices, we have been investigating how to transparently increase our compute capacity to include these providers. The approach taken has been to integrate these resources using our existing deployment and computer management tools and to provide them in a way that exposes them to users as part of the same site. The paper will describe the architecture, the toolset and the current production experiences of this model.

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.

Qudit quantum computation on matrix product states with global symmetry

NASA Astrophysics Data System (ADS)

Wang, Dongsheng; Stephen, David; Raussendorf, Robert

Resource states that contain nontrivial symmetry-protected topological order are identified for universal measurement-based quantum computation. Our resource states fall into two classes: one as the qudit generalizations of the qubit cluster state, and the other as the higher-symmetry generalizations of the spin-1 Affleck-Kennedy-Lieb-Tasaki (AKLT) state, namely, with unitary, orthogonal, or symplectic symmetry. The symmetry in cluster states protects information propagation (identity gate), while the higher symmetry in AKLT-type states enables nontrivial gate computation. This work demonstrates a close connection between measurement-based quantum computation and symmetry-protected topological order.

Qudit quantum computation on matrix product states with global symmetry

NASA Astrophysics Data System (ADS)

Wang, Dong-Sheng; Stephen, David T.; Raussendorf, Robert

2017-03-01

Resource states that contain nontrivial symmetry-protected topological order are identified for universal single-qudit measurement-based quantum computation. Our resource states fall into two classes: one as the qudit generalizations of the one-dimensional qubit cluster state, and the other as the higher-symmetry generalizations of the spin-1 Affleck-Kennedy-Lieb-Tasaki (AKLT) state, namely, with unitary, orthogonal, or symplectic symmetry. The symmetry in cluster states protects information propagation (identity gate), while the higher symmetry in AKLT-type states enables nontrivial gate computation. This work demonstrates a close connection between measurement-based quantum computation and symmetry-protected topological order.

VM Capacity-Aware Scheduling within Budget Constraints in IaaS Clouds

PubMed Central

Thanasias, Vasileios; Lee, Choonhwa; Hanif, Muhammad; Kim, Eunsam; Helal, Sumi

2016-01-01

Recently, cloud computing has drawn significant attention from both industry and academia, bringing unprecedented changes to computing and information technology. The infrastructure-as-a-Service (IaaS) model offers new abilities such as the elastic provisioning and relinquishing of computing resources in response to workload fluctuations. However, because the demand for resources dynamically changes over time, the provisioning of resources in a way that a given budget is efficiently utilized while maintaining a sufficing performance remains a key challenge. This paper addresses the problem of task scheduling and resource provisioning for a set of tasks running on IaaS clouds; it presents novel provisioning and scheduling algorithms capable of executing tasks within a given budget, while minimizing the slowdown due to the budget constraint. Our simulation study demonstrates a substantial reduction up to 70% in the overall task slowdown rate by the proposed algorithms. PMID:27501046

Need for evaluative methodologies in land use, regional resource and waste management planning

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

Croke, E. J.

The transfer of planning methodology from the research community to the practitioner very frequently takes the form of analytical and evaluative techniques and procedures. In the end, these become operational in the form of data acquisition, management and display systems, computational schemes that are codified in the form of manuals and handbooks, and computer simulation models. The complexity of the socioeconomic and physical processes that govern environmental resource and waste management have reinforced the need for computer assisted, scientifically sophisticated planning models that are fully operational, dependent on an attainable data base and accessible in terms of the resources normallymore » available to practitioners of regional resource management, waste management, and land use planning. A variety of models and procedures that attempt to meet one or more of the needs of these practitioners are discussed.« less

Geology and mineral and energy resources, Roswell Resource Area, New Mexico; an interactive computer presentation

USGS Publications Warehouse

Tidball, Ronald R.; Bartsch-Winkler, S. B.

1995-01-01

This Compact Disc-Read Only Memory (CD-ROM) contains a program illustrating the geology and mineral and energy resources of the Roswell Resource Area, an administrative unit of the U.S. Bureau of Land Management in east-central New Mexico. The program enables the user to access information on the geology, geochemistry, geophysics, mining history, metallic and industrial mineral commodities, hydrocarbons, and assessments of the area. The program was created with the display software, SuperCard, version 1.5, by Aldus. The program will run only on a Macintosh personal computer. This CD-ROM was produced in accordance with Macintosh HFS standards. The program was developed on a Macintosh II-series computer with system 7.0.1. The program is a compiled, executable form that is nonproprietary and does not require the presence of the SuperCard software.

Optimizing Resource Utilization in Grid Batch Systems

NASA Astrophysics Data System (ADS)

Gellrich, Andreas

2012-12-01

On Grid sites, the requirements of the computing tasks (jobs) to computing, storage, and network resources differ widely. For instance Monte Carlo production jobs are almost purely CPU-bound, whereas physics analysis jobs demand high data rates. In order to optimize the utilization of the compute node resources, jobs must be distributed intelligently over the nodes. Although the job resource requirements cannot be deduced directly, jobs are mapped to POSIX UID/GID according to the VO, VOMS group and role information contained in the VOMS proxy. The UID/GID then allows to distinguish jobs, if users are using VOMS proxies as planned by the VO management, e.g. ‘role=production’ for Monte Carlo jobs. It is possible to setup and configure batch systems (queuing system and scheduler) at Grid sites based on these considerations although scaling limits were observed with the scheduler MAUI. In tests these limitations could be overcome with a home-made scheduler.

Probability calculations for three-part mineral resource assessments

USGS Publications Warehouse

Ellefsen, Karl J.

2017-06-27

Three-part mineral resource assessment is a methodology for predicting, in a specified geographic region, both the number of undiscovered mineral deposits and the amount of mineral resources in those deposits. These predictions are based on probability calculations that are performed with computer software that is newly implemented. Compared to the previous implementation, the new implementation includes new features for the probability calculations themselves and for checks of those calculations. The development of the new implementation lead to a new understanding of the probability calculations, namely the assumptions inherent in the probability calculations. Several assumptions strongly affect the mineral resource predictions, so it is crucial that they are checked during an assessment. The evaluation of the new implementation leads to new findings about the probability calculations,namely findings regarding the precision of the computations,the computation time, and the sensitivity of the calculation results to the input.

A grid-enabled web service for low-resolution crystal structure refinement.

PubMed

O'Donovan, Daniel J; Stokes-Rees, Ian; Nam, Yunsun; Blacklow, Stephen C; Schröder, Gunnar F; Brunger, Axel T; Sliz, Piotr

2012-03-01

Deformable elastic network (DEN) restraints have proved to be a powerful tool for refining structures from low-resolution X-ray crystallographic data sets. Unfortunately, optimal refinement using DEN restraints requires extensive calculations and is often hindered by a lack of access to sufficient computational resources. The DEN web service presented here intends to provide structural biologists with access to resources for running computationally intensive DEN refinements in parallel on the Open Science Grid, the US cyberinfrastructure. Access to the grid is provided through a simple and intuitive web interface integrated into the SBGrid Science Portal. Using this portal, refinements combined with full parameter optimization that would take many thousands of hours on standard computational resources can now be completed in several hours. An example of the successful application of DEN restraints to the human Notch1 transcriptional complex using the grid resource, and summaries of all submitted refinements, are presented as justification.

VM Capacity-Aware Scheduling within Budget Constraints in IaaS Clouds.

PubMed

Thanasias, Vasileios; Lee, Choonhwa; Hanif, Muhammad; Kim, Eunsam; Helal, Sumi

2016-01-01

Recently, cloud computing has drawn significant attention from both industry and academia, bringing unprecedented changes to computing and information technology. The infrastructure-as-a-Service (IaaS) model offers new abilities such as the elastic provisioning and relinquishing of computing resources in response to workload fluctuations. However, because the demand for resources dynamically changes over time, the provisioning of resources in a way that a given budget is efficiently utilized while maintaining a sufficing performance remains a key challenge. This paper addresses the problem of task scheduling and resource provisioning for a set of tasks running on IaaS clouds; it presents novel provisioning and scheduling algorithms capable of executing tasks within a given budget, while minimizing the slowdown due to the budget constraint. Our simulation study demonstrates a substantial reduction up to 70% in the overall task slowdown rate by the proposed algorithms.

Climate simulations and services on HPC, Cloud and Grid infrastructures

NASA Astrophysics Data System (ADS)

Cofino, Antonio S.; Blanco, Carlos; Minondo Tshuma, Antonio

2017-04-01

Cloud, Grid and High Performance Computing have changed the accessibility and availability of computing resources for Earth Science research communities, specially for Climate community. These paradigms are modifying the way how climate applications are being executed. By using these technologies the number, variety and complexity of experiments and resources are increasing substantially. But, although computational capacity is increasing, traditional applications and tools used by the community are not good enough to manage this large volume and variety of experiments and computing resources. In this contribution, we evaluate the challenges to run climate simulations and services on Grid, Cloud and HPC infrestructures and how to tackle them. The Grid and Cloud infrastructures provided by EGI's VOs ( esr , earth.vo.ibergrid and fedcloud.egi.eu) will be evaluated, as well as HPC resources from PRACE infrastructure and institutional clusters. To solve those challenges, solutions using DRM4G framework will be shown. DRM4G provides a good framework to manage big volume and variety of computing resources for climate experiments. This work has been supported by the Spanish National R&D Plan under projects WRF4G (CGL2011-28864), INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R) ; the IS-ENES2 project from the 7FP of the European Commission (grant agreement no. 312979); the European Regional Development Fund—ERDF and the Programa de Personal Investigador en Formación Predoctoral from Universidad de Cantabria and Government of Cantabria.

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.

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research.

PubMed

Erdemir, Ahmet; Hunter, Peter J; Holzapfel, Gerhard A; Loew, Leslie M; Middleton, John; Jacobs, Christopher R; Nithiarasu, Perumal; Löhner, Rainlad; Wei, Guowei; Winkelstein, Beth A; Barocas, Victor H; Guilak, Farshid; Ku, Joy P; Hicks, Jennifer L; Delp, Scott L; Sacks, Michael; Weiss, Jeffrey A; Ateshian, Gerard A; Maas, Steve A; McCulloch, Andrew D; Peng, Grace C Y

2018-02-01

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate model sharing, and there are corresponding initiatives by the scientific journals. Outside the publishing enterprise, infrastructure to facilitate model sharing in biomechanics exists, and simulation software developers are interested in accommodating the community's needs for sharing of modeling resources. Encouragement for the use of standardized markups, concerns related to quality assurance, acknowledgement of increased burden, and importance of stewardship of resources are noted. In the short-term, it is advisable that the community builds upon recent strategies and experiments with new pathways for continued demonstration of model sharing, its promotion, and its utility. Nonetheless, the need for a long-term strategy to unify approaches in sharing computational models and related resources is acknowledged. Development of a sustainable platform supported by a culture of open model sharing will likely evolve through continued and inclusive discussions bringing all stakeholders at the table, e.g., by possibly establishing a consortium.

Opportunities and challenges of cloud computing to improve health care services.

PubMed

Kuo, Alex Mu-Hsing

2011-09-21

Cloud computing is a new way of delivering computing resources and services. Many managers and experts believe that it can improve health care services, benefit health care research, and change the face of health information technology. However, as with any innovation, cloud computing should be rigorously evaluated before its widespread adoption. This paper discusses the concept and its current place in health care, and uses 4 aspects (management, technology, security, and legal) to evaluate the opportunities and challenges of this computing model. Strategic planning that could be used by a health organization to determine its direction, strategy, and resource allocation when it has decided to migrate from traditional to cloud-based health services is also discussed.

Novel schemes for measurement-based quantum computation.

PubMed

Gross, D; Eisert, J

2007-06-01

We establish a framework which allows one to construct novel schemes for measurement-based quantum computation. The technique develops tools from many-body physics-based on finitely correlated or projected entangled pair states-to go beyond the cluster-state based one-way computer. We identify resource states radically different from the cluster state, in that they exhibit nonvanishing correlations, can be prepared using nonmaximally entangling gates, or have very different local entanglement properties. In the computational models, randomness is compensated in a different manner. It is shown that there exist resource states which are locally arbitrarily close to a pure state. We comment on the possibility of tailoring computational models to specific physical systems.

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

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

Fuess, S.; Garzoglio, G.; Holzman, B.

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a commonmore » interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.« less

Automation of the CFD Process on Distributed Computing Systems

NASA Technical Reports Server (NTRS)

Tejnil, Ed; Gee, Ken; Rizk, Yehia M.

2000-01-01

A script system was developed to automate and streamline portions of the CFD process. The system was designed to facilitate the use of CFD flow solvers on supercomputer and workstation platforms within a parametric design event. Integrating solver pre- and postprocessing phases, the fully automated ADTT script system marshalled the required input data, submitted the jobs to available computational resources, and processed the resulting output data. A number of codes were incorporated into the script system, which itself was part of a larger integrated design environment software package. The IDE and scripts were used in a design event involving a wind tunnel test. This experience highlighted the need for efficient data and resource management in all parts of the CFD process. To facilitate the use of CFD methods to perform parametric design studies, the script system was developed using UNIX shell and Perl languages. The goal of the work was to minimize the user interaction required to generate the data necessary to fill a parametric design space. The scripts wrote out the required input files for the user-specified flow solver, transferred all necessary input files to the computational resource, submitted and tracked the jobs using the resource queuing structure, and retrieved and post-processed the resulting dataset. For computational resources that did not run queueing software, the script system established its own simple first-in-first-out queueing structure to manage the workload. A variety of flow solvers were incorporated in the script system, including INS2D, PMARC, TIGER and GASP. Adapting the script system to a new flow solver was made easier through the use of object-oriented programming methods. The script system was incorporated into an ADTT integrated design environment and evaluated as part of a wind tunnel experiment. The system successfully generated the data required to fill the desired parametric design space. This stressed the computational resources required to compute and store the information. The scripts were continually modified to improve the utilization of the computational resources and reduce the likelihood of data loss due to failures. An ad-hoc file server was created to manage the large amount of data being generated as part of the design event. Files were stored and retrieved as needed to create new jobs and analyze the results. Additional information is contained in the original.

Computer-Based Resource Accounting Model for Generating Aggregate Resource Impacts of Alternative Automobile Technologies : Volume 1. Fleet Attributes Model

DOT National Transportation Integrated Search

1977-01-01

Auto production and operation consume energy, material, capital and labor resources. Numerous substitution possibilities exist within and between resource sectors, corresponding to the broad spectrum of potential design technologies. Alternative auto...

NASA's Information Power Grid: Large Scale Distributed Computing and Data Management

NASA Technical Reports Server (NTRS)

Johnston, William E.; Vaziri, Arsi; Hinke, Tom; Tanner, Leigh Ann; Feiereisen, William J.; Thigpen, William; Tang, Harry (Technical Monitor)

2001-01-01

Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.

Requirements for fault-tolerant factoring on an atom-optics quantum computer.

PubMed

Devitt, Simon J; Stephens, Ashley M; Munro, William J; Nemoto, Kae

2013-01-01

Quantum information processing and its associated technologies have reached a pivotal stage in their development, with many experiments having established the basic building blocks. Moving forward, the challenge is to scale up to larger machines capable of performing computational tasks not possible today. This raises questions that need to be urgently addressed, such as what resources these machines will consume and how large will they be. Here we estimate the resources required to execute Shor's factoring algorithm on an atom-optics quantum computer architecture. We determine the runtime and size of the computer as a function of the problem size and physical error rate. Our results suggest that once the physical error rate is low enough to allow quantum error correction, optimization to reduce resources and increase performance will come mostly from integrating algorithms and circuits within the error correction environment, rather than from improving the physical hardware.

Computer Literacy Project. A General Orientation in Basic Computer Concepts and Applications.

ERIC Educational Resources Information Center

Murray, David R.

This paper proposes a two-part, basic computer literacy program for university faculty, staff, and students with no prior exposure to computers. The program described would introduce basic computer concepts and computing center service programs and resources; provide fundamental preparation for other computer courses; and orient faculty towards…

Increasing processor utilization during parallel computation rundown

NASA Technical Reports Server (NTRS)

Jones, W. H.

1986-01-01

Some parallel processing environments provide for asynchronous execution and completion of general purpose parallel computations from a single computational phase. When all the computations from such a phase are complete, a new parallel computational phase is begun. Depending upon the granularity of the parallel computations to be performed, there may be a shortage of available work as a particular computational phase draws to a close (computational rundown). This can result in the waste of computing resources and the delay of the overall problem. In many practical instances, strict sequential ordering of phases of parallel computation is not totally required. In such cases, the beginning of one phase can be correctly computed before the end of a previous phase is completed. This allows additional work to be generated somewhat earlier to keep computing resources busy during each computational rundown. The conditions under which this can occur are identified and the frequency of occurrence of such overlapping in an actual parallel Navier-Stokes code is reported. A language construct is suggested and possible control strategies for the management of such computational phase overlapping are discussed.

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.

Outlook Bright for Computers in Chemistry.

ERIC Educational Resources Information Center

Baum, Rudy M.

1981-01-01

Discusses the recent decision to close down the National Resource for Computation in Chemistry (NRCC), implications of that decision, and various alternatives in the field of computational chemistry. (CS)

Computer-aided resource planning and scheduling for radiological services

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.

1996-05-01

There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.

Key Lessons in Building "Data Commons": The Open Science Data Cloud Ecosystem

NASA Astrophysics Data System (ADS)

Patterson, M.; Grossman, R.; Heath, A.; Murphy, M.; Wells, W.

2015-12-01

Cloud computing technology has created a shift around data and data analysis by allowing researchers to push computation to data as opposed to having to pull data to an individual researcher's computer. Subsequently, cloud-based resources can provide unique opportunities to capture computing environments used both to access raw data in its original form and also to create analysis products which may be the source of data for tables and figures presented in research publications. Since 2008, the Open Cloud Consortium (OCC) has operated the Open Science Data Cloud (OSDC), which provides scientific researchers with computational resources for storing, sharing, and analyzing large (terabyte and petabyte-scale) scientific datasets. OSDC has provided compute and storage services to over 750 researchers in a wide variety of data intensive disciplines. Recently, internal users have logged about 2 million core hours each month. The OSDC also serves the research community by colocating these resources with access to nearly a petabyte of public scientific datasets in a variety of fields also accessible for download externally by the public. In our experience operating these resources, researchers are well served by "data commons," meaning cyberinfrastructure that colocates data archives, computing, and storage infrastructure and supports essential tools and services for working with scientific data. In addition to the OSDC public data commons, the OCC operates a data commons in collaboration with NASA and is developing a data commons for NOAA datasets. As cloud-based infrastructures for distributing and computing over data become more pervasive, we ask, "What does it mean to publish data in a data commons?" Here we present the OSDC perspective and discuss several services that are key in architecting data commons, including digital identifier services.

Unconditionally verifiable blind quantum computation

NASA Astrophysics Data System (ADS)

Fitzsimons, Joseph F.; Kashefi, Elham

2017-07-01

Blind quantum computing (BQC) allows a client to have a server carry out a quantum computation for them such that the client's input, output, and computation remain private. A desirable property for any BQC protocol is verification, whereby the client can verify with high probability whether the server has followed the instructions of the protocol or if there has been some deviation resulting in a corrupted output state. A verifiable BQC protocol can be viewed as an interactive proof system leading to consequences for complexity theory. We previously proposed [A. Broadbent, J. Fitzsimons, and E. Kashefi, in Proceedings of the 50th Annual Symposium on Foundations of Computer Science, Atlanta, 2009 (IEEE, Piscataway, 2009), p. 517] a universal and unconditionally secure BQC scheme where the client only needs to be able to prepare single qubits in separable states randomly chosen from a finite set and send them to the server, who has the balance of the required quantum computational resources. In this paper we extend that protocol with additional functionality allowing blind computational basis measurements, which we use to construct another verifiable BQC protocol based on a different class of resource states. We rigorously prove that the probability of failing to detect an incorrect output is exponentially small in a security parameter, while resource overhead remains polynomial in this parameter. This resource state allows entangling gates to be performed between arbitrary pairs of logical qubits with only constant overhead. This is a significant improvement on the original scheme, which required that all computations to be performed must first be put into a nearest-neighbor form, incurring linear overhead in the number of qubits. Such an improvement has important consequences for efficiency and fault-tolerance thresholds.

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.

Engineering and Computing Portal to Solve Environmental Problems

NASA Astrophysics Data System (ADS)

Gudov, A. M.; Zavozkin, S. Y.; Sotnikov, I. Y.

2018-01-01

This paper describes architecture and services of the Engineering and Computing Portal, which is considered to be a complex solution that provides access to high-performance computing resources, enables to carry out computational experiments, teach parallel technologies and solve computing tasks, including technogenic safety ones.

30 CFR 206.175 - How do I determine quantities and qualities of production for computing royalties?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false How do I determine quantities and qualities of production for computing royalties? 206.175 Section 206.175 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR MINERALS REVENUE MANAGEMENT PRODUCT VALUATION Indian Gas § 206.175 How do I...

Dynamic Transfers Of Tasks Among Computers

NASA Technical Reports Server (NTRS)

Liu, Howard T.; Silvester, John A.

1989-01-01

Allocation scheme gives jobs to idle computers. Ideal resource-sharing algorithm should have following characteristics: Dynamics, decentralized, and heterogeneous. Proposed enhanced receiver-initiated dynamic algorithm (ERIDA) for resource sharing fulfills all above criteria. Provides method balancing workload among hosts, resulting in improvement in response time and throughput performance of total system. Adjusts dynamically to traffic load of each station.

Computer Processing 10-20-30. Teacher's Manual. Senior High School Teacher Resource Manual.

ERIC Educational Resources Information Center

Fisher, Mel; Lautt, Ray

Designed to help teachers meet the program objectives for the computer processing curriculum for senior high schools in the province of Alberta, Canada, this resource manual includes the following sections: (1) program objectives; (2) a flowchart of curriculum modules; (3) suggestions for short- and long-range planning; (4) sample lesson plans;…

Y2K Resources for Public Libraries.

ERIC Educational Resources Information Center

Foster, Janet

1999-01-01

Presents information for public libraries on computer-related vulnerabilities as the century turns from 1999 to 2000. Highlights include: general Y2K information; the Y2K Bug and PCs; Y2K sites for librarians; Online Computer Library Center (OCLC) and USMARC; technological developments in cyberspace; and a list of Web sites and Y2K resources. (AEF)

The Development of an Individualized Instructional Program in Beginning College Mathematics Utilizing Computer Based Resource Units. Final Report.

ERIC Educational Resources Information Center

Rockhill, Theron D.

Reported is an attempt to develop and evaluate an individualized instructional program in pre-calculus college mathematics. Four computer based resource units were developed in the areas of set theory, relations and function, algebra, trigonometry, and analytic geometry. Objectives were determined by experienced calculus teachers, and…

Desktop supercomputer: what can it do?

NASA Astrophysics Data System (ADS)

Bogdanov, A.; Degtyarev, A.; Korkhov, V.

2017-12-01

The paper addresses the issues of solving complex problems that require using supercomputers or multiprocessor clusters available for most researchers nowadays. Efficient distribution of high performance computing resources according to actual application needs has been a major research topic since high-performance computing (HPC) technologies became widely introduced. At the same time, comfortable and transparent access to these resources was a key user requirement. In this paper we discuss approaches to build a virtual private supercomputer available at user's desktop: a virtual computing environment tailored specifically for a target user with a particular target application. We describe and evaluate possibilities to create the virtual supercomputer based on light-weight virtualization technologies, and analyze the efficiency of our approach compared to traditional methods of HPC resource management.

Impact of remote sensing upon the planning, management and development of water resources, appendix

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L.; Fowler, T. R.; Frech, S. L.

1975-01-01

Lists are presented of water resource agencies from the federal, state, Water Resources Research Institute, university, local, and private sectors. Information is provided on their water resource activities, computers, and models used. For Basic doc., see N75-25263.

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem. [Spacelab inventory procurement planning

NASA Technical Reports Server (NTRS)

Schlagheck, R. A.

1977-01-01

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

Water Resources Management and Hydrologic Design Under Uncertain Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Teegavarapu, R. S.

2008-05-01

The impact of climate change on hydrologic design and management of water resource systems could be one of the important challenges faced by future practicing hydrologists and water resources managers. Many water resources managers currently rely on the historical hydrological data and adaptive real-time operations without consideration of the impact of climate change on major inputs influencing the behavior of hydrologic systems and the operating rules. Issues such as risk, reliability and robustness of water resources systems under different climate change scenarios were addressed in the past. However, water resources management with the decision maker's preferences attached to climate change has never been dealt with. This presentation discusses issues related to impacts of climate change on water resources management and application of a soft-computing approach, fuzzy set theory, for climate-sensitive management of water resources systems. A real-life case study example is presented to illustrate the applicability of soft-computing approach for handling the decision maker's preferences in accepting or rejecting the magnitude and direction of climate change.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W.; Moritz, Robert L.

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W; Moritz, Robert L

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Making Cloud Computing Available For Researchers and Innovators (Invited)

NASA Astrophysics Data System (ADS)

Winsor, R.

2010-12-01

High Performance Computing (HPC) facilities exist in most academic institutions but are almost invariably over-subscribed. Access is allocated based on academic merit, the only practical method of assigning valuable finite compute resources. Cloud computing on the other hand, and particularly commercial clouds, draw flexibly on an almost limitless resource as long as the user has sufficient funds to pay the bill. How can the commercial cloud model be applied to scientific computing? Is there a case to be made for a publicly available research cloud and how would it be structured? This talk will explore these themes and describe how Cybera, a not-for-profit non-governmental organization in Alberta Canada, aims to leverage its high speed research and education network to provide cloud computing facilities for a much wider user base.

One-way quantum computing in superconducting circuits

NASA Astrophysics Data System (ADS)

Albarrán-Arriagada, F.; Alvarado Barrios, G.; Sanz, M.; Romero, G.; Lamata, L.; Retamal, J. C.; Solano, E.

2018-03-01

We propose a method for the implementation of one-way quantum computing in superconducting circuits. Measurement-based quantum computing is a universal quantum computation paradigm in which an initial cluster state provides the quantum resource, while the iteration of sequential measurements and local rotations encodes the quantum algorithm. Up to now, technical constraints have limited a scalable approach to this quantum computing alternative. The initial cluster state can be generated with available controlled-phase gates, while the quantum algorithm makes use of high-fidelity readout and coherent feedforward. With current technology, we estimate that quantum algorithms with above 20 qubits may be implemented in the path toward quantum supremacy. Moreover, we propose an alternative initial state with properties of maximal persistence and maximal connectedness, reducing the required resources of one-way quantum computing protocols.

Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm.

PubMed

Feng, Yen-Yi; Wu, I-Chin; Chen, Tzu-Li

2017-03-01

The number of emergency cases or emergency room visits rapidly increases annually, thus leading to an imbalance in supply and demand and to the long-term overcrowding of hospital emergency departments (EDs). However, current solutions to increase medical resources and improve the handling of patient needs are either impractical or infeasible in the Taiwanese environment. Therefore, EDs must optimize resource allocation given limited medical resources to minimize the average length of stay of patients and medical resource waste costs. This study constructs a multi-objective mathematical model for medical resource allocation in EDs in accordance with emergency flow or procedure. The proposed mathematical model is complex and difficult to solve because its performance value is stochastic; furthermore, the model considers both objectives simultaneously. Thus, this study develops a multi-objective simulation optimization algorithm by integrating a non-dominated sorting genetic algorithm II (NSGA II) with multi-objective computing budget allocation (MOCBA) to address the challenges of multi-objective medical resource allocation. NSGA II is used to investigate plausible solutions for medical resource allocation, and MOCBA identifies effective sets of feasible Pareto (non-dominated) medical resource allocation solutions in addition to effectively allocating simulation or computation budgets. The discrete event simulation model of ED flow is inspired by a Taiwan hospital case and is constructed to estimate the expected performance values of each medical allocation solution as obtained through NSGA II. Finally, computational experiments are performed to verify the effectiveness and performance of the integrated NSGA II and MOCBA method, as well as to derive non-dominated medical resource allocation solutions from the algorithms.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1996-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Probabilistic resource allocation system with self-adaptive capability

NASA Technical Reports Server (NTRS)

Yufik, Yan M. (Inventor)

1998-01-01

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

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

BNL ATLAS Grid Computing

ScienceCinema

Michael Ernst

2017-12-09

As the sole Tier-1 computing facility for ATLAS in the United States and the largest ATLAS computing center worldwide Brookhaven provides a large portion of the overall computing resources for U.S. collaborators and serves as the central hub for storing,

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.

PanDA: Exascale Federation of Resources for the ATLAS Experiment at the LHC

NASA Astrophysics Data System (ADS)

Barreiro Megino, Fernando; Caballero Bejar, Jose; De, Kaushik; Hover, John; Klimentov, Alexei; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Padolski, Siarhei; Panitkin, Sergey; Petrosyan, Artem; Wenaus, Torre

2016-02-01

After a scheduled maintenance and upgrade period, the world's largest and most powerful machine - the Large Hadron Collider(LHC) - is about to enter its second run at unprecedented energies. In order to exploit the scientific potential of the machine, the experiments at the LHC face computational challenges with enormous data volumes that need to be analysed by thousand of physics users and compared to simulated data. Given diverse funding constraints, the computational resources for the LHC have been deployed in a worldwide mesh of data centres, connected to each other through Grid technologies. The PanDA (Production and Distributed Analysis) system was developed in 2005 for the ATLAS experiment on top of this heterogeneous infrastructure to seamlessly integrate the computational resources and give the users the feeling of a unique system. Since its origins, PanDA has evolved together with upcoming computing paradigms in and outside HEP, such as changes in the networking model, Cloud Computing and HPC. It is currently running steadily up to 200 thousand simultaneous cores (limited by the available resources for ATLAS), up to two million aggregated jobs per day and processes over an exabyte of data per year. The success of PanDA in ATLAS is triggering the widespread adoption and testing by other experiments. In this contribution we will give an overview of the PanDA components and focus on the new features and upcoming challenges that are relevant to the next decade of distributed computing workload management using PanDA.

Ubiquitous Versus One-to-One

ERIC Educational Resources Information Center

McAnear, Anita

2006-01-01

When we planned the editorial calendar with the topic ubiquitous computing, we were thinking of ubiquitous computing as the one-to-one ratio of computers to students and teachers and 24/7 access to electronic resources. At the time, we were aware that ubiquitous computing in the computer science field had more to do with wearable computers. Our…

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…

Have computers, will travel: providing on-site library instruction in rural health facilities using a portable computer lab.

PubMed

Neilson, Christine J

2010-01-01

The Saskatchewan Health Information Resources Partnership (SHIRP) provides library instruction to Saskatchewan's health care practitioners and students on placement in health care facilities as part of its mission to provide province-wide access to evidence-based health library resources. A portable computer lab was assembled in 2007 to provide hands-on training in rural health facilities that do not have computer labs of their own. Aside from some minor inconveniences, the introduction and operation of the portable lab has gone smoothly. The lab has been well received by SHIRP patrons and continues to be an essential part of SHIRP outreach.

Impact of remote sensing upon the planning, management and development of water resources. Summary of computers and computer growth trends for hydrologic modeling and the input of ERTS image data processing load

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L., Jr.

1975-01-01

An analysis of current computer usage by major water resources users was made to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era. The analysis showns significant impact due to the utilization and processing of ERTS CCT's data.

The importance of employing computational resources for the automation of drug discovery.

PubMed

Rosales-Hernández, Martha Cecilia; Correa-Basurto, José

2015-03-01

The application of computational tools to drug discovery helps researchers to design and evaluate new drugs swiftly with a reduce economic resources. To discover new potential drugs, computational chemistry incorporates automatization for obtaining biological data such as adsorption, distribution, metabolism, excretion and toxicity (ADMET), as well as drug mechanisms of action. This editorial looks at examples of these computational tools, including docking, molecular dynamics simulation, virtual screening, quantum chemistry, quantitative structural activity relationship, principal component analysis and drug screening workflow systems. The authors then provide their perspectives on the importance of these techniques for drug discovery. Computational tools help researchers to design and discover new drugs for the treatment of several human diseases without side effects, thus allowing for the evaluation of millions of compounds with a reduced cost in both time and economic resources. The problem is that operating each program is difficult; one is required to use several programs and understand each of the properties being tested. In the future, it is possible that a single computer and software program will be capable of evaluating the complete properties (mechanisms of action and ADMET properties) of ligands. It is also possible that after submitting one target, this computer-software will be capable of suggesting potential compounds along with ways to synthesize them, and presenting biological models for testing.

HPC on Competitive Cloud Resources

NASA Astrophysics Data System (ADS)

Bientinesi, Paolo; Iakymchuk, Roman; Napper, Jeff

Computing as a utility has reached the mainstream. Scientists can now easily rent time on large commercial clusters that can be expanded and reduced on-demand in real-time. However, current commercial cloud computing performance falls short of systems specifically designed for scientific applications. Scientific computing needs are quite different from those of the web applications that have been the focus of cloud computing vendors. In this chapter we demonstrate through empirical evaluation the computational efficiency of high-performance numerical applications in a commercial cloud environment when resources are shared under high contention. Using the Linpack benchmark as a case study, we show that cache utilization becomes highly unpredictable and similarly affects computation time. For some problems, not only is it more efficient to underutilize resources, but the solution can be reached sooner in realtime (wall-time). We also show that the smallest, cheapest (64-bit) instance on the studied environment is the best for price to performance ration. In light of the high-contention we witness, we believe that alternative definitions of efficiency for commercial cloud environments should be introduced where strong performance guarantees do not exist. Concepts like average, expected performance and execution time, expected cost to completion, and variance measures--traditionally ignored in the high-performance computing context--now should complement or even substitute the standard definitions of efficiency.

A System Architecture for Efficient Transmission of Massive DNA Sequencing Data.

PubMed

Sağiroğlu, Mahmut Şamİl; Külekcİ, M Oğuzhan

2017-11-01

The DNA sequencing data analysis pipelines require significant computational resources. In that sense, cloud computing infrastructures appear as a natural choice for this processing. However, the first practical difficulty in reaching the cloud computing services is the transmission of the massive DNA sequencing data from where they are produced to where they will be processed. The daily practice here begins with compressing the data in FASTQ file format, and then sending these data via fast data transmission protocols. In this study, we address the weaknesses in that daily practice and present a new system architecture that incorporates the computational resources available on the client side while dynamically adapting itself to the available bandwidth. Our proposal considers the real-life scenarios, where the bandwidth of the connection between the parties may fluctuate, and also the computing power on the client side may be of any size ranging from moderate personal computers to powerful workstations. The proposed architecture aims at utilizing both the communication bandwidth and the computing resources for satisfying the ultimate goal of reaching the results as early as possible. We present a prototype implementation of the proposed architecture, and analyze several real-life cases, which provide useful insights for the sequencing centers, especially on deciding when to use a cloud service and in what conditions.

Body CT (CAT Scan)

MedlinePlus

... Resources Professions Site Index A-Z Computed Tomography (CT) - Body Computed tomography (CT) of the body uses ... of CT Scanning of the Body? What is CT Scanning of the Body? Computed tomography, more commonly ...

A data management system to enable urgent natural disaster computing

NASA Astrophysics Data System (ADS)

Leong, Siew Hoon; Kranzlmüller, Dieter; Frank, Anton

2014-05-01

Civil protection, in particular natural disaster management, is very important to most nations and civilians in the world. When disasters like flash floods, earthquakes and tsunamis are expected or have taken place, it is of utmost importance to make timely decisions for managing the affected areas and reduce casualties. Computer simulations can generate information and provide predictions to facilitate this decision making process. Getting the data to the required resources is a critical requirement to enable the timely computation of the predictions. An urgent data management system to support natural disaster computing is thus necessary to effectively carry out data activities within a stipulated deadline. Since the trigger of a natural disaster is usually unpredictable, it is not always possible to prepare required resources well in advance. As such, an urgent data management system for natural disaster computing has to be able to work with any type of resources. Additional requirements include the need to manage deadlines and huge volume of data, fault tolerance, reliable, flexibility to changes, ease of usage, etc. The proposed data management platform includes a service manager to provide a uniform and extensible interface for the supported data protocols, a configuration manager to check and retrieve configurations of available resources, a scheduler manager to ensure that the deadlines can be met, a fault tolerance manager to increase the reliability of the platform and a data manager to initiate and perform the data activities. These managers will enable the selection of the most appropriate resource, transfer protocol, etc. such that the hard deadline of an urgent computation can be met for a particular urgent activity, e.g. data staging or computation. We associated 2 types of deadlines [2] with an urgent computing system. Soft-hard deadline: Missing a soft-firm deadline will render the computation less useful resulting in a cost that can have severe consequences Hard deadline: Missing a hard deadline renders the computation useless and results in full catastrophic consequences. A prototype of this system has a REST-based service manager. The REST-based implementation provides a uniform interface that is easy to use. New and upcoming file transfer protocols can easily be extended and accessed via the service manager. The service manager interacts with the other four managers to coordinate the data activities so that the fundamental natural disaster urgent computing requirement, i.e. deadline, can be fulfilled in a reliable manner. A data activity can include data storing, data archiving and data storing. Reliability is ensured by the choice of a network of managers organisation model[1] the configuration manager and the fault tolerance manager. With this proposed design, an easy to use, resource-independent data management system that can support and fulfill the computation of a natural disaster prediction within stipulated deadlines can thus be realised. References [1] H. G. Hegering, S. Abeck, and B. Neumair, Integrated management of networked systems - concepts, architectures, and their operational application, Morgan Kaufmann Publishers, 340 Pine Stret, Sixth Floor, San Francisco, CA 94104-3205, USA, 1999. [2] H. Kopetz, Real-time systems design principles for distributed embedded applications, second edition, Springer, LLC, 233 Spring Street, New York, NY 10013, USA, 2011. [3] S. H. Leong, A. Frank, and D. Kranzlmu¨ ller, Leveraging e-infrastructures for urgent computing, Procedia Computer Science 18 (2013), no. 0, 2177 - 2186, 2013 International Conference on Computational Science. [4] N. Trebon, Enabling urgent computing within the existing distributed computing infrastructure, Ph.D. thesis, University of Chicago, August 2011, http://people.cs.uchicago.edu/~ntrebon/docs/dissertation.pdf.

Simple Linux Utility for Resource Management

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

Jette, M.

2009-09-09

SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allciated nodes. Finally, it arbitrates conflicting requests for resouces by managing a queue of pending work.

Opportunities and Challenges of Cloud Computing to Improve Health Care Services

PubMed Central

2011-01-01

Cloud computing is a new way of delivering computing resources and services. Many managers and experts believe that it can improve health care services, benefit health care research, and change the face of health information technology. However, as with any innovation, cloud computing should be rigorously evaluated before its widespread adoption. This paper discusses the concept and its current place in health care, and uses 4 aspects (management, technology, security, and legal) to evaluate the opportunities and challenges of this computing model. Strategic planning that could be used by a health organization to determine its direction, strategy, and resource allocation when it has decided to migrate from traditional to cloud-based health services is also discussed. PMID:21937354

Some key considerations in evolving a computer system and software engineering support environment for the space station program

NASA Technical Reports Server (NTRS)

Mckay, C. W.; Bown, R. L.

1985-01-01

The space station data management system involves networks of computing resources that must work cooperatively and reliably over an indefinite life span. This program requires a long schedule of modular growth and an even longer period of maintenance and operation. The development and operation of space station computing resources will involve a spectrum of systems and software life cycle activities distributed across a variety of hosts, an integration, verification, and validation host with test bed, and distributed targets. The requirement for the early establishment and use of an apporopriate Computer Systems and Software Engineering Support Environment is identified. This environment will support the Research and Development Productivity challenges presented by the space station computing system.

A security mechanism based on evolutionary game in fog computing.

PubMed

Sun, Yan; Lin, Fuhong; Zhang, Nan

2018-02-01

Fog computing is a distributed computing paradigm at the edge of the network and requires cooperation of users and sharing of resources. When users in fog computing open their resources, their devices are easily intercepted and attacked because they are accessed through wireless network and present an extensive geographical distribution. In this study, a credible third party was introduced to supervise the behavior of users and protect the security of user cooperation. A fog computing security mechanism based on human nervous system is proposed, and the strategy for a stable system evolution is calculated. The MATLAB simulation results show that the proposed mechanism can reduce the number of attack behaviors effectively and stimulate users to cooperate in application tasks positively.

ATLAS@Home: Harnessing Volunteer Computing for HEP

NASA Astrophysics Data System (ADS)

Adam-Bourdarios, C.; Cameron, D.; Filipčič, A.; Lancon, E.; Wu, W.; ATLAS Collaboration

2015-12-01

A recent common theme among HEP computing is exploitation of opportunistic resources in order to provide the maximum statistics possible for Monte Carlo simulation. Volunteer computing has been used over the last few years in many other scientific fields and by CERN itself to run simulations of the LHC beams. The ATLAS@Home project was started to allow volunteers to run simulations of collisions in the ATLAS detector. So far many thousands of members of the public have signed up to contribute their spare CPU cycles for ATLAS, and there is potential for volunteer computing to provide a significant fraction of ATLAS computing resources. Here we describe the design of the project, the lessons learned so far and the future plans.

Network gateway security method for enterprise Grid: a literature review

NASA Astrophysics Data System (ADS)

Sujarwo, A.; Tan, J.

2017-03-01

The computational Grid has brought big computational resources closer to scientists. It enables people to do a large computational job anytime and anywhere without any physical border anymore. However, the massive and spread of computer participants either as user or computational provider arise problems in security. The challenge is on how the security system, especially the one which filters data in the gateway could works in flexibility depends on the registered Grid participants. This paper surveys what people have done to approach this challenge, in order to find the better and new method for enterprise Grid. The findings of this paper is the dynamically controlled enterprise firewall to secure the Grid resources from unwanted connections with a new firewall controlling method and components.

Opportunistic Computing with Lobster: Lessons Learned from Scaling up to 25k Non-Dedicated Cores

NASA Astrophysics Data System (ADS)

Wolf, Matthias; Woodard, Anna; Li, Wenzhao; Hurtado Anampa, Kenyi; Yannakopoulos, Anna; Tovar, Benjamin; Donnelly, Patrick; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2017-10-01

We previously described Lobster, a workflow management tool for exploiting volatile opportunistic computing resources for computation in HEP. We will discuss the various challenges that have been encountered while scaling up the simultaneous CPU core utilization and the software improvements required to overcome these challenges. Categories: Workflows can now be divided into categories based on their required system resources. This allows the batch queueing system to optimize assignment of tasks to nodes with the appropriate capabilities. Within each category, limits can be specified for the number of running jobs to regulate the utilization of communication bandwidth. System resource specifications for a task category can now be modified while a project is running, avoiding the need to restart the project if resource requirements differ from the initial estimates. Lobster now implements time limits on each task category to voluntarily terminate tasks. This allows partially completed work to be recovered. Workflow dependency specification: One workflow often requires data from other workflows as input. Rather than waiting for earlier workflows to be completed before beginning later ones, Lobster now allows dependent tasks to begin as soon as sufficient input data has accumulated. Resource monitoring: Lobster utilizes a new capability in Work Queue to monitor the system resources each task requires in order to identify bottlenecks and optimally assign tasks. The capability of the Lobster opportunistic workflow management system for HEP computation has been significantly increased. We have demonstrated efficient utilization of 25 000 non-dedicated cores and achieved a data input rate of 30 Gb/s and an output rate of 500GB/h. This has required new capabilities in task categorization, workflow dependency specification, and resource monitoring.

Rational use of cognitive resources: levels of analysis between the computational and the algorithmic.

PubMed

Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D

2015-04-01

Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.

Exploiting volatile opportunistic computing resources with Lobster

NASA Astrophysics Data System (ADS)

Woodard, Anna; Wolf, Matthias; Mueller, Charles; Tovar, Ben; Donnelly, Patrick; Hurtado Anampa, Kenyi; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2015-12-01

Analysis of high energy physics experiments using the Compact Muon Solenoid (CMS) at the Large Hadron Collider (LHC) can be limited by availability of computing resources. As a joint effort involving computer scientists and CMS physicists at Notre Dame, we have developed an opportunistic workflow management tool, Lobster, to harvest available cycles from university campus computing pools. Lobster consists of a management server, file server, and worker processes which can be submitted to any available computing resource without requiring root access. Lobster makes use of the Work Queue system to perform task management, while the CMS specific software environment is provided via CVMFS and Parrot. Data is handled via Chirp and Hadoop for local data storage and XrootD for access to the CMS wide-area data federation. An extensive set of monitoring and diagnostic tools have been developed to facilitate system optimisation. We have tested Lobster using the 20 000-core cluster at Notre Dame, achieving approximately 8-10k tasks running simultaneously, sustaining approximately 9 Gbit/s of input data and 340 Mbit/s of output data.

Interoperating Cloud-based Virtual Farms

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Colamaria, F.; Colella, D.; Casula, E.; Elia, D.; Franco, A.; Lusso, S.; Luparello, G.; Masera, M.; Miniello, G.; Mura, D.; Piano, S.; Vallero, S.; Venaruzzo, M.; Vino, G.

2015-12-01

The present work aims at optimizing the use of computing resources available at the grid Italian Tier-2 sites of the ALICE experiment at CERN LHC by making them accessible to interactive distributed analysis, thanks to modern solutions based on cloud computing. The scalability and elasticity of the computing resources via dynamic (“on-demand”) provisioning is essentially limited by the size of the computing site, reaching the theoretical optimum only in the asymptotic case of infinite resources. The main challenge of the project is to overcome this limitation by federating different sites through a distributed cloud facility. Storage capacities of the participating sites are seen as a single federated storage area, preventing the need of mirroring data across them: high data access efficiency is guaranteed by location-aware analysis software and storage interfaces, in a transparent way from an end-user perspective. Moreover, the interactive analysis on the federated cloud reduces the execution time with respect to grid batch jobs. The tests of the investigated solutions for both cloud computing and distributed storage on wide area network will be presented.

Distributed storage and cloud computing: a test case

NASA Astrophysics Data System (ADS)

Piano, S.; Delia Ricca, G.

2014-06-01

Since 2003 the computing farm hosted by the INFN Tier3 facility in Trieste supports the activities of many scientific communities. Hundreds of jobs from 45 different VOs, including those of the LHC experiments, are processed simultaneously. Given that normally the requirements of the different computational communities are not synchronized, the probability that at any given time the resources owned by one of the participants are not fully utilized is quite high. A balanced compensation should in principle allocate the free resources to other users, but there are limits to this mechanism. In fact, the Trieste site may not hold the amount of data needed to attract enough analysis jobs, and even in that case there could be a lack of bandwidth for their access. The Trieste ALICE and CMS computing groups, in collaboration with other Italian groups, aim to overcome the limitations of existing solutions using two approaches: sharing the data among all the participants taking full advantage of GARR-X wide area networks (10 GB/s) and integrating the resources dedicated to batch analysis with the ones reserved for dynamic interactive analysis, through modern solutions as cloud computing.

An Adaptive Priority Tuning System for Optimized Local CPU Scheduling using BOINC Clients

NASA Astrophysics Data System (ADS)

Mnaouer, Adel B.; Ragoonath, Colin

2010-11-01

Volunteer Computing (VC) is a Distributed Computing model which utilizes idle CPU cycles from computing resources donated by volunteers who are connected through the Internet to form a very large-scale, loosely coupled High Performance Computing environment. Distributed Volunteer Computing environments such as the BOINC framework is concerned mainly with the efficient scheduling of the available resources to the applications which require them. The BOINC framework thus contains a number of scheduling policies/algorithms both on the server-side and on the client which work together to maximize the available resources and to provide a degree of QoS in an environment which is highly volatile. This paper focuses on the BOINC client and introduces an adaptive priority tuning client side middleware application which improves the execution times of Work Units (WUs) while maintaining an acceptable Maximum Response Time (MRT) for the end user. We have conducted extensive experimentation of the proposed system and the results show clear speedup of BOINC applications using our optimized middleware as opposed to running using the original BOINC client.

Computer Literacy and Societal Impact of Computers: Education and Manpower.

ERIC Educational Resources Information Center

Hamblen, John W.

The use of computers in education and general society is continually expanding, but the growing need for highly educated computer technologists will continue unless universities take major steps toward the reallocation of their resources in favor of the burgeoning computer science departments, and government and industry provide a significant…

Cloud Computing. Technology Briefing. Number 1

ERIC Educational Resources Information Center

Alberta Education, 2013

2013-01-01

Cloud computing is Internet-based computing in which shared resources, software and information are delivered as a service that computers or mobile devices can access on demand. Cloud computing is already used extensively in education. Free or low-cost cloud-based services are used daily by learners and educators to support learning, social…

City University of New York--Availability of Student Computer Resources. Report.

ERIC Educational Resources Information Center

McCall, H. Carl

This audit reports on the availability of computer resources at the City University of New York's (CUNY) senior colleges. CUNY is the largest urban and the third largest public university system in the United States. Of the 19 CUNY campuses located throughout the five boroughs, 11 are senior colleges offering four-year degrees. For the fall 2001…

Relate@IU>>>Share@IU: A New and Different Computer-Based Communications Paradigm.

ERIC Educational Resources Information Center

Frick, Theodore W.; Roberto, Joseph; Korkmaz, Ali; Oh, Jeong-En; Twal, Riad

The purpose of this study was to examine problems with the current computer-based electronic communication systems and to initially test and revise a new and different paradigm for e-collaboration, Relate@IU. Understanding the concept of sending links to resources, rather than sending the resource itself, is at the core of how Relate@IU differs…

Benefits and Challenges in Using Computers and the Internet with Adult English Learners.

ERIC Educational Resources Information Center

Terrill, Lynda

Although resources and training vary from program to program, adult English as a Second or Other Language (ESOL) teachers and English learners across the country are integrating computers and Internet use with ESOL instruction. This can be seen in the growing number of ESOL resources available on the World Wide Web. There are very good reasons for…

Computer User's Guide to the Protection of Information Resources. NIST Special Publication 500-171.

ERIC Educational Resources Information Center

Helsing, Cheryl; And Others

Computers have changed the way information resources are handled. Large amounts of information are stored in one central place and can be accessed from remote locations. Users have a personal responsibility for the security of the system and the data stored in it. This document outlines the user's responsibilities and provides security and control…

Production experience with the ATLAS Event Service

NASA Astrophysics Data System (ADS)

Benjamin, D.; Calafiura, P.; Childers, T.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Compute Engine, and a growing number of HPC platforms. After briefly reviewing the concept and the architecture of the Event Service, we will report the status and experience gained in AES commissioning and production operations on supercomputers, and our plans for extending ES application beyond Geant4 simulation to other workflows, such as reconstruction and data analysis.

Building a Digital Library from the Ground Up: an Examination of Emergent Information Resources in the Machine Learning Community

NASA Astrophysics Data System (ADS)

Cunningham, Sally Jo

The current crop of digital libraries for the computing community are strongly grounded in the conventional library paradigm: they provide indexes to support searching of collections of research papers. As such, these digital libraries are relatively impoverished; the present computing digital libraries omit many of the documents and resources that are currently available to computing researchers, and offer few browsing structures. These computing digital libraries were built 'top down': the resources and collection contents are forced to fit an existing digital library architecture. A 'bottom up' approach to digital library development would begin with an investigation of a community's information needs and available documents, and then design a library to organize those documents in such a way as to fulfill the community's needs. The 'home grown', informal information resources developed by and for the machine learning community are examined as a case study, to determine the types of information and document organizations 'native' to this group of researchers. The insights gained in this type of case study can be used to inform construction of a digital library tailored to this community.

RAID v2.0: an updated resource of RNA-associated interactions across organisms

PubMed Central

Yi, Ying; Zhao, Yue; Li, Chunhua; Zhang, Lin; Huang, Huiying; Li, Yana; Liu, Lanlan; Hou, Ping; Cui, Tianyu; Tan, Puwen; Hu, Yongfei; Zhang, Ting; Huang, Yan; Li, Xiaobo; Yu, Jia; Wang, Dong

2017-01-01

With the development of biotechnologies and computational prediction algorithms, the number of experimental and computational prediction RNA-associated interactions has grown rapidly in recent years. However, diverse RNA-associated interactions are scattered over a wide variety of resources and organisms, whereas a fully comprehensive view of diverse RNA-associated interactions is still not available for any species. Hence, we have updated the RAID database to version 2.0 (RAID v2.0, www.rna-society.org/raid/) by integrating experimental and computational prediction interactions from manually reading literature and other database resources under one common framework. The new developments in RAID v2.0 include (i) over 850-fold RNA-associated interactions, an enhancement compared to the previous version; (ii) numerous resources integrated with experimental or computational prediction evidence for each RNA-associated interaction; (iii) a reliability assessment for each RNA-associated interaction based on an integrative confidence score; and (iv) an increase of species coverage to 60. Consequently, RAID v2.0 recruits more than 5.27 million RNA-associated interactions, including more than 4 million RNA–RNA interactions and more than 1.2 million RNA–protein interactions, referring to nearly 130 000 RNA/protein symbols across 60 species. PMID:27899615

Managing Saginaw Bay nutrient loading by surrounding watersheds through near real time hydrologic resource sheds

EPA Science Inventory

We can quantify source areas contributing material to a location during various time periods as resource sheds. Various kinds of resource sheds and their source material distributions are defined. For watershed hydrology, we compute resource sheds and their source material distri...

18 CFR 704.39 - Discount rate.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 18 Conservation of Power and Water Resources 2 2013-04-01 2012-04-01 true Discount rate. 704.39 Section 704.39 Conservation of Power and Water Resources WATER RESOURCES COUNCIL PLAN FORMULATION... the Water Resources Council of the rate thus computed. (c) Subject to the provisions of paragraphs (d...

18 CFR 704.39 - Discount rate.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 18 Conservation of Power and Water Resources 2 2014-04-01 2014-04-01 false Discount rate. 704.39 Section 704.39 Conservation of Power and Water Resources WATER RESOURCES COUNCIL PLAN FORMULATION... the Water Resources Council of the rate thus computed. (c) Subject to the provisions of paragraphs (d...

18 CFR 704.39 - Discount rate.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 2 2011-04-01 2011-04-01 false Discount rate. 704.39 Section 704.39 Conservation of Power and Water Resources WATER RESOURCES COUNCIL PLAN FORMULATION... the Water Resources Council of the rate thus computed. (c) Subject to the provisions of paragraphs (d...

18 CFR 704.39 - Discount rate.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Discount rate. 704.39 Section 704.39 Conservation of Power and Water Resources WATER RESOURCES COUNCIL PLAN FORMULATION... the Water Resources Council of the rate thus computed. (c) Subject to the provisions of paragraphs (d...

18 CFR 704.39 - Discount rate.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 18 Conservation of Power and Water Resources 2 2012-04-01 2012-04-01 false Discount rate. 704.39 Section 704.39 Conservation of Power and Water Resources WATER RESOURCES COUNCIL PLAN FORMULATION... the Water Resources Council of the rate thus computed. (c) Subject to the provisions of paragraphs (d...

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

Gross, D.; Eisert, J.; Schuch, N.

We introduce schemes for quantum computing based on local measurements on entangled resource states. This work elaborates on the framework established in Gross and Eisert [Phys. Rev. Lett. 98, 220503 (2007); quant-ph/0609149]. Our method makes use of tools from many-body physics--matrix product states, finitely correlated states, or projected entangled pairs states--to show how measurements on entangled states can be viewed as processing quantum information. This work hence constitutes an instance where a quantum information problem--how to realize quantum computation--was approached using tools from many-body theory and not vice versa. We give a more detailed description of the setting and presentmore » a large number of examples. We find computational schemes, which differ from the original one-way computer, for example, in the way the randomness of measurement outcomes is handled. Also, schemes are presented where the logical qubits are no longer strictly localized on the resource state. Notably, we find a great flexibility in the properties of the universal resource states: They may, for example, exhibit nonvanishing long-range correlation functions or be locally arbitrarily close to a pure state. We discuss variants of Kitaev's toric code states as universal resources, and contrast this with situations where they can be efficiently classically simulated. This framework opens up a way of thinking of tailoring resource states to specific physical systems, such as cold atoms in optical lattices or linear optical systems.« less

Formation of Virtual Organizations in Grids: A Game-Theoretic Approach

NASA Astrophysics Data System (ADS)

Carroll, Thomas E.; Grosu, Daniel

The execution of large scale grid applications requires the use of several computational resources owned by various Grid Service Providers (GSPs). GSPs must form Virtual Organizations (VOs) to be able to provide the composite resource to these applications. We consider grids as self-organizing systems composed of autonomous, self-interested GSPs that will organize themselves into VOs with every GSP having the objective of maximizing its profit. We formulate the resource composition among GSPs as a coalition formation problem and propose a game-theoretic framework based on cooperation structures to model it. Using this framework, we design a resource management system that supports the VO formation among GSPs in a grid computing system.

GANGA: A tool for computational-task management and easy access to Grid resources

NASA Astrophysics Data System (ADS)

Mościcki, J. T.; Brochu, F.; Ebke, J.; Egede, U.; Elmsheuser, J.; Harrison, K.; Jones, R. W. L.; Lee, H. C.; Liko, D.; Maier, A.; Muraru, A.; Patrick, G. N.; Pajchel, K.; Reece, W.; Samset, B. H.; Slater, M. W.; Soroko, A.; Tan, C. L.; van der Ster, D. C.; Williams, M.

2009-11-01

In this paper, we present the computational task-management tool GANGA, which allows for the specification, submission, bookkeeping and post-processing of computational tasks on a wide set of distributed resources. GANGA has been developed to solve a problem increasingly common in scientific projects, which is that researchers must regularly switch between different processing systems, each with its own command set, to complete their computational tasks. GANGA provides a homogeneous environment for processing data on heterogeneous resources. We give examples from High Energy Physics, demonstrating how an analysis can be developed on a local system and then transparently moved to a Grid system for processing of all available data. GANGA has an API that can be used via an interactive interface, in scripts, or through a GUI. Specific knowledge about types of tasks or computational resources is provided at run-time through a plugin system, making new developments easy to integrate. We give an overview of the GANGA architecture, give examples of current use, and demonstrate how GANGA can be used in many different areas of science. Catalogue identifier: AEEN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEN_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPL No. of lines in distributed program, including test data, etc.: 224 590 No. of bytes in distributed program, including test data, etc.: 14 365 315 Distribution format: tar.gz Programming language: Python Computer: personal computers, laptops Operating system: Linux/Unix RAM: 1 MB Classification: 6.2, 6.5 Nature of problem: Management of computational tasks for scientific applications on heterogenous distributed systems, including local, batch farms, opportunistic clusters and Grids. Solution method: High-level job management interface, including command line, scripting and GUI components. Restrictions: Access to the distributed resources depends on the installed, 3rd party software such as batch system client or Grid user interface.

Drug information resources used by nurse practitioners and collaborating physicians at the point of care in Nova Scotia, Canada: a survey and review of the literature

PubMed Central

Murphy, Andrea L; Fleming, Mark; Martin-Misener, Ruth; Sketris, Ingrid S; MacCara, Mary; Gass, David

2006-01-01

Background Keeping current with drug therapy information is challenging for health care practitioners. Technologies are often implemented to facilitate access to current and credible drug information sources. In the Canadian province of Nova Scotia, legislation was passed in 2002 to allow nurse practitioners (NPs) to practice collaboratively with physician partners. The purpose of this study was to determine the current utilization patterns of information technologies by these groups of practitioners. Methods Nurse practitioners and their collaborating physician partners in Nova Scotia were sent a survey in February 2005 to determine the frequency of use, usefulness, accessibility, credibility, and current/timeliness of personal digital assistant (PDA), computer, and print drug information resources. Two surveys were developed (one for PDA users and one for computer users) and revised based on a literature search, stakeholder consultation, and pilot-testing results. A second distribution to nonresponders occurred two weeks following the first. Data were entered and analysed with SPSS. Results Twenty-seven (14 NPs and 13 physicians) of 36 (75%) recipients responded. 22% (6) returned personal digital assistant (PDA) surveys. Respondents reported print, health professionals, and online/electronic resources as the most to least preferred means to access drug information, respectively. 37% and 35% of respondents reported using "both print and electronic but print more than electronic" and "print only", respectively, to search monograph-related drug information queries whereas 4% reported using "PDA only". Analysis of respondent ratings for all resources in the categories print, health professionals and other, and online/electronic resources, indicated that the Compendium of Pharmaceuticals and Specialties and pharmacists ranked highly for frequency of use, usefulness, accessibility, credibility, and current/timeliness by both groups of practitioners. Respondents' preferences and resource ratings were consistent with self-reported methods for conducting drug information queries. Few differences existed between NP and physician rankings of resources. Conclusion The use of computers and PDAs remains limited, which is also consistent with preferred and frequent use of print resources. Education for these practitioners regarding available electronic drug information resources may facilitate future computer and PDA use. Further research is needed to determine methods to increase computer and PDA use and whether these technologies affect prescribing and patient outcomes. PMID:16822323

Cross stratum resources protection in fog-computing-based radio over fiber networks for 5G services

NASA Astrophysics Data System (ADS)

Guo, Shaoyong; Shao, Sujie; Wang, Yao; Yang, Hui

2017-09-01

In order to meet the requirement of internet of things (IoT) and 5G, the cloud radio access network is a paradigm which converges all base stations computational resources into a cloud baseband unit (BBU) pool, while the distributed radio frequency signals are collected by remote radio head (RRH). A precondition for centralized processing in the BBU pool is an interconnection fronthaul network with high capacity and low delay. However, it has become more complex and frequent in the interaction between RRH and BBU and resource scheduling among BBUs in cloud. Cloud radio over fiber network has been proposed in our previous work already. In order to overcome the complexity and latency, in this paper, we first present a novel cross stratum resources protection (CSRP) architecture in fog-computing-based radio over fiber networks (F-RoFN) for 5G services. Additionally, a cross stratum protection (CSP) scheme considering the network survivability is introduced in the proposed architecture. The CSRP with CSP scheme can effectively pull the remote processing resource locally to implement the cooperative radio resource management, enhance the responsiveness and resilience to the dynamic end-to-end 5G service demands, and globally optimize optical network, wireless and fog resources. The feasibility and efficiency of the proposed architecture with CSP scheme are verified on our software defined networking testbed in terms of service latency, transmission success rate, resource occupation rate and blocking probability.

ATLAS user analysis on private cloud resources at GoeGrid

NASA Astrophysics Data System (ADS)

Glaser, F.; Nadal Serrano, J.; Grabowski, J.; Quadt, A.

2015-12-01

User analysis job demands can exceed available computing resources, especially before major conferences. ATLAS physics results can potentially be slowed down due to the lack of resources. For these reasons, cloud research and development activities are now included in the skeleton of the ATLAS computing model, which has been extended by using resources from commercial and private cloud providers to satisfy the demands. However, most of these activities are focused on Monte-Carlo production jobs, extending the resources at Tier-2. To evaluate the suitability of the cloud-computing model for user analysis jobs, we developed a framework to launch an ATLAS user analysis cluster in a cloud infrastructure on demand and evaluated two solutions. The first solution is entirely integrated in the Grid infrastructure by using the same mechanism, which is already in use at Tier-2: A designated Panda-Queue is monitored and additional worker nodes are launched in a cloud environment and assigned to a corresponding HTCondor queue according to the demand. Thereby, the use of cloud resources is completely transparent to the user. However, using this approach, submitted user analysis jobs can still suffer from a certain delay introduced by waiting time in the queue and the deployed infrastructure lacks customizability. Therefore, our second solution offers the possibility to easily deploy a totally private, customizable analysis cluster on private cloud resources belonging to the university.

Volunteer Clouds and Citizen Cyberscience for LHC Physics

NASA Astrophysics Data System (ADS)

Aguado Sanchez, Carlos; Blomer, Jakob; Buncic, Predrag; Chen, Gang; Ellis, John; Garcia Quintas, David; Harutyunyan, Artem; Grey, Francois; Lombrana Gonzalez, Daniel; Marquina, Miguel; Mato, Pere; Rantala, Jarno; Schulz, Holger; Segal, Ben; Sharma, Archana; Skands, Peter; Weir, David; Wu, Jie; Wu, Wenjing; Yadav, Rohit

2011-12-01

Computing for the LHC, and for HEP more generally, is traditionally viewed as requiring specialized infrastructure and software environments, and therefore not compatible with the recent trend in "volunteer computing", where volunteers supply free processing time on ordinary PCs and laptops via standard Internet connections. In this paper, we demonstrate that with the use of virtual machine technology, at least some standard LHC computing tasks can be tackled with volunteer computing resources. Specifically, by presenting volunteer computing resources to HEP scientists as a "volunteer cloud", essentially identical to a Grid or dedicated cluster from a job submission perspective, LHC simulations can be processed effectively. This article outlines both the technical steps required for such a solution and the implications for LHC computing as well as for LHC public outreach and for participation by scientists from developing regions in LHC research.

Reprocessing Multiyear GPS Data from Continuously Operating Reference Stations on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Yoon, S.

2016-12-01

To define geodetic reference frame using GPS data collected by Continuously Operating Reference Stations (CORS) network, historical GPS data needs to be reprocessed regularly. Reprocessing GPS data collected by upto 2000 CORS sites for the last two decades requires a lot of computational resource. At National Geodetic Survey (NGS), there has been one completed reprocessing in 2011, and currently, the second reprocessing is undergoing. For the first reprocessing effort, in-house computing resource was utilized. In the current second reprocessing effort, outsourced cloud computing platform is being utilized. In this presentation, the outline of data processing strategy at NGS is described as well as the effort to parallelize the data processing procedure in order to maximize the benefit of the cloud computing. The time and cost savings realized by utilizing cloud computing approach will also be discussed.

Cyber-workstation for computational neuroscience.

PubMed

Digiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C; Fortes, Jose; Sanchez, Justin C

2010-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

PubMed

Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

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.

Cyber-Workstation for Computational Neuroscience

PubMed Central

DiGiovanna, Jack; Rattanatamrong, Prapaporn; Zhao, Ming; Mahmoudi, Babak; Hermer, Linda; Figueiredo, Renato; Principe, Jose C.; Fortes, Jose; Sanchez, Justin C.

2009-01-01

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurophysiology laboratory with scalable computing resources to enable more sophisticated computational neuroscience investigation. The architecture designed here allows scientists to develop new models and integrate them with existing models (e.g. recursive least-squares regressor) by specifying appropriate connections in a block-diagram. Then, adaptive middleware transparently implements these user specifications using the full power of remote grid-computing hardware. In effect, the middleware deploys an on-demand and flexible neuroscience research test-bed to provide the neurophysiology laboratory extensive computational power from an outside source. The CW consolidates distributed software and hardware resources to support time-critical and/or resource-demanding computing during data collection from behaving animals. This power and flexibility is important as experimental and theoretical neuroscience evolves based on insights gained from data-intensive experiments, new technologies and engineering methodologies. This paper describes briefly the computational infrastructure and its most relevant components. Each component is discussed within a systematic process of setting up an in vivo, neuroscience experiment. Furthermore, a co-adaptive brain machine interface is implemented on the CW to illustrate how this integrated computational and experimental platform can be used to study systems neurophysiology and learning in a behavior task. We believe this implementation is also the first remote execution and adaptation of a brain-machine interface. PMID:20126436

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PubMed Central

Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

CERN Computing in Commercial Clouds

NASA Astrophysics Data System (ADS)

Cordeiro, C.; Field, L.; Garrido Bear, B.; Giordano, D.; Jones, B.; Keeble, O.; Manzi, A.; Martelli, E.; McCance, G.; Moreno-García, D.; Traylen, S.

2017-10-01

By the end of 2016 more than 10 Million core-hours of computing resources have been delivered by several commercial cloud providers to the four LHC experiments to run their production workloads, from simulation to full chain processing. In this paper we describe the experience gained at CERN in procuring and exploiting commercial cloud resources for the computing needs of the LHC experiments. The mechanisms used for provisioning, monitoring, accounting, alarming and benchmarking will be discussed, as well as the involvement of the LHC collaborations in terms of managing the workflows of the experiments within a multicloud environment.

The Lilongwe Central Hospital Patient Management Information System: A Success in Computer-Based Order Entry Where One Might Least Expect It

PubMed Central

GP, Douglas; RA, Deula; SE, Connor

2003-01-01

Computer-based order entry is a powerful tool for enhancing patient care. A pilot project in the pediatric department of the Lilongwe Central Hospital (LCH) in Malawi, Africa has demonstrated that computer-based order entry (COE): 1) can be successfully deployed and adopted in resource-poor settings, 2) can be built, deployed and sustained at relatively low cost and with local resources, and 3) has a greater potential to improve patient care in developing than in developed countries. PMID:14728338

A Queue Simulation Tool for a High Performance Scientific Computing Center

NASA Technical Reports Server (NTRS)

Spear, Carrie; McGalliard, James

2007-01-01

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

2012-12-01

ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

ACToR – Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

ACToR (Aggregated Computational Toxicology Resource) is a collection of databases collated or developed by the US EPA National Center for Computational Toxicology (NCCT). More than 200 sources of publicly available data on environmental chemicals have been brought together and made searchable by chemical name and other identifiers, and by chemical structure. Data includes chemical structure, physico-chemical values, in vitro assay data and in vivo toxicology data. Chemicals include, but are not limited to, high and medium production volume industrial chemicals, pesticides (active and inert ingredients), and potential ground and drinking water contaminants.

Common Accounting System for Monitoring the ATLAS Distributed Computing Resources

NASA Astrophysics Data System (ADS)

Karavakis, E.; Andreeva, J.; Campana, S.; Gayazov, S.; Jezequel, S.; Saiz, P.; Sargsyan, L.; Schovancova, J.; Ueda, I.; Atlas Collaboration

2014-06-01

This paper covers in detail a variety of accounting tools used to monitor the utilisation of the available computational and storage resources within the ATLAS Distributed Computing during the first three years of Large Hadron Collider data taking. The Experiment Dashboard provides a set of common accounting tools that combine monitoring information originating from many different information sources; either generic or ATLAS specific. This set of tools provides quality and scalable solutions that are flexible enough to support the constantly evolving requirements of the ATLAS user community.

Computer Aided Manufacturing.

ERIC Educational Resources Information Center

Insolia, Gerard

This document contains course outlines in computer-aided manufacturing developed for a business-industry technology resource center for firms in eastern Pennsylvania by Northampton Community College. The four units of the course cover the following: (1) introduction to computer-assisted design (CAD)/computer-assisted manufacturing (CAM); (2) CAM…

Scaling up a CMS tier-3 site with campus resources and a 100 Gb/s network connection: what could go wrong?

NASA Astrophysics Data System (ADS)

Wolf, Matthias; Woodard, Anna; Li, Wenzhao; Hurtado Anampa, Kenyi; Tovar, Benjamin; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2017-10-01

The University of Notre Dame (ND) CMS group operates a modest-sized Tier-3 site suitable for local, final-stage analysis of CMS data. However, through the ND Center for Research Computing (CRC), Notre Dame researchers have opportunistic access to roughly 25k CPU cores of computing and a 100 Gb/s WAN network link. To understand the limits of what might be possible in this scenario, we undertook to use these resources for a wide range of CMS computing tasks from user analysis through large-scale Monte Carlo production (including both detector simulation and data reconstruction.) We will discuss the challenges inherent in effectively utilizing CRC resources for these tasks and the solutions deployed to overcome them.

The Eukaryotic Pathogen Databases: a functional genomic resource integrating data from human and veterinary parasites.

PubMed

Harb, Omar S; Roos, David S

2015-01-01

Over the past 20 years, advances in high-throughput biological techniques and the availability of computational resources including fast Internet access have resulted in an explosion of large genome-scale data sets "big data." While such data are readily available for download and personal use and analysis from a variety of repositories, often such analysis requires access to seldom-available computational skills. As a result a number of databases have emerged to provide scientists with online tools enabling the interrogation of data without the need for sophisticated computational skills beyond basic knowledge of Internet browser utility. This chapter focuses on the Eukaryotic Pathogen Databases (EuPathDB: http://eupathdb.org) Bioinformatic Resource Center (BRC) and illustrates some of the available tools and methods.

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

Network reliability maximization for stochastic-flow network subject to correlated failures using genetic algorithm and tabu\\xA0search

NASA Astrophysics Data System (ADS)

Yeh, Cheng-Ta; Lin, Yi-Kuei; Yang, Jo-Yun

2018-07-01

Network reliability is an important performance index for many real-life systems, such as electric power systems, computer systems and transportation systems. These systems can be modelled as stochastic-flow networks (SFNs) composed of arcs and nodes. Most system supervisors respect the network reliability maximization by finding the optimal multi-state resource assignment, which is one resource to each arc. However, a disaster may cause correlated failures for the assigned resources, affecting the network reliability. This article focuses on determining the optimal resource assignment with maximal network reliability for SFNs. To solve the problem, this study proposes a hybrid algorithm integrating the genetic algorithm and tabu search to determine the optimal assignment, called the hybrid GA-TS algorithm (HGTA), and integrates minimal paths, recursive sum of disjoint products and the correlated binomial distribution to calculate network reliability. Several practical numerical experiments are adopted to demonstrate that HGTA has better computational quality than several popular soft computing algorithms.

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Architecture Framework for Trapped-Ion Quantum Computer based on Performance Simulation Tool

NASA Astrophysics Data System (ADS)

Ahsan, Muhammad

The challenge of building scalable quantum computer lies in striking appropriate balance between designing a reliable system architecture from large number of faulty computational resources and improving the physical quality of system components. The detailed investigation of performance variation with physics of the components and the system architecture requires adequate performance simulation tool. In this thesis we demonstrate a software tool capable of (1) mapping and scheduling the quantum circuit on a realistic quantum hardware architecture with physical resource constraints, (2) evaluating the performance metrics such as the execution time and the success probability of the algorithm execution, and (3) analyzing the constituents of these metrics and visualizing resource utilization to identify system components which crucially define the overall performance. Using this versatile tool, we explore vast design space for modular quantum computer architecture based on trapped ions. We find that while success probability is uniformly determined by the fidelity of physical quantum operation, the execution time is a function of system resources invested at various layers of design hierarchy. At physical level, the number of lasers performing quantum gates, impact the latency of the fault-tolerant circuit blocks execution. When these blocks are used to construct meaningful arithmetic circuit such as quantum adders, the number of ancilla qubits for complicated non-clifford gates and entanglement resources to establish long-distance communication channels, become major performance limiting factors. Next, in order to factorize large integers, these adders are assembled into modular exponentiation circuit comprising bulk of Shor's algorithm. At this stage, the overall scaling of resource-constraint performance with the size of problem, describes the effectiveness of chosen design. By matching the resource investment with the pace of advancement in hardware technology, we find optimal designs for different types of quantum adders. Conclusively, we show that 2,048-bit Shor's algorithm can be reliably executed within the resource budget of 1.5 million qubits.

Computer Viruses: Pathology and Detection.

ERIC Educational Resources Information Center

Maxwell, John R.; Lamon, William E.

1992-01-01

Explains how computer viruses were originally created, how a computer can become infected by a virus, how viruses operate, symptoms that indicate a computer is infected, how to detect and remove viruses, and how to prevent a reinfection. A sidebar lists eight antivirus resources. (four references) (LRW)

A Computer Security Course in the Undergraduate Computer Science Curriculum.

ERIC Educational Resources Information Center

Spillman, Richard

1992-01-01

Discusses the importance of computer security and considers criminal, national security, and personal privacy threats posed by security breakdown. Several examples are given, including incidents involving computer viruses. Objectives, content, instructional strategies, resources, and a sample examination for an experimental undergraduate computer…

Design for Run-Time Monitor on Cloud Computing

NASA Astrophysics Data System (ADS)

Kang, Mikyung; Kang, Dong-In; Yun, Mira; Park, Gyung-Leen; Lee, Junghoon

Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is the type of a parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring the system status change, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize resources on cloud computing. RTM monitors application software through library instrumentation as well as underlying hardware through performance counter optimizing its computing configuration based on the analyzed data.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

Traffic Simulations on Parallel Computers Using Domain Decomposition Techniques

DOT National Transportation Integrated Search

1995-01-01

Large scale simulations of Intelligent Transportation Systems (ITS) can only be acheived by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic...

The Merit Computer Network

ERIC Educational Resources Information Center

Aupperle, Eric M.; Davis, Donna L.

1978-01-01

The successful Merit Computer Network is examined in terms of both technology and operational management. The network is fully operational and has a significant and rapidly increasing usage, with three major institutions currently sharing computer resources. (Author/CMV)

Allocating Tactical High-Performance Computer (HPC) Resources to Offloaded Computation in Battlefield Scenarios

DTIC Science & Technology

2013-12-01

authors present a Computing on Dissemination with predictable contacts ( pCoD ) algorithm, since it is impossible to reserve task execution time in advance...Computing While Charging DAG Directed Acyclic Graph 18 TTL Time-to-live pCoD Predictable contacts CoD Computing on Dissemination upCoD Unpredictable

Factors Influencing the Adoption of Cloud Computing by Decision Making Managers

ERIC Educational Resources Information Center

Ross, Virginia Watson

2010-01-01

Cloud computing is a growing field, addressing the market need for access to computing resources to meet organizational computing requirements. The purpose of this research is to evaluate the factors that influence an organization in their decision whether to adopt cloud computing as a part of their strategic information technology planning.…

Networked Microcomputers--The Next Generation in College Computing.

ERIC Educational Resources Information Center

Harris, Albert L.

The evolution of computer hardware for college computing has mirrored the industry's growth. When computers were introduced into the educational environment, they had limited capacity and served one user at a time. Then came large mainframes with many terminals sharing the resource. Next, the use of computers in office automation emerged. As…

VECTR: Virtual Environment Computational Training Resource

NASA Technical Reports Server (NTRS)

Little, William L.

2018-01-01

The Westridge Middle School Curriculum and Community Night is an annual event designed to introduce students and parents to potential employers in the Central Florida area. NASA participated in the event in 2017, and has been asked to come back for the 2018 event on January 25. We will be demonstrating our Microsoft Hololens Virtual Rovers project, and the Virtual Environment Computational Training Resource (VECTR) virtual reality tool.

The Legnaro-Padova distributed Tier-2: challenges and results

NASA Astrophysics Data System (ADS)

Badoer, Simone; Biasotto, Massimo; Costa, Fulvia; Crescente, Alberto; Fantinel, Sergio; Ferrari, Roberto; Gulmini, Michele; Maron, Gaetano; Michelotto, Michele; Sgaravatto, Massimo; Toniolo, Nicola

2014-06-01

The Legnaro-Padova Tier-2 is a computing facility serving the ALICE and CMS LHC experiments. It also supports other High Energy Physics experiments and other virtual organizations of different disciplines, which can opportunistically harness idle resources if available. The unique characteristic of this Tier-2 is its topology: the computational resources are spread in two different sites, about 15 km apart: the INFN Legnaro National Laboratories and the INFN Padova unit, connected through a 10 Gbps network link (it will be soon updated to 20 Gbps). Nevertheless these resources are seamlessly integrated and are exposed as a single computing facility. Despite this intrinsic complexity, the Legnaro-Padova Tier-2 ranks among the best Grid sites for what concerns reliability and availability. The Tier-2 comprises about 190 worker nodes, providing about 26000 HS06 in total. Such computing nodes are managed by the LSF local resource management system, and are accessible using a Grid-based interface implemented through multiple CREAM CE front-ends. dCache, xrootd and Lustre are the storage systems in use at the Tier-2: about 1.5 PB of disk space is available to users in total, through multiple access protocols. A 10 Gbps network link, planned to be doubled in the next months, connects the Tier-2 to WAN. This link is used for the LHC Open Network Environment (LHCONE) and for other general purpose traffic. In this paper we discuss about the experiences at the Legnaro-Padova Tier-2: the problems that had to be addressed, the lessons learned, the implementation choices. We also present the tools used for the daily management operations. These include DOCET, a Java-based webtool designed, implemented and maintained at the Legnaro-Padova Tier-2, and deployed also in other sites, such as the LHC Italian T1. DOCET provides an uniform interface to manage all the information about the physical resources of a computing center. It is also used as documentation repository available to the Tier-2 operations team. Finally we discuss about the foreseen developments of the existing infrastructure. This includes in particular the evolution from a Grid-based resource towards a Cloud-based computing facility.

A Formative Analysis of Resources Used to Learn Software

ERIC Educational Resources Information Center

Kay, Robin

2007-01-01

A comprehensive, formal comparison of resources used to learn computer software has yet to be researched. Understanding the relative strengths and weakness of resources would provide useful guidance to teachers and students. The purpose of the current study was to explore the effectiveness of seven key resources: human assistance, the manual, the…

Community-Authored Resources for Education

ERIC Educational Resources Information Center

Tinker, Robert; Linn, Marcia; Gerard, Libby; Staudt, Carolyn

2010-01-01

Textbooks are resources for learning that provide the structure, content, assessments, and teacher guidance for an entire course. Technology can provide a far better resource that provides the same functions, but takes full advantage of computers. This resource would be much more than text on a screen. It would use the best technology; it would be…

Computational Complexity and Human Decision-Making.

PubMed

Bossaerts, Peter; Murawski, Carsten

2017-12-01

The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

AGIS: Evolution of Distributed Computing information system for ATLAS

NASA Astrophysics Data System (ADS)

Anisenkov, A.; Di Girolamo, A.; Alandes, M.; Karavakis, E.

2015-12-01

ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produces petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization of computing resources in order to meet the ATLAS requirements of petabytes scale data operations. It has been evolved after the first period of LHC data taking (Run-1) in order to cope with new challenges of the upcoming Run- 2. In this paper we describe the evolution and recent developments of the ATLAS Grid Information System (AGIS), developed in order to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

Semantic computing and language knowledge bases

NASA Astrophysics Data System (ADS)

Wang, Lei; Wang, Houfeng; Yu, Shiwen

2017-09-01

As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Family History Resources.

ERIC Educational Resources Information Center

Bookmark, 1991

1991-01-01

The 12 articles in this issue focus on the theme of family history resources: (1) "Introduction: Family History Resources" (Joseph F. Shubert); (2) "Work, Credentials, and Expectations of a Professional Genealogist" (Coreen P. Hallenbeck and Lewis W. Hallenbeck); (3) "Computers and Genealogy" (Theresa C. Strasser);…

Resources for Teaching Astronomy.

ERIC Educational Resources Information Center

Grafton, Teresa; Suggett, Martin

1991-01-01

Resources that are available for teachers presenting astronomy in the National Curriculum are listed. Included are societies and organizations, resource centers and places to visit, planetaria, telescopes and binoculars, planispheres, star charts, night sky diaries, equipment, audiovisual materials, computer software, books, and magazines. (KR)

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices

PubMed Central

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B.

2018-01-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support. PMID:29629431

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets

PubMed Central

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

Background As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Methods Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Results Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Conclusions Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. PMID:24464852

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

PubMed

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

Approaches in highly parameterized inversion-PESTCommander, a graphical user interface for file and run management across networks

USGS Publications Warehouse

Karanovic, Marinko; Muffels, Christopher T.; Tonkin, Matthew J.; Hunt, Randall J.

2012-01-01

Models of environmental systems have become increasingly complex, incorporating increasingly large numbers of parameters in an effort to represent physical processes on a scale approaching that at which they occur in nature. Consequently, the inverse problem of parameter estimation (specifically, model calibration) and subsequent uncertainty analysis have become increasingly computation-intensive endeavors. Fortunately, advances in computing have made computational power equivalent to that of dozens to hundreds of desktop computers accessible through a variety of alternate means: modelers have various possibilities, ranging from traditional Local Area Networks (LANs) to cloud computing. Commonly used parameter estimation software is well suited to take advantage of the availability of such increased computing power. Unfortunately, logistical issues become increasingly important as an increasing number and variety of computers are brought to bear on the inverse problem. To facilitate efficient access to disparate computer resources, the PESTCommander program documented herein has been developed to provide a Graphical User Interface (GUI) that facilitates the management of model files ("file management") and remote launching and termination of "slave" computers across a distributed network of computers ("run management"). In version 1.0 described here, PESTCommander can access and ascertain resources across traditional Windows LANs: however, the architecture of PESTCommander has been developed with the intent that future releases will be able to access computing resources (1) via trusted domains established in Wide Area Networks (WANs) in multiple remote locations and (2) via heterogeneous networks of Windows- and Unix-based operating systems. The design of PESTCommander also makes it suitable for extension to other computational resources, such as those that are available via cloud computing. Version 1.0 of PESTCommander was developed primarily to work with the parameter estimation software PEST; the discussion presented in this report focuses on the use of the PESTCommander together with Parallel PEST. However, PESTCommander can be used with a wide variety of programs and models that require management, distribution, and cleanup of files before or after model execution. In addition to its use with the Parallel PEST program suite, discussion is also included in this report regarding the use of PESTCommander with the Global Run Manager GENIE, which was developed simultaneously with PESTCommander.

Generic Divide and Conquer Internet-Based Computing

NASA Technical Reports Server (NTRS)

Follen, Gregory J. (Technical Monitor); Radenski, Atanas

2003-01-01

The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.

An integrated decision support system for TRAC: A proposal

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

1991-01-01

Optimal allocation and usage of resources is a key to effective management. Resources of concern to TRAC are: Manpower (PSY), Money (Travel, contracts), Computing, Data, Models, etc. Management activities of TRAC include: Planning, Programming, Tasking, Monitoring, Updating, and Coordinating. Existing systems are insufficient, not completely automated, manpower intensive, and has the potential for data inconsistency exists. A system is proposed which suggests a means to integrate all project management activities of TRAC through the development of a sophisticated software and by utilizing the existing computing systems and network resources. The systems integration proposal is examined in detail.

A Modeling Framework for Optimal Computational Resource Allocation Estimation: Considering the Trade-offs between Physical Resolutions, Uncertainty and Computational Costs

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.; Rajagopal, R.

2014-12-01

Hydrogeological models that represent flow and transport in subsurface domains are usually large-scale with excessive computational complexity and uncertain characteristics. Uncertainty quantification for predicting flow and transport in heterogeneous formations often entails utilizing a numerical Monte Carlo framework, which repeatedly simulates the model according to a random field representing hydrogeological characteristics of the field. The physical resolution (e.g. grid resolution associated with the physical space) for the simulation is customarily chosen based on recommendations in the literature, independent of the number of Monte Carlo realizations. This practice may lead to either excessive computational burden or inaccurate solutions. We propose an optimization-based methodology that considers the trade-off between the following conflicting objectives: time associated with computational costs, statistical convergence of the model predictions and physical errors corresponding to numerical grid resolution. In this research, we optimally allocate computational resources by developing a modeling framework for the overall error based on a joint statistical and numerical analysis and optimizing the error model subject to a given computational constraint. The derived expression for the overall error explicitly takes into account the joint dependence between the discretization error of the physical space and the statistical error associated with Monte Carlo realizations. The accuracy of the proposed framework is verified in this study by applying it to several computationally extensive examples. Having this framework at hand aims hydrogeologists to achieve the optimum physical and statistical resolutions to minimize the error with a given computational budget. Moreover, the influence of the available computational resources and the geometric properties of the contaminant source zone on the optimum resolutions are investigated. We conclude that the computational cost associated with optimal allocation can be substantially reduced compared with prevalent recommendations in the literature.

Role of the ATLAS Grid Information System (AGIS) in Distributed Data Analysis and Simulation

NASA Astrophysics Data System (ADS)

Anisenkov, A. V.

2018-03-01

In modern high-energy physics experiments, particular attention is paid to the global integration of information and computing resources into a unified system for efficient storage and processing of experimental data. Annually, the ATLAS experiment performed at the Large Hadron Collider at the European Organization for Nuclear Research (CERN) produces tens of petabytes raw data from the recording electronics and several petabytes of data from the simulation system. For processing and storage of such super-large volumes of data, the computing model of the ATLAS experiment is based on heterogeneous geographically distributed computing environment, which includes the worldwide LHC computing grid (WLCG) infrastructure and is able to meet the requirements of the experiment for processing huge data sets and provide a high degree of their accessibility (hundreds of petabytes). The paper considers the ATLAS grid information system (AGIS) used by the ATLAS collaboration to describe the topology and resources of the computing infrastructure, to configure and connect the high-level software systems of computer centers, to describe and store all possible parameters, control, configuration, and other auxiliary information required for the effective operation of the ATLAS distributed computing applications and services. The role of the AGIS system in the development of a unified description of the computing resources provided by grid sites, supercomputer centers, and cloud computing into a consistent information model for the ATLAS experiment is outlined. This approach has allowed the collaboration to extend the computing capabilities of the WLCG project and integrate the supercomputers and cloud computing platforms into the software components of the production and distributed analysis workload management system (PanDA, ATLAS).

The Need for Computer Science

ERIC Educational Resources Information Center

Margolis, Jane; Goode, Joanna; Bernier, David

2011-01-01

Broadening computer science learning to include more students is a crucial item on the United States' education agenda, these authors say. Although policymakers advocate more computer science expertise, computer science offerings in high schools are few--and actually shrinking. In addition, poorly resourced schools with a high percentage of…

Professional Computer Education Organizations--A Resource for Administrators.

ERIC Educational Resources Information Center

Ricketts, Dick

Professional computer education organizations serve a valuable function by generating, collecting, and disseminating information concerning the role of the computer in education. This report touches briefly on the reasons for the rapid and successful development of professional computer education organizations. A number of attributes of effective…

Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods

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

Zhang, Jie; Draxl, Caroline; Hopson, Thomas

Numerical weather prediction (NWP) models have been widely used for wind resource assessment. Model runs with higher spatial resolution are generally more accurate, yet extremely computational expensive. An alternative approach is to use data generated by a low resolution NWP model, in conjunction with statistical methods. In order to analyze the accuracy and computational efficiency of different types of NWP-based wind resource assessment methods, this paper performs a comparison of three deterministic and probabilistic NWP-based wind resource assessment methodologies: (i) a coarse resolution (0.5 degrees x 0.67 degrees) global reanalysis data set, the Modern-Era Retrospective Analysis for Research and Applicationsmore » (MERRA); (ii) an analog ensemble methodology based on the MERRA, which provides both deterministic and probabilistic predictions; and (iii) a fine resolution (2-km) NWP data set, the Wind Integration National Dataset (WIND) Toolkit, based on the Weather Research and Forecasting model. Results show that: (i) as expected, the analog ensemble and WIND Toolkit perform significantly better than MERRA confirming their ability to downscale coarse estimates; (ii) the analog ensemble provides the best estimate of the multi-year wind distribution at seven of the nine sites, while the WIND Toolkit is the best at one site; (iii) the WIND Toolkit is more accurate in estimating the distribution of hourly wind speed differences, which characterizes the wind variability, at five of the available sites, with the analog ensemble being best at the remaining four locations; and (iv) the analog ensemble computational cost is negligible, whereas the WIND Toolkit requires large computational resources. Future efforts could focus on the combination of the analog ensemble with intermediate resolution (e.g., 10-15 km) NWP estimates, to considerably reduce the computational burden, while providing accurate deterministic estimates and reliable probabilistic assessments.« less

Overview of the LINCS architecture

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

Fletcher, J.G.; Watson, R.W.

1982-01-13

Computing at the Lawrence Livermore National Laboratory (LLNL) has evolved over the past 15 years with a computer network based resource sharing environment. The increasing use of low cost and high performance micro, mini and midi computers and commercially available local networking systems will accelerate this trend. Further, even the large scale computer systems, on which much of the LLNL scientific computing depends, are evolving into multiprocessor systems. It is our belief that the most cost effective use of this environment will depend on the development of application systems structured into cooperating concurrent program modules (processes) distributed appropriately over differentmore » nodes of the environment. A node is defined as one or more processors with a local (shared) high speed memory. Given the latter view, the environment can be characterized as consisting of: multiple nodes communicating over noisy channels with arbitrary delays and throughput, heterogenous base resources and information encodings, no single administration controlling all resources, distributed system state, and no uniform time base. The system design problem is - how to turn the heterogeneous base hardware/firmware/software resources of this environment into a coherent set of resources that facilitate development of cost effective, reliable, and human engineered applications. We believe the answer lies in developing a layered, communication oriented distributed system architecture; layered and modular to support ease of understanding, reconfiguration, extensibility, and hiding of implementation or nonessential local details; communication oriented because that is a central feature of the environment. The Livermore Interactive Network Communication System (LINCS) is a hierarchical architecture designed to meet the above needs. While having characteristics in common with other architectures, it differs in several respects.« less

Research on Computers in Mathematics Education, IV. The Use of Computers in Mathematics Education Resource Series.

ERIC Educational Resources Information Center

Kieren, Thomas E.

This last paper in a set of four reviews research on a wide variety of computer applications in the mathematics classroom. It covers computer-based instruction, especially drill-and-practice and tutorial modes; computer-managed instruction; and computer-augmented problem-solving. Analytical comments on the findings and status of the research are…

Scheduling quality of precise form sets which consist of tasks of circular type in GRID systems

NASA Astrophysics Data System (ADS)

Saak, A. E.; Kureichik, V. V.; Kravchenko, Y. A.

2018-05-01

Users’ demand in computer power and rise of technology favour the arrival of Grid systems. The quality of Grid systems’ performance depends on computer and time resources scheduling. Grid systems with a centralized structure of the scheduling system and user’s task are modeled by resource quadrant and re-source rectangle accordingly. A Non-Euclidean heuristic measure, which takes into consideration both the area and the form of an occupied resource region, is used to estimate scheduling quality of heuristic algorithms. The authors use sets, which are induced by the elements of square squaring, as an example of studying the adapt-ability of a level polynomial algorithm with an excess and the one with minimal deviation.

Resource Constrained Planning of Multiple Projects with Separable Activities

NASA Astrophysics Data System (ADS)

Fujii, Susumu; Morita, Hiroshi; Kanawa, Takuya

In this study we consider a resource constrained planning problem of multiple projects with separable activities. This problem provides a plan to process the activities considering a resource availability with time window. We propose a solution algorithm based on the branch and bound method to obtain the optimal solution minimizing the completion time of all projects. We develop three methods for improvement of computational efficiency, that is, to obtain initial solution with minimum slack time rule, to estimate lower bound considering both time and resource constraints and to introduce an equivalence relation for bounding operation. The effectiveness of the proposed methods is demonstrated by numerical examples. Especially as the number of planning projects increases, the average computational time and the number of searched nodes are reduced.

A computational model of the human hand 93-ERI-053

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

Hollerbach, K.; Axelrod, T.

1996-03-01

The objectives of the Computational Hand Modeling project were to prove the feasibility of the Laboratory`s NIKE3D finite element code to orthopaedic problems. Because of the great complexity of anatomical structures and the nonlinearity of their behavior, we have focused on a subset of joints of the hand and lower extremity and have developed algorithms to model their behavior. The algorithms developed here solve fundamental problems in computational biomechanics and can be expanded to describe any other joints of the human body. This kind of computational modeling has never successfully been attempted before, due in part to a lack ofmore » biomaterials data and a lack of computational resources. With the computational resources available at the National Laboratories and the collaborative relationships we have established with experimental and other modeling laboratories, we have been in a position to pursue our innovative approach to biomechanical and orthopedic modeling.« less

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.

A world-wide databridge supported by a commercial cloud provider

NASA Astrophysics Data System (ADS)

Tat Cheung, Kwong; Field, Laurence; Furano, Fabrizio

2017-10-01

Volunteer computing has the potential to provide significant additional computing capacity for the LHC experiments. One of the challenges with exploiting volunteer computing is to support a global community of volunteers that provides heterogeneous resources. However, high energy physics applications require more data input and output than the CPU intensive applications that are typically used by other volunteer computing projects. While the so-called databridge has already been successfully proposed as a method to span the untrusted and trusted domains of volunteer computing and Grid computing respective, globally transferring data between potentially poor-performing residential networks and CERN could be unreliable, leading to wasted resources usage. The expectation is that by placing a storage endpoint that is part of a wider, flexible geographical databridge deployment closer to the volunteers, the transfer success rate and the overall performance can be improved. This contribution investigates the provision of a globally distributed databridge implemented upon a commercial cloud provider.

Computational Science at the Argonne Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Romero, Nichols

2014-03-01

The goal of the Argonne Leadership Computing Facility (ALCF) is to extend the frontiers of science by solving problems that require innovative approaches and the largest-scale computing systems. ALCF's most powerful computer - Mira, an IBM Blue Gene/Q system - has nearly one million cores. How does one program such systems? What software tools are available? Which scientific and engineering applications are able to utilize such levels of parallelism? This talk will address these questions and describe a sampling of projects that are using ALCF systems in their research, including ones in nanoscience, materials science, and chemistry. Finally, the ways to gain access to ALCF resources will be presented. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357.

Integration of Titan supercomputer at OLCF with ATLAS Production System

NASA Astrophysics Data System (ADS)

Barreiro Megino, F.; De, K.; Jha, S.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Padolski, S.; Panitkin, S.; Wells, J.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The PanDA (Production and Distributed Analysis) workload management system was developed to meet the scale and complexity of distributed computing for the ATLAS experiment. PanDA managed resources are distributed worldwide, on hundreds of computing sites, with thousands of physicists accessing hundreds of Petabytes of data and the rate of data processing already exceeds Exabyte per year. While PanDA currently uses more than 200,000 cores at well over 100 Grid sites, future LHC data taking runs will require more resources than Grid computing can possibly provide. Additional computing and storage resources are required. Therefore ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. In this paper we will describe a project aimed at integration of ATLAS Production System with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). Current approach utilizes modified PanDA Pilot framework for job submission to Titan’s batch queues and local data management, with lightweight MPI wrappers to run single node workloads in parallel on Titan’s multi-core worker nodes. It provides for running of standard ATLAS production jobs on unused resources (backfill) on Titan. The system already allowed ATLAS to collect on Titan millions of core-hours per month, execute hundreds of thousands jobs, while simultaneously improving Titans utilization efficiency. We will discuss the details of the implementation, current experience with running the system, as well as future plans aimed at improvements in scalability and efficiency. Notice: This manuscript has been authored, by employees of Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms

PubMed Central

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.

2011-01-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404

CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.

PubMed

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W

2012-06-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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

GapMap: Enabling Comprehensive Autism Resource Epidemiology

PubMed Central

Albert, Nikhila; Schwartz, Jessey; Du, Michael

2017-01-01

Background For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. Objective The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. Methods We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. Results The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. Conclusions This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. PMID:28473303

GapMap: Enabling Comprehensive Autism Resource Epidemiology.

PubMed

Albert, Nikhila; Daniels, Jena; Schwartz, Jessey; Du, Michael; Wall, Dennis P

2017-05-04

For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. ©Nikhila Albert, Jena Daniels, Jessey Schwartz, Michael Du, Dennis P Wall. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 04.05.2017.

Supercomputing resources empowering superstack with interactive and integrated systems

NASA Astrophysics Data System (ADS)

Rückemann, Claus-Peter

2012-09-01

This paper presents the results from the development and implementation of Superstack algorithms to be dynamically used with integrated systems and supercomputing resources. Processing of geophysical data, thus named geoprocessing, is an essential part of the analysis of geoscientific data. The theory of Superstack algorithms and the practical application on modern computing architectures was inspired by developments introduced with processing of seismic data on mainframes and within the last years leading to high end scientific computing applications. There are several stacking algorithms known but with low signal to noise ratio in seismic data the use of iterative algorithms like the Superstack can support analysis and interpretation. The new Superstack algorithms are in use with wave theory and optical phenomena on highly performant computing resources for huge data sets as well as for sophisticated application scenarios in geosciences and archaeology.

Inclusive Schools. Topical Bibliography on Inclusive Schools.

ERIC Educational Resources Information Center

Sorenson, Barbara, Comp.; Drill, Janet, Comp.

This abstract bibliography of approximately 200 references looks at various aspects of inclusive schools. References are a result of computer searches of three databases: the Educational Resources Information Center (ERIC), Exceptional Child Education Resources, and the Western Regional Resources Center. Preliminary information includes directions…

Current Issues for Higher Education Information Resources Management.

ERIC Educational Resources Information Center

CAUSE/EFFECT, 1996

1996-01-01

Issues identified as important to the future of information resources management and use in higher education include information policy in a networked environment, distributed computing, integrating information resources and college planning, benchmarking information technology, integrated digital libraries, technology integration in teaching,…

Basic Skills Resource Center: Documentation and Phaseover Report for the Military Educators Resource NETWORK

DTIC Science & Technology

1985-01-01

narrative form. 111. Describe the subject of your request in 3 or 4 precise terms (e.g., reading skills , computer assisted instruction, adult literacy ...00 Research Product 85-03 L’C £ BASIC SKILLS RESOURCE CENTER: DOCUMENTATION AND PHASEOVER REPORT FOR THE MILITARY EDUCATORS RESOURCE NETWORK... SKILLS RESOURCE CENTER: DOCUMENTATION AND Interim Report PHLASEOVER REPORT FOR THE MILITARY EDUCATORS Feb 1982 - Sept 1984 RESOURCE NETWORK 6

ANL site response for the DOE FY1994 information resources management long-range plan

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

Boxberger, L.M.

1992-03-01

Argonne National Laboratory`s ANL Site Response for the DOE FY1994 Information Resources Management (IRM) Long-Range Plan (ANL/TM 500) is one of many contributions to the DOE information resources management long-range planning process and, as such, is an integral part of the DOE policy and program planning system. The Laboratory has constructed this response according to instructions in a Call issued in September 1991 by the DOE Office of IRM Policy, Plans and Oversight. As one of a continuing series, this Site Response is an update and extension of the Laboratory`s previous submissions. The response contains both narrative and tabular material.more » It covers an eight-year period consisting of the base year (FY1991), the current year (FY1992), the budget year (FY1993), the plan year (FY1994), and the out years (FY1995-FY1998). This Site Response was compiled by Argonne National Laboratory`s Computing and Telecommunications Division (CTD), which has the responsibility to provide leadership in optimizing computing and information services and disseminating computer-related technologies throughout the Laboratory. The Site Response consists of 5 parts: (1) a site overview, describes the ANL mission, overall organization structure, the strategic approach to meet information resource needs, the planning process, major issues and points of contact. (2) a software plan for DOE contractors, Part 2B, ``Software Plan FMS plan for DOE organizations, (3) computing resources telecommunications, (4) telecommunications, (5) printing and publishing.« less

ANL site response for the DOE FY1994 information resources management long-range plan

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

Boxberger, L.M.

1992-03-01

Argonne National Laboratory's ANL Site Response for the DOE FY1994 Information Resources Management (IRM) Long-Range Plan (ANL/TM 500) is one of many contributions to the DOE information resources management long-range planning process and, as such, is an integral part of the DOE policy and program planning system. The Laboratory has constructed this response according to instructions in a Call issued in September 1991 by the DOE Office of IRM Policy, Plans and Oversight. As one of a continuing series, this Site Response is an update and extension of the Laboratory's previous submissions. The response contains both narrative and tabular material.more » It covers an eight-year period consisting of the base year (FY1991), the current year (FY1992), the budget year (FY1993), the plan year (FY1994), and the out years (FY1995-FY1998). This Site Response was compiled by Argonne National Laboratory's Computing and Telecommunications Division (CTD), which has the responsibility to provide leadership in optimizing computing and information services and disseminating computer-related technologies throughout the Laboratory. The Site Response consists of 5 parts: (1) a site overview, describes the ANL mission, overall organization structure, the strategic approach to meet information resource needs, the planning process, major issues and points of contact. (2) a software plan for DOE contractors, Part 2B, Software Plan FMS plan for DOE organizations, (3) computing resources telecommunications, (4) telecommunications, (5) printing and publishing.« less

Italian regional health system structure and expected cancer survival.

PubMed

Vercelli, Marina; Lillini, Roberto; Quaglia, Alberto; Capocaccia, Riccardo

2014-01-01

Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels. Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995-1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macro-economy, demography, labor market, and health resources for 1995-2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables. The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics. The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

Integrating information about location and value of resources by white-faced saki monkeys (Pithecia pithecia).

PubMed

Cunningham, Elena; Janson, Charles

2007-07-01

Most studies of spatial memory in primates focus on species that inhabit large home ranges and have dispersed, patchy resources. Researchers assume that primates use memory to minimize distances traveled between resources. We investigated the use of spatial memory in a group of six white-faced sakis (Pithecia pithecia) on 12.8-ha Round Island, Guri Lake, Venezuela during a period of fruit abundance. The sakis' movements were analyzed with logistic regressions, a predictive computer model and a computer model that simulates movements. We considered all the resources available to the sakis and compared observed distances to predicted distances from a computer model for foragers who know nothing about the location of resources. Surprisingly, the observed distances were four times greater than the predicted distances, suggesting that the sakis passed by a majority of the available fruit trees without feeding. The odds of visiting a food tree, however, were significantly increased if the tree had been visited in the previous 3 days and had more than 100 fruit. The sakis' preferred resources were highly productive fruit trees, Capparis trees, and trees with water holes. They traveled efficiently to these sites. The sakis choice of feeding sites indicate that they combined knowledge acquired by repeatedly traveling through their home range with 'what' and 'where' information gained from individual visits to resources. Although the sakis' foraging choices increased the distance they traveled overall, choosing more valued sites allowed the group to minimize intra-group feeding competition, maintain intergroup dominance over important resources, and monitor the state of resources throughout their home range. The sakis' foraging decisions appear to have used spatial memory, elements of episodic-like memory and social and nutritional considerations.

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…

Natural resources information system.

NASA Technical Reports Server (NTRS)

Leachtenauer, J. C.; Woll, A. M.

1972-01-01

A computer-based Natural Resources Information System was developed for the Bureaus of Indian Affairs and Land Management. The system stores, processes and displays data useful to the land manager in the decision making process. Emphasis is placed on the use of remote sensing as a data source. Data input consists of maps, imagery overlays, and on-site data. Maps and overlays are entered using a digitizer and stored as irregular polygons, lines and points. Processing functions include set intersection, union and difference and area, length and value computations. Data output consists of computer tabulations and overlays prepared on a drum plotter.

Lattice Boltzmann for Airframe Noise Predictions

NASA Technical Reports Server (NTRS)

Barad, Michael; Kocheemoolayil, Joseph; Kiris, Cetin

2017-01-01

Increase predictive use of High-Fidelity Computational Aero- Acoustics (CAA) capabilities for NASA's next generation aviation concepts. CFD has been utilized substantially in analysis and design for steady-state problems (RANS). Computational resources are extremely challenged for high-fidelity unsteady problems (e.g. unsteady loads, buffet boundary, jet and installation noise, fan noise, active flow control, airframe noise, etc) ü Need novel techniques for reducing the computational resources consumed by current high-fidelity CAA Need routine acoustic analysis of aircraft components at full-scale Reynolds number from first principles Need an order of magnitude reduction in wall time to solution!

Computational Multiqubit Tunnelling in Programmable Quantum Annealers

DTIC Science & Technology

2016-08-25

ARTICLE Received 3 Jun 2015 | Accepted 26 Nov 2015 | Published 7 Jan 2016 Computational multiqubit tunnelling in programmable quantum annealers...state itself. Quantum tunnelling has been hypothesized as an advantageous physical resource for optimization in quantum annealing. However, computational ...qubit tunnelling plays a computational role in a currently available programmable quantum annealer. We devise a probe for tunnelling, a computational

A Web of Resources for Introductory Computer Science.

ERIC Educational Resources Information Center

Rebelsky, Samuel A.

As the field of Computer Science has grown, the syllabus of the introductory Computer Science course has changed significantly. No longer is it a simple introduction to programming or a tutorial on computer concepts and applications. Rather, it has become a survey of the field of Computer Science, touching on a wide variety of topics from digital…

Goals and Objectives for Computing in the Associated Colleges of the St. Lawrence Valley.

ERIC Educational Resources Information Center

Grupe, Fritz H.

A forecast of the computing requirements of the Associated Colleges of the St. Lawrence Valley, an analysis of their needs, and specifications for a joint computer system are presented. Problems encountered included the lack of resources and computer sophistication at the member schools and a dearth of experience with long-term computer consortium…

Distributed GPU Computing in GIScience

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yang, C.; Huang, Q.; Li, J.; Sun, M.

2013-12-01

Geoscientists strived to discover potential principles and patterns hidden inside ever-growing Big Data for scientific discoveries. To better achieve this objective, more capable computing resources are required to process, analyze and visualize Big Data (Ferreira et al., 2003; Li et al., 2013). Current CPU-based computing techniques cannot promptly meet the computing challenges caused by increasing amount of datasets from different domains, such as social media, earth observation, environmental sensing (Li et al., 2013). Meanwhile CPU-based computing resources structured as cluster or supercomputer is costly. In the past several years with GPU-based technology matured in both the capability and performance, GPU-based computing has emerged as a new computing paradigm. Compare to traditional computing microprocessor, the modern GPU, as a compelling alternative microprocessor, has outstanding high parallel processing capability with cost-effectiveness and efficiency(Owens et al., 2008), although it is initially designed for graphical rendering in visualization pipe. This presentation reports a distributed GPU computing framework for integrating GPU-based computing within distributed environment. Within this framework, 1) for each single computer, computing resources of both GPU-based and CPU-based can be fully utilized to improve the performance of visualizing and processing Big Data; 2) within a network environment, a variety of computers can be used to build up a virtual super computer to support CPU-based and GPU-based computing in distributed computing environment; 3) GPUs, as a specific graphic targeted device, are used to greatly improve the rendering efficiency in distributed geo-visualization, especially for 3D/4D visualization. Key words: Geovisualization, GIScience, Spatiotemporal Studies Reference : 1. Ferreira de Oliveira, M. C., & Levkowitz, H. (2003). From visual data exploration to visual data mining: A survey. Visualization and Computer Graphics, IEEE Transactions on, 9(3), 378-394. 2. Li, J., Jiang, Y., Yang, C., Huang, Q., & Rice, M. (2013). Visualizing 3D/4D Environmental Data Using Many-core Graphics Processing Units (GPUs) and Multi-core Central Processing Units (CPUs). Computers & Geosciences, 59(9), 78-89. 3. Owens, J. D., Houston, M., Luebke, D., Green, S., Stone, J. E., & Phillips, J. C. (2008). GPU computing. Proceedings of the IEEE, 96(5), 879-899.

Natural Resource Information System. Volume 2: System operating procedures and instructions

NASA Technical Reports Server (NTRS)

1972-01-01

A total computer software system description is provided for the prototype Natural Resource Information System designed to store, process, and display data of maximum usefulness to land management decision making. Program modules are described, as are the computer file design, file updating methods, digitizing process, and paper tape conversion to magnetic tape. Operating instructions for the system, data output, printed output, and graphic output are also discussed.

ERDC MSRC (Major Shared Resource Center) Resource. High Performance Computing for the Warfighter. Fall 2008

DTIC Science & Technology

2008-01-01

32 “Solving the Hard Problems” at UGC 2008 in Seattle By Rose J. Dykes, ERDC MSRC...two fields to remain competitive in the global market . The ERDC MSRC attempts to take every available opportunity to encourage students to enter these...Attendees of the 18th annual DoD High Performance Computing Mod ern- ization Pr ogram (HPCMP) Users Gr oup Confer ence ( UGC

Are Cloud Environments Ready for Scientific Applications?

NASA Astrophysics Data System (ADS)

Mehrotra, P.; Shackleford, K.

2011-12-01

Cloud computing environments are becoming widely available both in the commercial and government sectors. They provide flexibility to rapidly provision resources in order to meet dynamic and changing computational needs without the customers incurring capital expenses and/or requiring technical expertise. Clouds also provide reliable access to resources even though the end-user may not have in-house expertise for acquiring or operating such resources. Consolidation and pooling in a cloud environment allow organizations to achieve economies of scale in provisioning or procuring computing resources and services. Because of these and other benefits, many businesses and organizations are migrating their business applications (e.g., websites, social media, and business processes) to cloud environments-evidenced by the commercial success of offerings such as the Amazon EC2. In this paper, we focus on the feasibility of utilizing cloud environments for scientific workloads and workflows particularly of interest to NASA scientists and engineers. There is a wide spectrum of such technical computations. These applications range from small workstation-level computations to mid-range computing requiring small clusters to high-performance simulations requiring supercomputing systems with high bandwidth/low latency interconnects. Data-centric applications manage and manipulate large data sets such as satellite observational data and/or data previously produced by high-fidelity modeling and simulation computations. Most of the applications are run in batch mode with static resource requirements. However, there do exist situations that have dynamic demands, particularly ones with public-facing interfaces providing information to the general public, collaborators and partners, as well as to internal NASA users. In the last few months we have been studying the suitability of cloud environments for NASA's technical and scientific workloads. We have ported several applications to multiple cloud environments including NASA's Nebula environment, Amazon's EC2, Magellan at NERSC, and SGI's Cyclone system. We critically examined the performance of the applications on these systems. We also collected information on the usability of these cloud environments. In this talk we will present the results of our study focusing on the efficacy of using clouds for NASA's scientific applications.

RAID v2.0: an updated resource of RNA-associated interactions across organisms.

PubMed

Yi, Ying; Zhao, Yue; Li, Chunhua; Zhang, Lin; Huang, Huiying; Li, Yana; Liu, Lanlan; Hou, Ping; Cui, Tianyu; Tan, Puwen; Hu, Yongfei; Zhang, Ting; Huang, Yan; Li, Xiaobo; Yu, Jia; Wang, Dong

2017-01-04

With the development of biotechnologies and computational prediction algorithms, the number of experimental and computational prediction RNA-associated interactions has grown rapidly in recent years. However, diverse RNA-associated interactions are scattered over a wide variety of resources and organisms, whereas a fully comprehensive view of diverse RNA-associated interactions is still not available for any species. Hence, we have updated the RAID database to version 2.0 (RAID v2.0, www.rna-society.org/raid/) by integrating experimental and computational prediction interactions from manually reading literature and other database resources under one common framework. The new developments in RAID v2.0 include (i) over 850-fold RNA-associated interactions, an enhancement compared to the previous version; (ii) numerous resources integrated with experimental or computational prediction evidence for each RNA-associated interaction; (iii) a reliability assessment for each RNA-associated interaction based on an integrative confidence score; and (iv) an increase of species coverage to 60. Consequently, RAID v2.0 recruits more than 5.27 million RNA-associated interactions, including more than 4 million RNA-RNA interactions and more than 1.2 million RNA-protein interactions, referring to nearly 130 000 RNA/protein symbols across 60 species. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Population-based learning of load balancing policies for a distributed computer system

NASA Technical Reports Server (NTRS)

Mehra, Pankaj; Wah, Benjamin W.

1993-01-01

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

NASA Astrophysics Data System (ADS)

Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Twomey, M. S.; Zaytsev, A.

2014-06-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

Enabling BOINC in infrastructure as a service cloud system

NASA Astrophysics Data System (ADS)

Montes, Diego; Añel, Juan A.; Pena, Tomás F.; Uhe, Peter; Wallom, David C. H.

2017-02-01

Volunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low-cost access to massive computing resources but also where there is a significant public interest in the research being done.We discuss the way in which cloud services can help BOINC-based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing platform within the cloud, and outline new approaches that could open up new possibilities in this field, using Climateprediction.net (http://www.climateprediction.net/) as a case study.

OUR's: Optimum Utilization of Resources; A Guide to Instructional Resources in Occupational Education. Research Pub. 77-1.

ERIC Educational Resources Information Center

Beamish, Eric; And Others

This resource guide contains over 300 entries which are available through the Optimum Utilization of Resources (OUR's) exchange system. The entries describe learning materials, such as slides, video tapes, audio tapes, films, print material, and computer assisted instructional programs, which have been developed primarily by faculty of the…

A Framework for Understanding Physics Students' Computational Modeling Practices

NASA Astrophysics Data System (ADS)

Lunk, Brandon Robert

With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by their existing physics content knowledge, particularly their knowledge of analytic procedures. While this existing knowledge was often applied in inappropriate circumstances, the students were still able to display a considerable amount of understanding of the physics content and of analytic solution procedures. These observations could not be adequately accommodated by the existing literature of programming comprehension. In extending the resource framework to the task of computational modeling, I model students' practices in terms of three important elements. First, a knowledge base includes re- sources for understanding physics, math, and programming structures. Second, a mechanism for monitoring and control describes students' expectations as being directed towards numerical, analytic, qualitative or rote solution approaches and which can be influenced by the problem representation. Third, a set of solution approaches---many of which were identified in this study---describe what aspects of the knowledge base students use and how they use that knowledge to enact their expectations. This framework allows us as researchers to track student discussions and pinpoint the source of difficulties. This work opens up many avenues of potential research. First, this framework gives researchers a vocabulary for extending Resource Theory to other domains of instruction, such as modeling how physics students use graphs. Second, this framework can be used as the basis for modeling expert physicists' programming practices. Important instructional implications also follow from this research. Namely, as we broaden the use of computational modeling in the physics classroom, our instructional practices should focus on helping students understand the step-by-step nature of programming in contrast to the already salient analytic procedures.

A Comprehensive Toolset for General-Purpose Private Computing and Outsourcing

DTIC Science & Technology

2016-12-08

project and scientific advances made towards each of the research thrusts throughout the project duration. 1 Project Objectives Cloud computing enables...possibilities that the cloud enables is computation outsourcing, when the client can utilize any necessary computing resources for its computational task...Security considerations, however, stand on the way of harnessing the full benefits of cloud computing to the fullest extent and prevent clients from

Cognitive Model Exploration and Optimization: A New Challenge for Computational Science

DTIC Science & Technology

2010-03-01

the generation and analysis of computational cognitive models to explain various aspects of cognition. Typically the behavior of these models...computational scale of a workstation, so we have turned to high performance computing (HPC) clusters and volunteer computing for large-scale...computational resources. The majority of applications on the Department of Defense HPC clusters focus on solving partial differential equations (Post

Cloud-based crowd sensing: a framework for location-based crowd analyzer and advisor

NASA Astrophysics Data System (ADS)

Aishwarya, K. C.; Nambi, A.; Hudson, S.; Nadesh, R. K.

2017-11-01

Cloud computing is an emerging field of computer science to integrate and explore large and powerful computing systems and storages for personal and also for enterprise requirements. Mobile Cloud Computing is the inheritance of this concept towards mobile hand-held devices. Crowdsensing, or to be precise, Mobile Crowdsensing is the process of sharing resources from an available group of mobile handheld devices that support sharing of different resources such as data, memory and bandwidth to perform a single task for collective reasons. In this paper, we propose a framework to use Crowdsensing and perform a crowd analyzer and advisor whether the user can go to the place or not. This is an ongoing research and is a new concept to which the direction of cloud computing has shifted and is viable for more expansion in the near future.

Developing a Science Commons for Geosciences

NASA Astrophysics Data System (ADS)

Lenhardt, W. C.; Lander, H.

2016-12-01

Many scientific communities, recognizing the research possibilities inherent in data sets, have created domain specific archives such as the Incorporated Research Institutions for Seismology (iris.edu) and ClinicalTrials.gov. Though this is an important step forward, most scientists, including geoscientists, also use a variety of software tools and at least some amount of computation to conduct their research. While the archives make it simpler for scientists to locate the required data, provisioning disk space, compute resources, and network bandwidth can still require significant efforts. This challenge exists despite the wealth of resources available to researchers, namely lab IT resources, institutional IT resources, national compute resources (XSEDE, OSG), private clouds, public clouds, and the development of cyberinfrastructure technologies meant to facilitate use of those resources. Further tasks include obtaining and installing required tools for analysis and visualization. If the research effort is a collaboration or involves certain types of data, then the partners may well have additional non-scientific tasks such as securing the data and developing secure sharing methods for the data. These requirements motivate our investigations into the "Science Commons". This paper will present a working definition of a science commons, compare and contrast examples of existing science commons, and describe a project based at RENCI to implement a science commons for risk analytics. We will then explore what a similar tool might look like for the geosciences.

Cloud computing in medical imaging.

PubMed

Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

2013-07-01

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

Job Superscheduler Architecture and Performance in Computational Grid Environments

NASA Technical Reports Server (NTRS)

Shan, Hongzhang; Oliker, Leonid; Biswas, Rupak

2003-01-01

Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.

Dynfarm: A Dynamic Site Extension

NASA Astrophysics Data System (ADS)

Ciaschini, V.; De Girolamo, D.

2017-10-01

Requests for computing resources from LHC experiments are constantly mounting, and so are their peak usage. Since dimensioning a site to handle the peak usage times is impractical due to constraints on resources that many publicly-owned computing centres have, opportunistic usage of resources from external, even commercial, cloud providers is becoming more and more interesting, and is even the subject of upcoming initiative from the EU commission, named HelixNebula. While extra resources are always a good thing, to fully take advantage of them they must be integrated in the site’s own infrastructure and made available to users as if they were local resources. At the CNAF INFN Tier-1 we have developed a framework, called dynfarm, capable of taking external resources and, placing minimal and easily satisfied requirements upon them, fully integrate them into a pre-existing infrastructure and treat them as if they were local, fully-owned resources. In this article we for the first time will a give a full, complete description of the framework’s architecture along with all of its capabilities, to describe exactly what is possible with it and what are its requirements.

Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing.

PubMed

Ma, Xiao; Lin, Chuang; Zhang, Han; Liu, Jianwei

2018-06-15

Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

NASA Astrophysics Data System (ADS)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets.

PubMed

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Parallel computing for automated model calibration

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

Burke, John S.; Danielson, Gary R.; Schulz, Douglas A.

2002-07-29

Natural resources model calibration is a significant burden on computing and staff resources in modeling efforts. Most assessments must consider multiple calibration objectives (for example magnitude and timing of stream flow peak). An automated calibration process that allows real time updating of data/models, allowing scientists to focus effort on improving models is needed. We are in the process of building a fully featured multi objective calibration tool capable of processing multiple models cheaply and efficiently using null cycle computing. Our parallel processing and calibration software routines have been generically, but our focus has been on natural resources model calibration. Somore » far, the natural resources models have been friendly to parallel calibration efforts in that they require no inter-process communication, only need a small amount of input data and only output a small amount of statistical information for each calibration run. A typical auto calibration run might involve running a model 10,000 times with a variety of input parameters and summary statistical output. In the past model calibration has been done against individual models for each data set. The individual model runs are relatively fast, ranging from seconds to minutes. The process was run on a single computer using a simple iterative process. We have completed two Auto Calibration prototypes and are currently designing a more feature rich tool. Our prototypes have focused on running the calibration in a distributed computing cross platform environment. They allow incorporation of?smart? calibration parameter generation (using artificial intelligence processing techniques). Null cycle computing similar to SETI@Home has also been a focus of our efforts. This paper details the design of the latest prototype and discusses our plans for the next revision of the software.« less

Medical Student Preferences for Self-Directed Study Resources in Gross Anatomy

ERIC Educational Resources Information Center

Choi-Lundberg, Derek L.; Low, Tze Feng; Patman, Phillip; Turner, Paul; Sinha, Sankar N.

2016-01-01

Gross anatomy instruction in medical curricula involve a range of resources and activities including dissection, prosected specimens, anatomical models, radiological images, surface anatomy, textbooks, atlases, and computer-assisted learning (CAL). These resources and activities are underpinned by the expectation that students will actively engage…

Immersive Education, an Annotated Webliography

ERIC Educational Resources Information Center

Pricer, Wayne F.

2011-01-01

In this second installment of a two-part feature on immersive education a webliography will provide resources discussing the use of various types of computer simulations including: (a) augmented reality, (b) virtual reality programs, (c) gaming resources for teaching with technology, (d) virtual reality lab resources, (e) virtual reality standards…

Mathematics and Computer Science | Argonne National Laboratory

Science.gov Websites

Genomics and Systems Biology LCRCLaboratory Computing Resource Center MCSGMidwest Center for Structural Genomics NAISENorthwestern-Argonne Institute of Science & Engineering SBCStructural Biology Center

Cloud computing basics for librarians.

PubMed

Hoy, Matthew B

2012-01-01

"Cloud computing" is the name for the recent trend of moving software and computing resources to an online, shared-service model. This article briefly defines cloud computing, discusses different models, explores the advantages and disadvantages, and describes some of the ways cloud computing can be used in libraries. Examples of cloud services are included at the end of the article. Copyright © Taylor & Francis Group, LLC

omniClassifier: a Desktop Grid Computing System for Big Data Prediction Modeling

PubMed Central

Phan, John H.; Kothari, Sonal; Wang, May D.

2016-01-01

Robust prediction models are important for numerous science, engineering, and biomedical applications. However, best-practice procedures for optimizing prediction models can be computationally complex, especially when choosing models from among hundreds or thousands of parameter choices. Computational complexity has further increased with the growth of data in these fields, concurrent with the era of “Big Data”. Grid computing is a potential solution to the computational challenges of Big Data. Desktop grid computing, which uses idle CPU cycles of commodity desktop machines, coupled with commercial cloud computing resources can enable research labs to gain easier and more cost effective access to vast computing resources. We have developed omniClassifier, a multi-purpose prediction modeling application that provides researchers with a tool for conducting machine learning research within the guidelines of recommended best-practices. omniClassifier is implemented as a desktop grid computing system using the Berkeley Open Infrastructure for Network Computing (BOINC) middleware. In addition to describing implementation details, we use various gene expression datasets to demonstrate the potential scalability of omniClassifier for efficient and robust Big Data prediction modeling. A prototype of omniClassifier can be accessed at http://omniclassifier.bme.gatech.edu/. PMID:27532062

An open-source computational and data resource to analyze digital maps of immunopeptidomes

DOE PAGES

Caron, Etienne; Espona, Lucia; Kowalewski, Daniel J.; ...

2015-07-08

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

Managing large-scale workflow execution from resource provisioning to provenance tracking: The CyberShake example

USGS Publications Warehouse

Deelman, E.; Callaghan, S.; Field, E.; Francoeur, H.; Graves, R.; Gupta, N.; Gupta, V.; Jordan, T.H.; Kesselman, C.; Maechling, P.; Mehringer, J.; Mehta, G.; Okaya, D.; Vahi, K.; Zhao, L.

2006-01-01

This paper discusses the process of building an environment where large-scale, complex, scientific analysis can be scheduled onto a heterogeneous collection of computational and storage resources. The example application is the Southern California Earthquake Center (SCEC) CyberShake project, an analysis designed to compute probabilistic seismic hazard curves for sites in the Los Angeles area. We explain which software tools were used to build to the system, describe their functionality and interactions. We show the results of running the CyberShake analysis that included over 250,000 jobs using resources available through SCEC and the TeraGrid. ?? 2006 IEEE.

Interoperable PKI Data Distribution in Computational Grids

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

Pala, Massimiliano; Cholia, Shreyas; Rea, Scott A.

One of the most successful working examples of virtual organizations, computational grids need authentication mechanisms that inter-operate across domain boundaries. Public Key Infrastructures(PKIs) provide sufficient flexibility to allow resource managers to securely grant access to their systems in such distributed environments. However, as PKIs grow and services are added to enhance both security and usability, users and applications must struggle to discover available resources-particularly when the Certification Authority (CA) is alien to the relying party. This article presents how to overcome these limitations of the current grid authentication model by integrating the PKI Resource Query Protocol (PRQP) into the Gridmore » Security Infrastructure (GSI).« less