Understanding Shale Gas: Recent Progress and Remaining Challenges

DOE PAGES

Striolo, Alberto; Cole, David R.

2017-08-27

Because of a number of technological advancements, unconventional hydrocarbons, and in particular shale gas, have transformed the US economy. Much is being learned, as demonstrated by the reduced cost of extracting shale gas in the US over the past five years. However, a number of challenges still need to be addressed. Many of these challenges represent grand scientific and technological tasks, overcoming which will have a number of positive impacts, ranging from the reduction of the environmental footprint of shale gas production to improvements and leaps forward in diverse sectors, including chemical manufacturing and catalytic transformations. This review addresses recentmore » advancements in computational and experimental approaches, which led to improved understanding of, in particular, structure and transport of fluids, including hydrocarbons, electrolytes, water, and CO 2 in heterogeneous subsurface rocks such as those typically found in shale formations. Finally, the narrative is concluded with a suggestion of a few research directions that, by synergistically combining computational and experimental advances, could allow us to overcome some of the hurdles that currently hinder the production of hydrocarbons from shale formations.« less

Final Project Report. Scalable fault tolerance runtime technology for petascale computers

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

Krishnamoorthy, Sriram; Sadayappan, P

With the massive number of components comprising the forthcoming petascale computer systems, hardware failures will be routinely encountered during execution of large-scale applications. Due to the multidisciplinary, multiresolution, and multiscale nature of scientific problems that drive the demand for high end systems, applications place increasingly differing demands on the system resources: disk, network, memory, and CPU. In addition to MPI, future applications are expected to use advanced programming models such as those developed under the DARPA HPCS program as well as existing global address space programming models such as Global Arrays, UPC, and Co-Array Fortran. While there has been amore » considerable amount of work in fault tolerant MPI with a number of strategies and extensions for fault tolerance proposed, virtually none of advanced models proposed for emerging petascale systems is currently fault aware. To achieve fault tolerance, development of underlying runtime and OS technologies able to scale to petascale level is needed. This project has evaluated range of runtime techniques for fault tolerance for advanced programming models.« less

Representation of Serendipitous Scientific Data

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

A computer program defines and implements an innovative kind of data structure than can be used for representing information derived from serendipitous discoveries made via collection of scientific data on long exploratory spacecraft missions. Data structures capable of collecting any kind of data can easily be implemented in advance, but the task of designing a fixed and efficient data structure suitable for processing raw data into useful information and taking advantage of serendipitous scientific discovery is becoming increasingly difficult as missions go deeper into space. The present software eases the task by enabling definition of arbitrarily complex data structures that can adapt at run time as raw data are transformed into other types of information. This software runs on a variety of computers, and can be distributed in either source code or binary code form. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware. It has no specific memory requirements and depends upon the other software with which it is used. This program is implemented as a library that is called by, and becomes folded into, the other software with which it is used.

Advancing Science through Mining Libraries, Ontologies, and Communities*

PubMed Central

Evans, James A.; Rzhetsky, Andrey

2011-01-01

Life scientists today cannot hope to read everything relevant to their research. Emerging text-mining tools can help by identifying topics and distilling statements from books and articles with increased accuracy. Researchers often organize these statements into ontologies, consistent systems of reality claims. Like scientific thinking and interchange, however, text-mined information (even when accurately captured) is complex, redundant, sometimes incoherent, and often contradictory: it is rooted in a mixture of only partially consistent ontologies. We review work that models scientific reason and suggest how computational reasoning across ontologies and the broader distribution of textual statements can assess the certainty of statements and the process by which statements become certain. With the emergence of digitized data regarding networks of scientific authorship, institutions, and resources, we explore the possibility of accounting for social dependences and cultural biases in reasoning models. Computational reasoning is starting to fill out ontologies and flag internal inconsistencies in several areas of bioscience. In the not too distant future, scientists may be able to use statements and rich models of the processes that produced them to identify underexplored areas, resurrect forgotten findings and ideas, deconvolute the spaghetti of underlying ontologies, and synthesize novel knowledge and hypotheses. PMID:21566119

Introducing Seismic Tomography with Computational Modeling

NASA Astrophysics Data System (ADS)

Neves, R.; Neves, M. L.; Teodoro, V.

2011-12-01

Learning seismic tomography principles and techniques involves advanced physical and computational knowledge. In depth learning of such computational skills is a difficult cognitive process that requires a strong background in physics, mathematics and computer programming. The corresponding learning environments and pedagogic methodologies should then involve sets of computational modelling activities with computer software systems which allow students the possibility to improve their mathematical or programming knowledge and simultaneously focus on the learning of seismic wave propagation and inverse theory. To reduce the level of cognitive opacity associated with mathematical or programming knowledge, several computer modelling systems have already been developed (Neves & Teodoro, 2010). Among such systems, Modellus is particularly well suited to achieve this goal because it is a domain general environment for explorative and expressive modelling with the following main advantages: 1) an easy and intuitive creation of mathematical models using just standard mathematical notation; 2) the simultaneous exploration of images, tables, graphs and object animations; 3) the attribution of mathematical properties expressed in the models to animated objects; and finally 4) the computation and display of mathematical quantities obtained from the analysis of images and graphs. Here we describe virtual simulations and educational exercises which enable students an easy grasp of the fundamental of seismic tomography. The simulations make the lecture more interactive and allow students the possibility to overcome their lack of advanced mathematical or programming knowledge and focus on the learning of seismological concepts and processes taking advantage of basic scientific computation methods and tools.

Information from imagery: ISPRS scientific vision and research agenda

NASA Astrophysics Data System (ADS)

Chen, Jun; Dowman, Ian; Li, Songnian; Li, Zhilin; Madden, Marguerite; Mills, Jon; Paparoditis, Nicolas; Rottensteiner, Franz; Sester, Monika; Toth, Charles; Trinder, John; Heipke, Christian

2016-05-01

With the increased availability of very high-resolution satellite imagery, terrain based imaging and participatory sensing, inexpensive platforms, and advanced information and communication technologies, the application of imagery is now ubiquitous, playing an important role in many aspects of life and work today. As a leading organisation in this field, the International Society for Photogrammetry and Remote Sensing (ISPRS) has been devoted to effectively and efficiently obtaining and utilising information from imagery since its foundation in the year 1910. This paper examines the significant challenges currently facing ISPRS and its communities, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving. The state-of-the-art in ISPRS related research and development is reviewed and the trends and topics for future work are identified. By providing an overarching scientific vision and research agenda, we hope to call on and mobilise all ISPRS scientists, practitioners and other stakeholders to continue improving our understanding and capacity on information from imagery and to deliver advanced geospatial knowledge that enables humankind to better deal with the challenges ahead, posed for example by global change, ubiquitous sensing, and a demand for real-time information generation.

Agile parallel bioinformatics workflow management using Pwrake.

PubMed

Mishima, Hiroyuki; Sasaki, Kensaku; Tanaka, Masahiro; Tatebe, Osamu; Yoshiura, Koh-Ichiro

2011-09-08

In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows.

Agile parallel bioinformatics workflow management using Pwrake

PubMed Central

2011-01-01

Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows. PMID:21899774

Advances in PCR technology.

PubMed

Lauerman, Lloyd H

2004-12-01

Since the discovery of the polymerase chain reaction (PCR) 20 years ago, an avalanche of scientific publications have reported major developments and changes in specialized equipment, reagents, sample preparation, computer programs and techniques, generated through business, government and university research. The requirement for genetic sequences for primer selection and validation has been greatly facilitated by the development of new sequencing techniques, machines and computer programs. Genetic libraries, such as GenBank, EMBL and DDBJ continue to accumulate a wealth of genetic sequence information for the development and validation of molecular-based diagnostic procedures concerning human and veterinary disease agents. The mechanization of various aspects of the PCR assay, such as robotics, microfluidics and nanotechnology, has made it possible for the rapid advancement of new procedures. Real-time PCR, DNA microarray and DNA chips utilize these newer techniques in conjunction with computer and computer programs. Instruments for hand-held PCR assays are being developed. The PCR and reverse transcription-PCR (RT-PCR) assays have greatly accelerated the speed and accuracy of diagnoses of human and animal disease, especially of the infectious agents that are difficult to isolate or demonstrate. The PCR has made it possible to genetically characterize a microbial isolate inexpensively and rapidly for identification, typing and epidemiological comparison.

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

PubMed Central

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

2013-01-01

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

Numerical methods for engine-airframe integration

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

Murthy, S.N.B.; Paynter, G.C.

1986-01-01

Various papers on numerical methods for engine-airframe integration are presented. The individual topics considered include: scientific computing environment for the 1980s, overview of prediction of complex turbulent flows, numerical solutions of the compressible Navier-Stokes equations, elements of computational engine/airframe integrations, computational requirements for efficient engine installation, application of CAE and CFD techniques to complete tactical missile design, CFD applications to engine/airframe integration, and application of a second-generation low-order panel methods to powerplant installation studies. Also addressed are: three-dimensional flow analysis of turboprop inlet and nacelle configurations, application of computational methods to the design of large turbofan engine nacelles, comparison ofmore » full potential and Euler solution algorithms for aeropropulsive flow field computations, subsonic/transonic, supersonic nozzle flows and nozzle integration, subsonic/transonic prediction capabilities for nozzle/afterbody configurations, three-dimensional viscous design methodology of supersonic inlet systems for advanced technology aircraft, and a user's technology assessment.« less

Education through the prism of computation

NASA Astrophysics Data System (ADS)

Kaurov, Vitaliy

2014-03-01

With the rapid development of technology, computation claims its irrevocable place among research components of modern science. Thus to foster a successful future scientist, engineer or educator we need to add computation to the foundations of scientific education. We will discuss what type of paradigm shifts it brings to these foundations on the example of Wolfram Science Summer School. It is one of the most advanced computational outreach programs run by Wolfram Foundation, welcoming participants of almost all ages and backgrounds. Centered on complexity science and physics, it also covers numerous adjacent and interdisciplinary fields such as finance, biology, medicine and even music. We will talk about educational and research experiences in this program during the 12 years of its existence. We will review statistics and outputs the program has produced. Among these are interactive electronic publications at the Wolfram Demonstrations Project and contributions to the computational knowledge engine Wolfram|Alpa.

NASA High Performance Computing and Communications program

NASA Technical Reports Server (NTRS)

Holcomb, Lee; Smith, Paul; Hunter, Paul

1994-01-01

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 1(X)-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientists' abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project, exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects, as well as summaries of early accomplishments and the significance, status, and plans for individual research and development programs within each project. Areas of emphasis include benchmarking, testbeds, software and simulation methods.

Redrawing the frontiers in the age of post-publication review

PubMed Central

Galbraith, David W.

2015-01-01

Publication forms the core structure supporting the development and transmission of scientific knowledge. For this reason, it is essential that the highest standards of quality control be maintained, in particular to ensure that the information being transmitted allows reproducible replication of the described experiments, and that the interpretation of the results is sound. Quality control has traditionally involved editorial decisions based on anonymous pre-publication peer review. Post-publication review of individual articles took the lesser role since it did not feed directly back to the original literature. Rapid advances in computer and communications technologies over the last thirty years have revolutionized scientific publication, and the role and scope of post-publication review has greatly expanded. This perspective examines the ways in which pre- and post-publication peer review influence the scientific literature, and in particular how they might best be redrawn to deal with the twin problems of scientific non-reproducibility and fraud increasingly encountered at the frontiers of science. PMID:26097488

Component-based integration of chemistry and optimization software.

PubMed

Kenny, Joseph P; Benson, Steven J; Alexeev, Yuri; Sarich, Jason; Janssen, Curtis L; McInnes, Lois Curfman; Krishnan, Manojkumar; Nieplocha, Jarek; Jurrus, Elizabeth; Fahlstrom, Carl; Windus, Theresa L

2004-11-15

Typical scientific software designs make rigid assumptions regarding programming language and data structures, frustrating software interoperability and scientific collaboration. Component-based software engineering is an emerging approach to managing the increasing complexity of scientific software. Component technology facilitates code interoperability and reuse. Through the adoption of methodology and tools developed by the Common Component Architecture Forum, we have developed a component architecture for molecular structure optimization. Using the NWChem and Massively Parallel Quantum Chemistry packages, we have produced chemistry components that provide capacity for energy and energy derivative evaluation. We have constructed geometry optimization applications by integrating the Toolkit for Advanced Optimization, Portable Extensible Toolkit for Scientific Computation, and Global Arrays packages, which provide optimization and linear algebra capabilities. We present a brief overview of the component development process and a description of abstract interfaces for chemical optimizations. The components conforming to these abstract interfaces allow the construction of applications using different chemistry and mathematics packages interchangeably. Initial numerical results for the component software demonstrate good performance, and highlight potential research enabled by this platform.

Air, Ocean and Climate Monitoring Enhancing Undergraduate Training in the Physical, Environmental and Computer Sciences

NASA Technical Reports Server (NTRS)

Hope, W. W.; Johnson, L. P.; Obl, W.; Stewart, A.; Harris, W. C.; Craig, R. D.

2000-01-01

Faculty in the Department of Physical, Environmental and Computer Sciences strongly believe in the concept that undergraduate research and research-related activities must be integrated into the fabric of our undergraduate Science and Technology curricula. High level skills, such as problem solving, reasoning, collaboration and the ability to engage in research, are learned for advanced study in graduate school or for competing for well paying positions in the scientific community. One goal of our academic programs is to have a pipeline of research activities from high school to four year college, to graduate school, based on the GISS Institute on Climate and Planets model.

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

Basic Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Basic Energy Sciences, November 3-5, 2015, Rockville, Maryland

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

Windus, Theresa; Banda, Michael; Devereaux, Thomas

Computers have revolutionized every aspect of our lives. Yet in science, the most tantalizing applications of computing lie just beyond our reach. The current quest to build an exascale computer with one thousand times the capability of today’s fastest machines (and more than a million times that of a laptop) will take researchers over the next horizon. The field of materials, chemical reactions, and compounds is inherently complex. Imagine millions of new materials with new functionalities waiting to be discovered — while researchers also seek to extend those materials that are known to a dizzying number of new forms. Wemore » could translate massive amounts of data from high precision experiments into new understanding through data mining and analysis. We could have at our disposal the ability to predict the properties of these materials, to follow their transformations during reactions on an atom-by-atom basis, and to discover completely new chemical pathways or physical states of matter. Extending these predictions from the nanoscale to the mesoscale, from the ultrafast world of reactions to long-time simulations to predict the lifetime performance of materials, and to the discovery of new materials and processes will have a profound impact on energy technology. In addition, discovery of new materials is vital to move computing beyond Moore’s law. To realize this vision, more than hardware is needed. New algorithms to take advantage of the increase in computing power, new programming paradigms, and new ways of mining massive data sets are needed as well. This report summarizes the opportunities and the requisite computing ecosystem needed to realize the potential before us. In addition to pursuing new and more complete physical models and theoretical frameworks, this review found that the following broadly grouped areas relevant to the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR) would directly affect the Basic Energy Sciences (BES) mission need. Simulation, visualization, and data analysis are crucial for advances in energy science and technology. Revolutionary mathematical, software, and algorithm developments are required in all areas of BES science to take advantage of exascale computing architectures and to meet data analysis, management, and workflow needs. In partnership with ASCR, BES has an emerging and pressing need to develop new and disruptive capabilities in data science. More capable and larger high-performance computing (HPC) and data ecosystems are required to support priority research in BES. Continued success in BES research requires developing the next-generation workforce through education and training and by providing sustained career opportunities.« less

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

Chrzanowski, P; Walter, K

For the Laboratory and staff, 2006 was a year of outstanding achievements. As our many accomplishments in this annual report illustrate, the Laboratory's focus on important problems that affect our nation's security and our researchers breakthroughs in science and technology have led to major successes. As a national laboratory that is part of the Department of Energy's National Nuclear Security Administration (DOE/NNSA), Livermore is a key contributor to the Stockpile Stewardship Program for maintaining the safety, security, and reliability of the nation's nuclear weapons stockpile. The program has been highly successful, and our annual report features some of the Laboratory'smore » significant stockpile stewardship accomplishments in 2006. A notable example is a long-term study with Los Alamos National Laboratory, which found that weapon pit performance will not sharply degrade from the aging effects on plutonium. The conclusion was based on a wide range of nonnuclear experiments, detailed simulations, theoretical advances, and thorough analyses of the results of past nuclear tests. The study was a superb scientific effort. The continuing success of stockpile stewardship enabled NNSA in 2006 to lay out Complex 2030, a vision for a transformed nuclear weapons complex that is more responsive, cost efficient, and highly secure. One of the ways our Laboratory will help lead this transformation is through the design and development of reliable replacement warheads (RRWs). Compared to current designs, these warheads would have enhanced performance margins and security features and would be less costly to manufacture and maintain in a smaller, modernized production complex. In early 2007, NNSA selected Lawrence Livermore and Sandia National Laboratories-California to develop ''RRW-1'' for the U.S. Navy. Design efforts for the RRW, the plutonium aging work, and many other stockpile stewardship accomplishments rely on computer simulations performed on NNSA's Advanced Simulation and Computing (ASC) Program supercomputers at Livermore. ASC Purple and BlueGene/L, the world's fastest computer, together provide nearly a half petaflop (500 trillion operations per second) of computer power for use by the three NNSA national laboratories. Livermore-led teams were awarded the Gordon Bell Prize for Peak Performance in both 2005 and 2006. The winning simulations, run on BlueGene/L, investigated the properties of materials at the length and time scales of atomic interactions. The computing power that makes possible such detailed simulations provides unprecedented opportunities for scientific discovery. Laboratory scientists are meeting the extraordinary challenge of creating experimental capabilities to match the resolution of supercomputer simulations. Working with a wide range of collaborators, we are developing experimental tools that gather better data at the nanometer and subnanosecond scales. Applications range from imaging biomolecules to studying matter at extreme conditions of pressure and temperature. The premier high-energy-density experimental physics facility in the world will be the National Ignition Facility (NIF) when construction is completed in 2009. We are leading the national effort to perform the first fusion ignition experiments using NIF's 192-beam laser and prepare to explore some of the remaining important issues in weapons physics. With scientific colleagues from throughout the nation, we are also designing revolutionary experiments on NIF to advance the fields of astrophysics, planetary physics, and materials science. Mission-directed, multidisciplinary science and technology at Livermore is also focused on reducing the threat posed by the proliferation of weapons of mass destruction as well as their acquisition and use by terrorists. The Laboratory helps this important national effort by providing its unique expertise, integration analyses, and operational support to the Department of Homeland Security. For this vital facet of the Laboratory's national security mission, we are developing advanced technologies, such as a pocket-size explosives detector and an airborne persistent surveillance system, both of which earned R&D 100 Awards. Altogether, Livermore won seven R&D 100 Awards in 2006, the most for any organization. Emerging threats to national and global security go beyond defense and homeland security. Livermore pursues major scientific and technical advances to meet the need for a clean environment; clean, abundant energy; better water management; and improved human health. Our annual report highlights the link between human activities and the warming of tropical oceans, as well as techniques for imaging biological molecules and detecting bone cancer in its earliest stages. In addition, we showcase many scientific discoveries: distant planets, the composition of comets, a new superheavy element.« less

Fast Geostatistical Inversion using Randomized Matrix Decompositions and Sketchings for Heterogeneous Aquifer Characterization

NASA Astrophysics Data System (ADS)

O'Malley, D.; Le, E. B.; Vesselinov, V. V.

2015-12-01

We present a fast, scalable, and highly-implementable stochastic inverse method for characterization of aquifer heterogeneity. The method utilizes recent advances in randomized matrix algebra and exploits the structure of the Quasi-Linear Geostatistical Approach (QLGA), without requiring a structured grid like Fast-Fourier Transform (FFT) methods. The QLGA framework is a more stable version of Gauss-Newton iterates for a large number of unknown model parameters, but provides unbiased estimates. The methods are matrix-free and do not require derivatives or adjoints, and are thus ideal for complex models and black-box implementation. We also incorporate randomized least-square solvers and data-reduction methods, which speed up computation and simulate missing data points. The new inverse methodology is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. Inversion results based on series of synthetic problems with steady-state and transient calibration data are presented.

A Spacelab Expert System for Remote Engineering and Science

NASA Technical Reports Server (NTRS)

Groleau, Nick; Colombano, Silvano; Friedland, Peter (Technical Monitor)

1994-01-01

NASA's space science program is based on strictly pre-planned activities. This approach does not always result in the best science. We describe an existing computer system that enables space science to be conducted in a more reactive manner through advanced automation techniques that have recently been used in SLS-2 October 1993 space shuttle flight. Advanced computing techniques, usually developed in the field of Artificial Intelligence, allow large portions of the scientific investigator's knowledge to be "packaged" in a portable computer to present advice to the astronaut operator. We strongly believe that this technology has wide applicability to other forms of remote science/engineering. In this brief article, we present the technology of remote science/engineering assistance as implemented for the SLS-2 space shuttle flight. We begin with a logical overview of the system (paying particular attention to the implementation details relevant to the use of the embedded knowledge for system reasoning), then describe its use and success in space, and conclude with ideas about possible earth uses of the technology in the life and medical sciences.

Earth System Grid II, Turning Climate Datasets into Community Resources

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

Middleton, Don

2006-08-01

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

Evolving the Land Information System into a Cloud Computing Service

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

Houser, Paul R.

The Land Information System (LIS) was developed to use advanced flexible land surface modeling and data assimilation frameworks to integrate extremely large satellite- and ground-based observations with advanced land surface models to produce continuous high-resolution fields of land surface states and fluxes. The resulting fields are extremely useful for drought and flood assessment, agricultural planning, disaster management, weather and climate forecasting, water resources assessment, and the like. We envisioned transforming the LIS modeling system into a scientific cloud computing-aware web and data service that would allow clients to easily setup and configure for use in addressing large water management issues.more » The focus of this Phase 1 project was to determine the scientific, technical, commercial merit and feasibility of the proposed LIS-cloud innovations that are currently barriers to broad LIS applicability. We (a) quantified the barriers to broad LIS utility and commercialization (high performance computing, big data, user interface, and licensing issues); (b) designed the proposed LIS-cloud web service, model-data interface, database services, and user interfaces; (c) constructed a prototype LIS user interface including abstractions for simulation control, visualization, and data interaction, (d) used the prototype to conduct a market analysis and survey to determine potential market size and competition, (e) identified LIS software licensing and copyright limitations and developed solutions, and (f) developed a business plan for development and marketing of the LIS-cloud innovation. While some significant feasibility issues were found in the LIS licensing, overall a high degree of LIS-cloud technical feasibility was found.« less

Cross-Identification of Astronomical Catalogs on Multiple GPUs

NASA Astrophysics Data System (ADS)

Lee, M. A.; Budavári, T.

2013-10-01

One of the most fundamental problems in observational astronomy is the cross-identification of sources. Observations are made in different wavelengths, at different times, and from different locations and instruments, resulting in a large set of independent observations. The scientific outcome is often limited by our ability to quickly perform meaningful associations between detections. The matching, however, is difficult scientifically, statistically, as well as computationally. The former two require detailed physical modeling and advanced probabilistic concepts; the latter is due to the large volumes of data and the problem's combinatorial nature. In order to tackle the computational challenge and to prepare for future surveys, whose measurements will be exponentially increasing in size past the scale of feasible CPU-based solutions, we developed a new implementation which addresses the issue by performing the associations on multiple Graphics Processing Units (GPUs). Our implementation utilizes up to 6 GPUs in combination with the Thrust library to achieve an over 40x speed up verses the previous best implementation running on a multi-CPU SQL Server.

An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook

PubMed Central

Stevens, Jean-Luc R.; Elver, Marco; Bednar, James A.

2013-01-01

Lancet is a new, simulator-independent Python utility for succinctly specifying, launching, and collating results from large batches of interrelated computationally demanding program runs. This paper demonstrates how to combine Lancet with IPython Notebook to provide a flexible, lightweight, and agile workflow for fully reproducible scientific research. This informal and pragmatic approach uses IPython Notebook to capture the steps in a scientific computation as it is gradually automated and made ready for publication, without mandating the use of any separate application that can constrain scientific exploration and innovation. The resulting notebook concisely records each step involved in even very complex computational processes that led to a particular figure or numerical result, allowing the complete chain of events to be replicated automatically. Lancet was originally designed to help solve problems in computational neuroscience, such as analyzing the sensitivity of a complex simulation to various parameters, or collecting the results from multiple runs with different random starting points. However, because it is never possible to know in advance what tools might be required in future tasks, Lancet has been designed to be completely general, supporting any type of program as long as it can be launched as a process and can return output in the form of files. For instance, Lancet is also heavily used by one of the authors in a separate research group for launching batches of microprocessor simulations. This general design will allow Lancet to continue supporting a given research project even as the underlying approaches and tools change. PMID:24416014

Building Capacity Through Hands-on Computational Internships to Assure Reproducible Results and Implementation of Digital Documentation in the ICERT REU Program

NASA Astrophysics Data System (ADS)

Gomez, R.; Gentle, J.

2015-12-01

Modern data pipelines and computational processes require that meticulous methodologies be applied in order to insure that the source data, algorithms, and results are properly curated, managed and retained while remaining discoverable, accessible, and reproducible. Given the complexity of understanding the scientific problem domain being researched, combined with the overhead of learning to use advanced computing technologies, it becomes paramount that the next generation of scientists and researchers learn to embrace best-practices. The Integrative Computational Education and Research Traineeship (ICERT) is a National Science Foundation (NSF) Research Experience for Undergraduates (REU) Site at the Texas Advanced Computing Center (TACC). During Summer 2015, two ICERT interns joined the 3DDY project. 3DDY converts geospatial datasets into file types that can take advantage of new formats, such as natural user interfaces, interactive visualization, and 3D printing. Mentored by TACC researchers for ten weeks, students with no previous background in computational science learned to use scripts to build the first prototype of the 3DDY application, and leveraged Wrangler, the newest high performance computing (HPC) resource at TACC. Test datasets for quadrangles in central Texas were used to assemble the 3DDY workflow and code. Test files were successfully converted into a stereo lithographic (STL) format, which is amenable for use with a 3D printers. Test files and the scripts were documented and shared using the Figshare site while metadata was documented for the 3DDY application using OntoSoft. These efforts validated a straightforward set of workflows to transform geospatial data and established the first prototype version of 3DDY. Adding the data and software management procedures helped students realize a broader set of tangible results (e.g. Figshare entries), better document their progress and the final state of their work for the research group and community, helped students and researchers follow a clear set of formats and fill in the necessary details that may be lost otherwise, and exposed the students to the next generation workflows and practices for digital scholarship and scientific inquiry for converting geospatial data into formats that are easy to reuse.

Reflections on biomedical informatics: from cybernetics to genomic medicine and nanomedicine.

PubMed

Maojo, Victor; Kulikowski, Casimir A

2006-01-01

Expanding on our previous analysis of Biomedical Informatics (BMI), the present perspective ranges from cybernetics to nanomedicine, based on its scientific, historical, philosophical, theoretical, experimental, and technological aspects as they affect systems developments, simulation and modelling, education, and the impact on healthcare. We then suggest that BMI is still searching for strong basic scientific principles around which it can crystallize. As -omic biological knowledge increasingly impacts the future of medicine, ubiquitous computing and informatics become even more essential, not only for the technological infrastructure, but as a part of the scientific enterprise itself. The Virtual Physiological Human and investigations into nanomedicine will surely produce yet more unpredictable opportunities, leading to significant changes in biomedical research and practice. As a discipline involved in making such advances possible, BMI is likely to need to re-define itself and extend its research horizons to meet the new challenges.

3-D Imaging In Virtual Environment: A Scientific Clinical and Teaching Tool

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; DeVincenzi, Donald L. (Technical Monitor)

1996-01-01

The advent of powerful graphics workstations and computers has led to the advancement of scientific knowledge through three-dimensional (3-D) reconstruction and imaging of biological cells and tissues. The Biocomputation Center at NASA Ames Research Center pioneered the effort to produce an entirely computerized method for reconstruction of objects from serial sections studied in a transmission electron microscope (TEM). The software developed, ROSS (Reconstruction of Serial Sections), is now being distributed to users across the United States through Space Act Agreements. The software is in widely disparate fields such as geology, botany, biology and medicine. In the Biocomputation Center, ROSS serves as the basis for development of virtual environment technologies for scientific and medical use. This report will describe the Virtual Surgery Workstation Project that is ongoing with clinicians at Stanford University Medical Center, and the role of the Visible Human data in the project.

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus

PubMed Central

Karp, Peter D.; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida). PMID:26097686

ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-01-01

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).

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

McCoy, Michel; Archer, Bill; Hendrickson, Bruce

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computationalmore » resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further away from the original test base. Where possible, the program also enables the use of high performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and counter nuclear terrorism.« less

Center for Technology for Advanced Scientific Componet Software (TASCS)

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

Govindaraju, Madhusudhan

Advanced Scientific Computing Research Computer Science FY 2010Report Center for Technology for Advanced Scientific Component Software: Distributed CCA State University of New York, Binghamton, NY, 13902 Summary The overall objective of Binghamton's involvement is to work on enhancements of the CCA environment, motivated by the applications and research initiatives discussed in the proposal. This year we are working on re-focusing our design and development efforts to develop proof-of-concept implementations that have the potential to significantly impact scientific components. We worked on developing parallel implementations for non-hydrostatic code and worked on a model coupling interface for biogeochemical computations coded in MATLAB.more » We also worked on the design and implementation modules that will be required for the emerging MapReduce model to be effective for scientific applications. Finally, we focused on optimizing the processing of scientific datasets on multi-core processors. Research Details We worked on the following research projects that we are working on applying to CCA-based scientific applications. 1. Non-Hydrostatic Hydrodynamics: Non-static hydrodynamics are significantly more accurate at modeling internal waves that may be important in lake ecosystems. Non-hydrostatic codes, however, are significantly more computationally expensive, often prohibitively so. We have worked with Chin Wu at the University of Wisconsin to parallelize non-hydrostatic code. We have obtained a speed up of about 26 times maximum. Although this is significant progress, we hope to improve the performance further, such that it becomes a practical alternative to hydrostatic codes. 2. Model-coupling for water-based ecosystems: To answer pressing questions about water resources requires that physical models (hydrodynamics) be coupled with biological and chemical models. Most hydrodynamics codes are written in Fortran, however, while most ecologists work in MATLAB. This disconnect creates a great barrier. To address this, we are working on a model coupling interface that will allow biogeochemical computations written in MATLAB to couple with Fortran codes. This will greatly improve the productivity of ecosystem scientists. 2. Low overhead and Elastic MapReduce Implementation Optimized for Memory and CPU-Intensive Applications: Since its inception, MapReduce has frequently been associated with Hadoop and large-scale datasets. Its deployment at Amazon in the cloud, and its applications at Yahoo! for large-scale distributed document indexing and database building, among other tasks, have thrust MapReduce to the forefront of the data processing application domain. The applicability of the paradigm however extends far beyond its use with data intensive applications and diskbased systems, and can also be brought to bear in processing small but CPU intensive distributed applications. MapReduce however carries its own burdens. Through experiments using Hadoop in the context of diverse applications, we uncovered latencies and delay conditions potentially inhibiting the expected performance of a parallel execution in CPU-intensive applications. Furthermore, as it currently stands, MapReduce is favored for data-centric applications, and as such tends to be solely applied to disk-based applications. The paradigm, falls short in bringing its novelty to diskless systems dedicated to in-memory applications, and compute intensive programs processing much smaller data, but requiring intensive computations. In this project, we focused both on the performance of processing large-scale hierarchical data in distributed scientific applications, as well as the processing of smaller but demanding input sizes primarily used in diskless, and memory resident I/O systems. We designed LEMO-MR [1], a Low overhead, elastic, configurable for in- memory applications, and on-demand fault tolerance, an optimized implementation of MapReduce, for both on disk and in memory applications. We conducted experiments to identify not only the necessary components of this model, but also trade offs and factors to be considered. We have initial results to show the efficacy of our implementation in terms of potential speedup that can be achieved for representative data sets used by cloud applications. We have quantified the performance gains exhibited by our MapReduce implementation over Apache Hadoop in a compute intensive environment. 3. Cache Performance Optimization for Processing XML and HDF-based Application Data on Multi-core Processors: It is important to design and develop scientific middleware libraries to harness the opportunities presented by emerging multi-core processors. Implementations of scientific middleware and applications that do not adapt to the programming paradigm when executing on emerging processors can severely impact the overall performance. In this project, we focused on the utilization of the L2 cache, which is a critical shared resource on chip multiprocessors (CMP). The access pattern of the shared L2 cache, which is dependent on how the application schedules and assigns processing work to each thread, can either enhance or hurt the ability to hide memory latency on a multi-core processor. Therefore, while processing scientific datasets such as HDF5, it is essential to conduct fine-grained analysis of cache utilization, to inform scheduling decisions in multi-threaded programming. In this project, using the TAU toolkit for performance feedback from dual- and quad-core machines, we conducted performance analysis and recommendations on how processing threads can be scheduled on multi-core nodes to enhance the performance of a class of scientific applications that requires processing of HDF5 data. In particular, we quantified the gains associated with the use of the adaptations we have made to the Cache-Affinity and Balanced-Set scheduling algorithms to improve L2 cache performance, and hence the overall application execution time [2]. References: 1. Zacharia Fadika, Madhusudhan Govindaraju, ``MapReduce Implementation for Memory-Based and Processing Intensive Applications'', accepted in 2nd IEEE International Conference on Cloud Computing Technology and Science, Indianapolis, USA, Nov 30 - Dec 3, 2010. 2. Rajdeep Bhowmik, Madhusudhan Govindaraju, ``Cache Performance Optimization for Processing XML-based Application Data on Multi-core Processors'', in proceedings of The 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 17-20, 2010, Melbourne, Victoria, Australia. Contact Information: Madhusudhan Govindaraju Binghamton University State University of New York (SUNY) mgovinda@cs.binghamton.edu Phone: 607-777-4904« less

Preface: SciDAC 2005

NASA Astrophysics Data System (ADS)

Mezzacappa, Anthony

2005-01-01

On 26-30 June 2005 at the Grand Hyatt on Union Square in San Francisco several hundred computational scientists from around the world came together for what can certainly be described as a celebration of computational science. Scientists from the SciDAC Program and scientists from other agencies and nations were joined by applied mathematicians and computer scientists to highlight the many successes in the past year where computation has led to scientific discovery in a variety of fields: lattice quantum chromodynamics, accelerator modeling, chemistry, biology, materials science, Earth and climate science, astrophysics, and combustion and fusion energy science. Also highlighted were the advances in numerical methods and computer science, and the multidisciplinary collaboration cutting across science, mathematics, and computer science that enabled these discoveries. The SciDAC Program was conceived and funded by the US Department of Energy Office of Science. It is the Office of Science's premier computational science program founded on what is arguably the perfect formula: the priority and focus is science and scientific discovery, with the understanding that the full arsenal of `enabling technologies' in applied mathematics and computer science must be brought to bear if we are to have any hope of attacking and ultimately solving today's computational Grand Challenge problems. The SciDAC Program has been in existence for four years, and many of the computational scientists funded by this program will tell you that the program has given them the hope of addressing their scientific problems in full realism for the very first time. Many of these scientists will also tell you that SciDAC has also fundamentally changed the way they do computational science. We begin this volume with one of DOE's great traditions, and core missions: energy research. As we will see, computation has been seminal to the critical advances that have been made in this arena. Of course, to understand our world, whether it is to understand its very nature or to understand it so as to control it for practical application, will require explorations on all of its scales. Computational science has been no less an important tool in this arena than it has been in the arena of energy research. From explorations of quantum chromodynamics, the fundamental theory that describes how quarks make up the protons and neutrons of which we are composed, to explorations of the complex biomolecules that are the building blocks of life, to explorations of some of the most violent phenomena in our universe and of the Universe itself, computation has provided not only significant insight, but often the only means by which we have been able to explore these complex, multicomponent systems and by which we have been able to achieve scientific discovery and understanding. While our ultimate target remains scientific discovery, it certainly can be said that at a fundamental level the world is mathematical. Equations ultimately govern the evolution of the systems of interest to us, be they physical, chemical, or biological systems. The development and choice of discretizations of these underlying equations is often a critical deciding factor in whether or not one is able to model such systems stably, faithfully, and practically, and in turn, the algorithms to solve the resultant discrete equations are the complementary, critical ingredient in the recipe to model the natural world. The use of parallel computing platforms, especially at the TeraScale, and the trend toward even larger numbers of processors, continue to present significant challenges in the development and implementation of these algorithms. Computational scientists often speak of their `workflows'. A workflow, as the name suggests, is the sum total of all complex and interlocking tasks, from simulation set up, execution, and I/O, to visualization and scientific discovery, through which the advancement in our understanding of the natural world is realized. For the computational scientist, enabling such workflows presents myriad, signiflcant challenges, and it is computer scientists that are called upon at such times to address these challenges. Simulations are currently generating data at the staggering rate of tens of TeraBytes per simulation, over the course of days. In the next few years, these data generation rates are expected to climb exponentially to hundreds of TeraBytes per simulation, performed over the course of months. The output, management, movement, analysis, and visualization of these data will be our key to unlocking the scientific discoveries buried within the data. And there is no hope of generating such data to begin with, or of scientific discovery, without stable computing platforms and a sufficiently high and sustained performance of scientific applications codes on them. Thus, scientific discovery in the realm of computational science at the TeraScale and beyond will occur at the intersection of science, applied mathematics, and computer science. The SciDAC Program was constructed to mirror this reality, and the pages that follow are a testament to the efficacy of such an approach. We would like to acknowledge the individuals on whose talents and efforts the success of SciDAC 2005 was based. Special thanks go to Betsy Riley for her work on the SciDAC 2005 Web site and meeting agenda, for lining up our corporate sponsors, for coordinating all media communications, and for her efforts in processing the proceedings contributions, to Sherry Hempfling for coordinating the overall SciDAC 2005 meeting planning, for handling a significant share of its associated communications, and for coordinating with the ORNL Conference Center and Grand Hyatt, to Angela Harris for producing many of the documents and records on which our meeting planning was based and for her efforts in coordinating with ORNL Graphics Services, to Angie Beach of the ORNL Conference Center for her efforts in procurement and setting up and executing the contracts with the hotel, and to John Bui and John Smith for their superb wireless networking and A/V set up and support. We are grateful for the relentless efforts of all of these individuals, their remarkable talents, and for the joy of working with them during this past year. They were the cornerstones of SciDAC 2005. Thanks also go to Kymba A'Hearn and Patty Boyd for on-site registration, Brittany Hagen for administrative support, Bruce Johnston for netcast support, Tim Jones for help with the proceedings and Web site, Sherry Lamb for housing and registration, Cindy Lathum for Web site design, Carolyn Peters for on-site registration, and Dami Rich for graphic design. And we would like to express our appreciation to the Oak Ridge National Laboratory, especially Jeff Nichols, the Argonne National Laboratory, the Lawrence Berkeley National Laboratory, and to our corporate sponsors, Cray, IBM, Intel, and SGI, for their support. We would like to extend special thanks also to our plenary speakers, technical speakers, poster presenters, and panelists for all of their efforts on behalf of SciDAC 2005 and for their remarkable achievements and contributions. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas and Margaret Smith of Institute of Physics Publishing, who worked tirelessly in order to provide us with this finished volume within two months, which is nothing short of miraculous. Finally, we wish to express our heartfelt thanks to Michael Strayer, SciDAC Director, whose vision it was to focus SciDAC 2005 on scientific discovery, around which all of the excitement we experienced revolved, and to our DOE SciDAC program managers, especially Fred Johnson, for their support, input, and help throughout.

An investigation of Taiwanese graduate students' level of civic scientific literacy

NASA Astrophysics Data System (ADS)

Lee, Yu-Mei

2003-07-01

Professionals in a variety of disciplines have stressed the importance of advancing the scientific literacy of all citizens in a democratic and science- and technology-based society. Taiwan has been striving hard to advance its democracy and heavily relies on a knowledge-based economy. The high rank Taiwan receives in international comparisons demonstrates Taiwan's high achievement in science at the middle school level. However, no empirical evidence has been collected to examine whether this high achievement at the middle school level promises a high level of scientific literacy in adults. This study investigated the level of scientific literacy of Taiwanese graduate students using Miller's framework of three dimensions of civic scientific literacy, including: (1) a vocabulary of basic scientific constructs, (2) an understanding of the process of scientific inquiry, and (3) some level of understanding of the impact of science and technology on individuals and on society. A web-based questionnaire was employed to survey Taiwanese graduate students studying in three different types of graduate schools and eleven academic fields. A total of 525 responses were collected. In addition, following the survey, eight participants were purposefully selected for individual interviews in order to obtain additional information on participants' scientific literacy. Descriptive statistical analyses were computed to summarize the participants' overall responses to each of the survey sections. Regression models using dummy coding of categorical variables (i.e., gender, school type, and academic areas) were performed to examine whether significant differences exist among different groups. The major findings suggest that: (1) Taiwanese graduate students' civic scientific literacy is not at a satisfactory level; (2) the participants carry mixed attitudes toward science and technology, (3) Taiwanese graduate students are not very attentive to new information of science and technology; (4) all three categorical variables had an impact on the participants' understanding of basic scientific constructs, while only school type had an effect on the participants' understanding of the scientific inquiry process; and (5) the interview results did not support the survey results. The researcher suggests that further studies are required to determine the reasons behind these findings.

Levitating Trains and Kamikaze Genes: Technological Literacy for the Future

NASA Astrophysics Data System (ADS)

Brennan, Richard P.

1994-08-01

A lively survey of the horizons of modern technology. Provides easy-to-read summaries of the state of the art in space science, biotechnology, computer science, exotic energy sources and materials engineering as well as life-enhancing medical advancements and environmental, transportation and defense/weapons technologies. Each chapter explains how a current or future technology works and provides an understanding of the underlying scientific concepts. Includes an extensive self-test to review your knowledge.

Paramedir: A Tool for Programmable Performance Analysis

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Labarta, Jesus; Gimenez, Judit

2004-01-01

Performance analysis of parallel scientific applications is time consuming and requires great expertise in areas such as programming paradigms, system software, and computer hardware architectures. In this paper we describe a tool that facilitates the programmability of performance metric calculations thereby allowing the automation of the analysis and reducing the application development time. We demonstrate how the system can be used to capture knowledge and intuition acquired by advanced parallel programmers in order to be transferred to novice users.

To simulate or not to simulate: what are the questions?

PubMed

Dudai, Yadin; Evers, Kathinka

2014-10-22

Simulation is a powerful method in science and engineering. However, simulation is an umbrella term, and its meaning and goals differ among disciplines. Rapid advances in neuroscience and computing draw increasing attention to large-scale brain simulations. What is the meaning of simulation, and what should the method expect to achieve? We discuss the concept of simulation from an integrated scientific and philosophical vantage point and pinpoint selected issues that are specific to brain simulation.

ISEES: an institute for sustainable software to accelerate environmental science

NASA Astrophysics Data System (ADS)

Jones, M. B.; Schildhauer, M.; Fox, P. A.

2013-12-01

Software is essential to the full science lifecycle, spanning data acquisition, processing, quality assessment, data integration, analysis, modeling, and visualization. Software runs our meteorological sensor systems, our data loggers, and our ocean gliders. Every aspect of science is impacted by, and improved by, software. Scientific advances ranging from modeling climate change to the sequencing of the human genome have been rendered possible in the last few decades due to the massive improvements in the capabilities of computers to process data through software. This pivotal role of software in science is broadly acknowledged, while simultaneously being systematically undervalued through minimal investments in maintenance and innovation. As a community, we need to embrace the creation, use, and maintenance of software within science, and address problems such as code complexity, openness,reproducibility, and accessibility. We also need to fully develop new skills and practices in software engineering as a core competency in our earth science disciplines, starting with undergraduate and graduate education and extending into university and agency professional positions. The Institute for Sustainable Earth and Environmental Software (ISEES) is being envisioned as a community-driven activity that can facilitate and galvanize activites around scientific software in an analogous way to synthesis centers such as NCEAS and NESCent that have stimulated massive advances in ecology and evolution. We will describe the results of six workshops (Science Drivers, Software Lifecycles, Software Components, Workforce Development and Training, Sustainability and Governance, and Community Engagement) that have been held in 2013 to envision such an institute. We will present community recommendations from these workshops and our strategic vision for how ISEES will address the technical issues in the software lifecycle, sustainability of the whole software ecosystem, and the critical issue of computational training for the scientific community. Process for envisioning ISEES.

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.

Extreme Scale Computing to Secure the Nation

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

Brown, D L; McGraw, J R; Johnson, J R

2009-11-10

Since the dawn of modern electronic computing in the mid 1940's, U.S. national security programs have been dominant users of every new generation of high-performance computer. Indeed, the first general-purpose electronic computer, ENIAC (the Electronic Numerical Integrator and Computer), was used to calculate the expected explosive yield of early thermonuclear weapons designs. Even the U. S. numerical weather prediction program, another early application for high-performance computing, was initially funded jointly by sponsors that included the U.S. Air Force and Navy, agencies interested in accurate weather predictions to support U.S. military operations. For the decades of the cold war, national securitymore » requirements continued to drive the development of high performance computing (HPC), including advancement of the computing hardware and development of sophisticated simulation codes to support weapons and military aircraft design, numerical weather prediction as well as data-intensive applications such as cryptography and cybersecurity U.S. national security concerns continue to drive the development of high-performance computers and software in the U.S. and in fact, events following the end of the cold war have driven an increase in the growth rate of computer performance at the high-end of the market. This mainly derives from our nation's observance of a moratorium on underground nuclear testing beginning in 1992, followed by our voluntary adherence to the Comprehensive Test Ban Treaty (CTBT) beginning in 1995. The CTBT prohibits further underground nuclear tests, which in the past had been a key component of the nation's science-based program for assuring the reliability, performance and safety of U.S. nuclear weapons. In response to this change, the U.S. Department of Energy (DOE) initiated the Science-Based Stockpile Stewardship (SBSS) program in response to the Fiscal Year 1994 National Defense Authorization Act, which requires, 'in the absence of nuclear testing, a progam to: (1) Support a focused, multifaceted program to increase the understanding of the enduring stockpile; (2) Predict, detect, and evaluate potential problems of the aging of the stockpile; (3) Refurbish and re-manufacture weapons and components, as required; and (4) Maintain the science and engineering institutions needed to support the nation's nuclear deterrent, now and in the future'. This program continues to fulfill its national security mission by adding significant new capabilities for producing scientific results through large-scale computational simulation coupled with careful experimentation, including sub-critical nuclear experiments permitted under the CTBT. To develop the computational science and the computational horsepower needed to support its mission, SBSS initiated the Accelerated Strategic Computing Initiative, later renamed the Advanced Simulation & Computing (ASC) program (sidebar: 'History of ASC Computing Program Computing Capability'). The modern 3D computational simulation capability of the ASC program supports the assessment and certification of the current nuclear stockpile through calibration with past underground test (UGT) data. While an impressive accomplishment, continued evolution of national security mission requirements will demand computing resources at a significantly greater scale than we have today. In particular, continued observance and potential Senate confirmation of the Comprehensive Test Ban Treaty (CTBT) together with the U.S administration's promise for a significant reduction in the size of the stockpile and the inexorable aging and consequent refurbishment of the stockpile all demand increasing refinement of our computational simulation capabilities. Assessment of the present and future stockpile with increased confidence of the safety and reliability without reliance upon calibration with past or future test data is a long-term goal of the ASC program. This will be accomplished through significant increases in the scientific bases that underlie the computational tools. Computer codes must be developed that replace phenomenology with increased levels of scientific understanding together with an accompanying quantification of uncertainty. These advanced codes will place significantly higher demands on the computing infrastructure than do the current 3D ASC codes. This article discusses not only the need for a future computing capability at the exascale for the SBSS program, but also considers high performance computing requirements for broader national security questions. For example, the increasing concern over potential nuclear terrorist threats demands a capability to assess threats and potential disablement technologies as well as a rapid forensic capability for determining a nuclear weapons design from post-detonation evidence (nuclear counterterrorism).« less

Advances in color science: from retina to behavior

PubMed Central

Chatterjee, Soumya; Field, Greg D.; Horwitz, Gregory D.; Johnson, Elizabeth N.; Koida, Kowa; Mancuso, Katherine

2010-01-01

Color has become a premier model system for understanding how information is processed by neural circuits, and for investigating the relationships among genes, neural circuits and perception. Both the physical stimulus for color and the perceptual output experienced as color are quite well characterized, but the neural mechanisms that underlie the transformation from stimulus to perception are incompletely understood. The past several years have seen important scientific and technical advances that are changing our understanding of these mechanisms. Here, and in the accompanying minisymposium, we review the latest findings and hypotheses regarding color computations in the retina, primary visual cortex and higher-order visual areas, focusing on non-human primates, a model of human color vision. PMID:21068298

Advances in medical image computing.

PubMed

Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

2009-01-01

Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse.

PubMed

Eppig, Janan T

2017-07-01

The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. © The Author 2017. Published by Oxford University Press.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

PubMed Central

Eppig, Janan T.

2017-01-01

Abstract The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. PMID:28838066

The article of the future.

PubMed

Souza, Eliana Pereira Salles de; Cabrera, Eliana Márcia Sotello; Braile, Domingo Marcolino

2010-01-01

Technological advances and the Internet have contributed to the increased disclosure and updating of knowledge and science. Scientific papers are considered the best form of disclosure of information and have been undergoing many changes, not on their way of development, but on the structure of publication. The Future paper, a name for this new structure, uses hypermediatic resources, allowing a quick, easy and organized access to these items online. The exchange of information, comments and criticisms can be performed in real time, providing agility in science disclosure. The trend for the future of documents, both from professionals or enterprises, is the "cloud computing", in which all documents will be developed and updated with the use of various equipments: computer, palm, netbook, ipad, without need to have the software installed on your computer, requiring only an Internet connection.

Preface: SciDAC 2008

NASA Astrophysics Data System (ADS)

Stevens, Rick

2008-07-01

The fourth annual Scientific Discovery through Advanced Computing (SciDAC) Conference was held June 13-18, 2008, in Seattle, Washington. The SciDAC conference series is the premier communitywide venue for presentation of results from the DOE Office of Science's interdisciplinary computational science program. Started in 2001 and renewed in 2006, the DOE SciDAC program is the country's - and arguably the world's - most significant interdisciplinary research program supporting the development of advanced scientific computing methods and their application to fundamental and applied areas of science. SciDAC supports computational science across many disciplines, including astrophysics, biology, chemistry, fusion sciences, and nuclear physics. Moreover, the program actively encourages the creation of long-term partnerships among scientists focused on challenging problems and computer scientists and applied mathematicians developing the technology and tools needed to address those problems. The SciDAC program has played an increasingly important role in scientific research by allowing scientists to create more accurate models of complex processes, simulate problems once thought to be impossible, and analyze the growing amount of data generated by experiments. To help further the research community's ability to tap into the capabilities of current and future supercomputers, Under Secretary for Science, Raymond Orbach, launched the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program in 2003. The INCITE program was conceived specifically to seek out computationally intensive, large-scale research projects with the potential to significantly advance key areas in science and engineering. The program encourages proposals from universities, other research institutions, and industry. During the first two years of the INCITE program, 10 percent of the resources at NERSC were allocated to INCITE awardees. However, demand for supercomputing resources far exceeded available systems; and in 2003, the Office of Science identified increasing computing capability by a factor of 100 as the second priority on its Facilities of the Future list. The goal was to establish leadership-class computing resources to support open science. As a result of a peer reviewed competition, the first leadership computing facility was established at Oak Ridge National Laboratory in 2004. A second leadership computing facility was established at Argonne National Laboratory in 2006. This expansion of computational resources led to a corresponding expansion of the INCITE program. In 2008, Argonne, Lawrence Berkeley, Oak Ridge, and Pacific Northwest national laboratories all provided resources for INCITE. By awarding large blocks of computer time on the DOE leadership computing facilities, the INCITE program enables the largest-scale computations to be pursued. In 2009, INCITE will award over half a billion node-hours of time. The SciDAC conference celebrates progress in advancing science through large-scale modeling and simulation. Over 350 participants attended this year's talks, poster sessions, and tutorials, spanning the disciplines supported by DOE. While the principal focus was on SciDAC accomplishments, this year's conference also included invited presentations and posters from DOE INCITE awardees. Another new feature in the SciDAC conference series was an electronic theater and video poster session, which provided an opportunity for the community to see over 50 scientific visualizations in a venue equipped with many high-resolution large-format displays. To highlight the growing international interest in petascale computing, this year's SciDAC conference included a keynote presentation by Herman Lederer from the Max Planck Institut, one of the leaders of DEISA (Distributed European Infrastructure for Supercomputing Applications) project and a member of the PRACE consortium, Europe's main petascale project. We also heard excellent talks from several European groups, including Laurent Gicquel of CERFACS, who spoke on `Large-Eddy Simulations of Turbulent Reacting Flows of Real Burners: Status and Challenges', and Jean-Francois Hamelin from EDF, who presented a talk on `Getting Ready for Petaflop Capacities and Beyond: A Utility Perspective'. Two other compelling addresses gave attendees a glimpse into the future. Tomas Diaz de la Rubia of Lawrence Livermore National Laboratory spoke on a vision for a fusion/fission hybrid reactor known as the `LIFE Engine' and discussed some of the materials and modeling challenges that need to be overcome to realize the vision for a 1000-year greenhouse-gas-free power source. Dan Reed from Microsoft gave a capstone talk on the convergence of technology, architecture, and infrastructure for cloud computing, data-intensive computing, and exascale computing (1018 flops/sec). High-performance computing is making rapid strides. The SciDAC community's computational resources are expanding dramatically. In the summer of 2008 the first general purpose petascale system (IBM Cell-based RoadRunner at Los Alamos National Laboratory) was recognized in the top 500 list of fastest machines heralding in the dawning of the petascale era. The DOE's leadership computing facility at Argonne reached number three on the Top 500 and is at the moment the most capable open science machine based on an IBM BG/P system with a peak performance of over 550 teraflops/sec. Later this year Oak Ridge is expected to deploy a 1 petaflops/sec Cray XT system. And even before the scientific community has had an opportunity to make significant use of petascale systems, the computer science research community is forging ahead with ideas and strategies for development of systems that may by the end of the next decade sustain exascale performance. Several talks addressed barriers to, and strategies for, achieving exascale capabilities. The last day of the conference was devoted to tutorials hosted by Microsoft Research at a new conference facility in Redmond, Washington. Over 90 people attended the tutorials, which covered topics ranging from an introduction to BG/P programming to advanced numerical libraries. The SciDAC and INCITE programs and the DOE Office of Advanced Scientific Computing Research core program investments in applied mathematics, computer science, and computational and networking facilities provide a nearly optimum framework for advancing computational science for DOE's Office of Science. At a broader level this framework also is benefiting the entire American scientific enterprise. As we look forward, it is clear that computational approaches will play an increasingly significant role in addressing challenging problems in basic science, energy, and environmental research. It takes many people to organize and support the SciDAC conference, and I would like to thank as many of them as possible. The backbone of the conference is the technical program; and the task of selecting, vetting, and recruiting speakers is the job of the organizing committee. I thank the members of this committee for all the hard work and the many tens of conference calls that enabled a wonderful program to be assembled. This year the following people served on the organizing committee: Jim Ahrens, LANL; David Bader, LLNL; Bryan Barnett, Microsoft; Peter Beckman, ANL; Vincent Chan, GA; Jackie Chen, SNL; Lori Diachin, LLNL; Dan Fay, Microsoft; Ian Foster, ANL; Mark Gordon, Ames; Mohammad Khaleel, PNNL; David Keyes, Columbia University; Bob Lucas, University of Southern California; Tony Mezzacappa, ORNL; Jeff Nichols, ORNL; David Nowak, ANL; Michael Papka, ANL; Thomas Schultess, ORNL; Horst Simon, LBNL; David Skinner, LBNL; Panagiotis Spentzouris, Fermilab; Bob Sugar, UCSB; and Kathy Yelick, LBNL. I owe a special thanks to Mike Papka and Jim Ahrens for handling the electronic theater. I also thank all those who submitted videos. It was a highly successful experiment. Behind the scenes an enormous amount of work is required to make a large conference go smoothly. First I thank Cheryl Zidel for her tireless efforts as organizing committee liaison and posters chair and, in general, handling all of my end of the program and keeping me calm. I also thank Gail Pieper for her work in editing the proceedings, Beth Cerny Patino for her work on the Organizing Committee website and electronic theater, and Ken Raffenetti for his work in keeping that website working. Jon Bashor and John Hules did an excellent job in handling conference communications. I thank Caitlin Youngquist for the striking graphic design; Dan Fay for tutorials arrangements; and Lynn Dory, Suzanne Stevenson, Sarah Pebelske and Sarah Zidel for on-site registration and conference support. We all owe Yeen Mankin an extra-special thanks for choosing the hotel, handling contracts, arranging menus, securing venues, and reassuring the chair that everything was under control. We are pleased to have obtained corporate sponsorship from Cray, IBM, Intel, HP, and SiCortex. I thank all the speakers and panel presenters. I also thank the former conference chairs Tony Metzzacappa, Bill Tang, and David Keyes, who were never far away for advice and encouragement. Finally, I offer my thanks to Michael Strayer, without whose leadership, vision, and persistence the SciDAC program would not have come into being and flourished. I am honored to be part of his program and his friend. Rick Stevens Seattle, Washington July 18, 2008

Information Management for a Large Multidisciplinary Project

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Randall, Donald P.; Cronin, Catherine K.

1992-01-01

In 1989, NASA's Langley Research Center (LaRC) initiated the High-Speed Airframe Integration Research (HiSAIR) Program to develop and demonstrate an integrated environment for high-speed aircraft design using advanced multidisciplinary analysis and optimization procedures. The major goals of this program were to evolve the interactions among disciplines and promote sharing of information, to provide a timely exchange of information among aeronautical disciplines, and to increase the awareness of the effects each discipline has upon other disciplines. LaRC historically has emphasized the advancement of analysis techniques. HiSAIR was founded to synthesize these advanced methods into a multidisciplinary design process emphasizing information feedback among disciplines and optimization. Crucial to the development of such an environment are the definition of the required data exchanges and the methodology for both recording the information and providing the exchanges in a timely manner. These requirements demand extensive use of data management techniques, graphic visualization, and interactive computing. HiSAIR represents the first attempt at LaRC to promote interdisciplinary information exchange on a large scale using advanced data management methodologies combined with state-of-the-art, scientific visualization techniques on graphics workstations in a distributed computing environment. The subject of this paper is the development of the data management system for HiSAIR.

Opal web services for biomedical applications.

PubMed

Ren, Jingyuan; Williams, Nadya; Clementi, Luca; Krishnan, Sriram; Li, Wilfred W

2010-07-01

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal's programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239,814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

Use of CAS in secondary school: a factor influencing the transition to university-level mathematics?

NASA Astrophysics Data System (ADS)

Varsavsky, Cristina

2012-01-01

Australian secondary school systems offer three levels of senior (year 12) mathematics studies, none of them compulsory: elementary, intermediate and advanced. The intermediate and advanced studies prepare students for further mathematics studies at university level. In the state of Victoria, there are two versions of intermediate mathematics: one where students learn and are examined with a computer algebra system (CAS) and another where students can only use scientific calculators. This study compares the performance of 1240 students as they transitioned to traditional university-level mathematics and according to whether they learned intermediate mathematics with or without the assistance of a CAS. This study concludes that students without CAS show a slight advantage, but the most important factor affecting student performance is the uptake of advanced-level mathematics studies in secondary school.

History of the numerical aerodynamic simulation program

NASA Technical Reports Server (NTRS)

Peterson, Victor L.; Ballhaus, William F., Jr.

1987-01-01

The Numerical Aerodynamic Simulation (NAS) program has reached a milestone with the completion of the initial operating configuration of the NAS Processing System Network. This achievement is the first major milestone in the continuing effort to provide a state-of-the-art supercomputer facility for the national aerospace community and to serve as a pathfinder for the development and use of future supercomputer systems. The underlying factors that motivated the initiation of the program are first identified and then discussed. These include the emergence and evolution of computational aerodynamics as a powerful new capability in aerodynamics research and development, the computer power required for advances in the discipline, the complementary nature of computation and wind tunnel testing, and the need for the government to play a pathfinding role in the development and use of large-scale scientific computing systems. Finally, the history of the NAS program is traced from its inception in 1975 to the present time.

GPU-Accelerated Molecular Modeling Coming Of Age

PubMed Central

Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

2010-01-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions.

PubMed

Navab, Nassir; Fellow, Miccai; Hennersperger, Christoph; Frisch, Benjamin; Fürst, Bernhard

2016-10-01

In the last decade, many researchers in medical image computing and computer assisted interventions across the world focused on the development of the Virtual Physiological Human (VPH), aiming at changing the practice of medicine from classification and treatment of diseases to that of modeling and treating patients. These projects resulted in major advancements in segmentation, registration, morphological, physiological and biomechanical modeling based on state of art medical imaging as well as other sensory data. However, a major issue which has not yet come into the focus is personalizing intra-operative imaging, allowing for optimal treatment. In this paper, we discuss the personalization of imaging and visualization process with particular focus on satisfying the challenging requirements of computer assisted interventions. We discuss such requirements and review a series of scientific contributions made by our research team to tackle some of these major challenges. Copyright © 2016. Published by Elsevier B.V.

Mind the Gap! A Journey towards Computational Toxicology.

PubMed

Mangiatordi, Giuseppe Felice; Alberga, Domenico; Altomare, Cosimo Damiano; Carotti, Angelo; Catto, Marco; Cellamare, Saverio; Gadaleta, Domenico; Lattanzi, Gianluca; Leonetti, Francesco; Pisani, Leonardo; Stefanachi, Angela; Trisciuzzi, Daniela; Nicolotti, Orazio

2016-09-01

Computational methods have advanced toxicology towards the development of target-specific models based on a clear cause-effect rationale. However, the predictive potential of these models presents strengths and weaknesses. On the good side, in silico models are valuable cheap alternatives to in vitro and in vivo experiments. On the other, the unconscious use of in silico methods can mislead end-users with elusive results. The focus of this review is on the basic scientific and regulatory recommendations in the derivation and application of computational models. Attention is paid to examine the interplay between computational toxicology and drug discovery and development. Avoiding the easy temptation of an overoptimistic future, we report our view on what can, or cannot, realistically be done. Indeed, studies of safety/toxicity represent a key element of chemical prioritization programs carried out by chemical industries, and primarily by pharmaceutical companies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

GPU-accelerated molecular modeling coming of age.

PubMed

Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

2010-09-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

The 1987 RIACS annual report

NASA Technical Reports Server (NTRS)

1987-01-01

The Research Institute for Advanced Computer Science (RIACS) was established at the NASA Ames Research Center in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 64 universities with graduate programs in the aerospace sciences, under several Cooperative Agreements with NASA. RIACS's goal is to provide preeminent leadership in basic and applied computer science research as partners in support of NASA's goals and missions. In pursuit of this goal, RIACS contributes to several of the grand challenges in science and engineering facing NASA: flying an airplane inside a computer; determining the chemical properties of materials under hostile conditions in the atmospheres of earth and the planets; sending intelligent machines on unmanned space missions; creating a one-world network that makes all scientific resources, including those in space, accessible to all the world's scientists; providing intelligent computational support to all stages of the process of scientific investigation from problem formulation to results dissemination; and developing accurate global models for climatic behavior throughout the world. In working with these challenges, we seek novel architectures, and novel ways to use them, that exploit the potential of parallel and distributed computation and make possible new functions that are beyond the current reach of computing machines. The investigation includes pattern computers as well as the more familiar numeric and symbolic computers, and it includes networked systems of resources distributed around the world. We believe that successful computer science research is interdisciplinary: it is driven by (and drives) important problems in other disciplines. We believe that research should be guided by a clear long-term vision with planned milestones. And we believe that our environment must foster and exploit innovation. Our activities and accomplishments for the calendar year 1987 and our plans for 1988 are reported.

Working Group on Virtual Data Integration

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

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

2016-02-04

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

Visualization Techniques in Space and Atmospheric Sciences

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P. (Editor); Bredekamp, Joseph H. (Editor)

1995-01-01

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

NAS Technical Summaries, March 1993 - February 1994

NASA Technical Reports Server (NTRS)

1995-01-01

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefitting other supercomputer centers in government and industry. The 1993-94 operational year concluded with 448 high-speed processor projects and 95 parallel projects representing NASA, the Department of Defense, other government agencies, private industry, and universities. This document provides a glimpse at some of the significant scientific results for the year.

NAS technical summaries. Numerical aerodynamic simulation program, March 1992 - February 1993

NASA Technical Reports Server (NTRS)

1994-01-01

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefitting other supercomputer centers in government and industry. The 1992-93 operational year concluded with 399 high-speed processor projects and 91 parallel projects representing NASA, the Department of Defense, other government agencies, private industry, and universities. This document provides a glimpse at some of the significant scientific results for the year.

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

Opening Remarks: SciDAC 2007

NASA Astrophysics Data System (ADS)

Strayer, Michael

2007-09-01

Good morning. Welcome to Boston, the home of the Red Sox, Celtics and Bruins, baked beans, tea parties, Robert Parker, and SciDAC 2007. A year ago I stood before you to share the legacy of the first SciDAC program and identify the challenges that we must address on the road to petascale computing—a road E E Cummins described as `. . . never traveled, gladly beyond any experience.' Today, I want to explore the preparations for the rapidly approaching extreme scale (X-scale) generation. These preparations are the first step propelling us along the road of burgeoning scientific discovery enabled by the application of X- scale computing. We look to petascale computing and beyond to open up a world of discovery that cuts across scientific fields and leads us to a greater understanding of not only our world, but our universe. As part of the President's America Competitiveness Initiative, the ASCR Office has been preparing a ten year vision for computing. As part of this planning the LBNL together with ORNL and ANL hosted three town hall meetings on Simulation and Modeling at the Exascale for Energy, Ecological Sustainability and Global Security (E3). The proposed E3 initiative is organized around four programmatic themes: Engaging our top scientists, engineers, computer scientists and applied mathematicians; investing in pioneering large-scale science; developing scalable analysis algorithms, and storage architectures to accelerate discovery; and accelerating the build-out and future development of the DOE open computing facilities. It is clear that we have only just started down the path to extreme scale computing. Plan to attend Thursday's session on the out-briefing and discussion of these meetings. The road to the petascale has been at best rocky. In FY07, the continuing resolution provided 12% less money for Advanced Scientific Computing than either the President, the Senate, or the House. As a consequence, many of you had to absorb a no cost extension for your SciDAC work. I am pleased that the President's FY08 budget restores the funding for SciDAC. Quoting from Advanced Scientific Computing Research description in the House Energy and Water Development Appropriations Bill for FY08, "Perhaps no other area of research at the Department is so critical to sustaining U.S. leadership in science and technology, revolutionizing the way science is done and improving research productivity." As a society we need to revolutionize our approaches to energy, environmental and global security challenges. As we go forward along the road to the X-scale generation, the use of computation will continue to be a critical tool along with theory and experiment in understanding the behavior of the fundamental components of nature as well as for fundamental discovery and exploration of the behavior of complex systems. The foundation to overcome these societal challenges will build from the experiences and knowledge gained as you, members of our SciDAC research teams, work together to attack problems at the tera- and peta- scale. If SciDAC is viewed as an experiment for revolutionizing scientific methodology, then a strategic goal of ASCR program must be to broaden the intellectual base prepared to address the challenges of the new X-scale generation of computing. We must focus our computational science experiences gained over the past five years on the opportunities introduced with extreme scale computing. Our facilities are on a path to provide the resources needed to undertake the first part of our journey. Using the newly upgraded 119 teraflop Cray XT system at the Leadership Computing Facility, SciDAC research teams have in three days performed a 100-year study of the time evolution of the atmospheric CO2 concentration originating from the land surface. The simulation of the El Nino/Southern Oscillation which was part of this study has been characterized as `the most impressive new result in ten years' gained new insight into the behavior of superheated ionic gas in the ITER reactor as a result of an AORSA run on 22,500 processors that achieved over 87 trillion calculations per second (87 teraflops) which is 74% of the system's theoretical peak. Tomorrow, Argonne and IBM will announce that the first IBM Blue Gene/P, a 100 teraflop system, will be shipped to the Argonne Leadership Computing Facility later this fiscal year. By the end of FY2007 ASCR high performance and leadership computing resources will include the 114 teraflop IBM Blue Gene/P; a 102 teraflop Cray XT4 at NERSC and a 119 teraflop Cray XT system at Oak Ridge. Before ringing in the New Year, Oak Ridge will upgrade to 250 teraflops with the replacement of the dual core processors with quad core processors and Argonne will upgrade to between 250-500 teraflops, and next year, a petascale Cray Baker system is scheduled for delivery at Oak Ridge. The multidisciplinary teams in our SciDAC Centers for Enabling Technologies and our SciDAC Institutes must continue to work with our Scientific Application teams to overcome the barriers that prevent effective use of these new systems. These challenges include: the need for new algorithms as well as operating system and runtime software and tools which scale to parallel systems composed of hundreds of thousands processors; program development environments and tools which scale effectively and provide ease of use for developers and scientific end users; and visualization and data management systems that support moving, storing, analyzing, manipulating and visualizing multi-petabytes of scientific data and objects. The SciDAC Centers, located primarily at our DOE national laboratories will take the lead in ensuring that critical computer science and applied mathematics issues are addressed in a timely and comprehensive fashion and to address issues associated with research software lifecycle. In contrast, the SciDAC Institutes, which are university-led centers of excellence, will have more flexibility to pursue new research topics through a range of research collaborations. The Institutes will also work to broaden the intellectual and researcher base—conducting short courses and summer schools to take advantage of new high performance computing capabilities. The SciDAC Outreach Center at Lawrence Berkeley National Laboratory complements the outreach efforts of the SciDAC Institutes. The Outreach Center is our clearinghouse for SciDAC activities and resources and will communicate with the high performance computing community in part to understand their needs for workshops, summer schools and institutes. SciDAC is not ASCR's only effort to broaden the computational science community needed to meet the challenges of the new X-scale generation. I hope that you were able to attend the Computational Science Graduate Fellowship poster session last night. ASCR developed the fellowship in 1991 to meet the nation's growing need for scientists and technology professionals with advanced computer skills. CSGF, now jointly funded between ASCR and NNSA, is more than a traditional academic fellowship. It has provided more than 200 of the best and brightest graduate students with guidance, support and community in preparing them as computational scientists. Today CSGF alumni are bringing their diverse top-level skills and knowledge to research teams at DOE laboratories and in industries such as Proctor and Gamble, Lockheed Martin and Intel. At universities they are working to train the next generation of computational scientists. To build on this success, we intend to develop a wholly new Early Career Principal Investigator's (ECPI) program. Our objective is to stimulate academic research in scientific areas within ASCR's purview especially among faculty in early stages of their academic careers. Last February, we lost Ken Kennedy, one of the leading lights of our community. As we move forward into the extreme computing generation, his vision and insight will be greatly missed. In memorial to Ken Kennedy, we shall designate the ECPI grants to beginning faculty in Computer Science as the Ken Kennedy Fellowship. Watch the ASCR website for more information about ECPI and other early career programs in the computational sciences. We look to you, our scientists, researchers, and visionaries to take X-scale computing and use it to explode scientific discovery in your fields. We at SciDAC will work to ensure that this tool is the sharpest and most precise and efficient instrument to carve away the unknown and reveal the most exciting secrets and stimulating scientific discoveries of our time. The partnership between research and computing is the marriage that will spur greater discovery, and as Spencer said to Susan in Robert Parker's novel, `Sudden Mischief', `We stick together long enough, and we may get as smart as hell'. Michael Strayer

Software for visualization, analysis, and manipulation of laser scan images

NASA Astrophysics Data System (ADS)

Burnsides, Dennis B.

1997-03-01

The recent introduction of laser surface scanning to scientific applications presents a challenge to computer scientists and engineers. Full utilization of this two- dimensional (2-D) and three-dimensional (3-D) data requires advances in techniques and methods for data processing and visualization. This paper explores the development of software to support the visualization, analysis and manipulation of laser scan images. Specific examples presented are from on-going efforts at the Air Force Computerized Anthropometric Research and Design (CARD) Laboratory.

Sscience & technology review; Science Technology Review

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

NONE

1996-07-01

This review is published ten times a year to communicate, to a broad audience, Lawrence Livermore National Laboratory`s scientific and technological accomplishments, particularly in the Laboratory`s core mission areas - global security, energy and the environment, and bioscience and biotechnology. This review for the month of July 1996 discusses: Frontiers of research in advanced computations, The multibeam Fabry-Perot velocimeter: Efficient measurement of high velocities, High-tech tools for the American textile industry, and Rock mechanics: can the Tuff take the stress.

Astronomy Aid

NASA Technical Reports Server (NTRS)

1995-01-01

As a Jet Propulsion Laboratory astronomer, John D. Callahan developed a computer program called Multimission Interactive Planner (MIP) to help astronomers analyze scientific and optical data collected on the Voyager's Grand Tour. The commercial version of the program called XonVu is published by XonTech, Inc. Callahan has since developed two more advanced programs based on MIP technology, Grand Tour and Jovian Traveler, which simulate Voyager and Giotto missions. The software allows astronomers and space novices to view the objects seen by the spacecraft, manipulating perspective, distance and field of vision.

Workshop on Advances in Scientific Computation and Differential Equations 󈨡 (SCADE)

DTIC Science & Technology

1994-07-18

STATEMENT ~~’"j’’ Approved for public release; distribution unlimited. I ABSTRACT (MAMMU 200WOMW 94 808 1 64 4.L SUBIECT TERMS Ii11URE Of PAGES 12 16...called differential algebraic ODEs (DAES). (Some important early research on this topic was by L. Petzold.) Both theoretically and in terms of...completely specify the solution. In many physical systems, especially those in biology, or other large scale slowly responding systems, the inclusion of some

Advanced interdisciplinary undergraduate program: light engineering

NASA Astrophysics Data System (ADS)

Bakholdin, Alexey; Bougrov, Vladislav; Voznesenskaya, Anna; Ezhova, Kseniia

2016-09-01

The undergraduate educational program "Light Engineering" of an advanced level of studies is focused on development of scientific learning outcomes and training of professionals, whose activities are in the interdisciplinary fields of Optical engineering and Technical physics. The program gives practical experience in transmission, reception, storage, processing and displaying information using opto-electronic devices, automation of optical systems design, computer image modeling, automated quality control and characterization of optical devices. The program is implemented in accordance with Educational standards of the ITMO University. The specific features of the Program is practice- and problem-based learning implemented by engaging students to perform research and projects, internships at the enterprises and in leading Russian and international research educational centers. The modular structure of the Program and a significant proportion of variable disciplines provide the concept of individual learning for each student. Learning outcomes of the program's graduates include theoretical knowledge and skills in natural science and core professional disciplines, deep knowledge of modern computer technologies, research expertise, design skills, optical and optoelectronic systems and devices.

Predictive models in urology.

PubMed

Cestari, Andrea

2013-01-01

Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.

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

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

Crabtree, George; Glotzer, Sharon; McCurdy, Bill

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

Design Considerations of a Virtual Laboratory for Advanced X-ray Sources

NASA Astrophysics Data System (ADS)

Luginsland, J. W.; Frese, M. H.; Frese, S. D.; Watrous, J. J.; Heileman, G. L.

2004-11-01

The field of scientific computation has greatly advanced in the last few years, resulting in the ability to perform complex computer simulations that can predict the performance of real-world experiments in a number of fields of study. Among the forces driving this new computational capability is the advent of parallel algorithms, allowing calculations in three-dimensional space with realistic time scales. Electromagnetic radiation sources driven by high-voltage, high-current electron beams offer an area to further push the state-of-the-art in high fidelity, first-principles simulation tools. The physics of these x-ray sources combine kinetic plasma physics (electron beams) with dense fluid-like plasma physics (anode plasmas) and x-ray generation (bremsstrahlung). There are a number of mature techniques and software packages for dealing with the individual aspects of these sources, such as Particle-In-Cell (PIC), Magneto-Hydrodynamics (MHD), and radiation transport codes. The current effort is focused on developing an object-oriented software environment using the Rational© Unified Process and the Unified Modeling Language (UML) to provide a framework where multiple 3D parallel physics packages, such as a PIC code (ICEPIC), a MHD code (MACH), and a x-ray transport code (ITS) can co-exist in a system-of-systems approach to modeling advanced x-ray sources. Initial software design and assessments of the various physics algorithms' fidelity will be presented.

MOLAR: Modular Linux and Adaptive Runtime Support for HEC OS/R Research

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

Frank Mueller

2009-02-05

MOLAR is a multi-institution research effort that concentrates on adaptive, reliable,and efficient operating and runtime system solutions for ultra-scale high-end scientific computing on the next generation of supercomputers. This research addresses the challenges outlined by the FAST-OS - forum to address scalable technology for runtime and operating systems --- and HECRTF --- high-end computing revitalization task force --- activities by providing a modular Linux and adaptable runtime support for high-end computing operating and runtime systems. The MOLAR research has the following goals to address these issues. (1) Create a modular and configurable Linux system that allows customized changes based onmore » the requirements of the applications, runtime systems, and cluster management software. (2) Build runtime systems that leverage the OS modularity and configurability to improve efficiency, reliability, scalability, ease-of-use, and provide support to legacy and promising programming models. (3) Advance computer reliability, availability and serviceability (RAS) management systems to work cooperatively with the OS/R to identify and preemptively resolve system issues. (4) Explore the use of advanced monitoring and adaptation to improve application performance and predictability of system interruptions. The overall goal of the research conducted at NCSU is to develop scalable algorithms for high-availability without single points of failure and without single points of control.« less

Review of the synergies between computational modeling and experimental characterization of materials across length scales

DOE PAGES

Dingreville, Rémi; Karnesky, Richard A.; Puel, Guillaume; ...

2015-11-16

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends in which predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure–property relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanicsmore » community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to “simply” support experimental work. This is illustrated by examples from several application areas on structural materials. In conclusion this manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.« less

Parameters that affect parallel processing for computational electromagnetic simulation codes on high performance computing clusters

NASA Astrophysics Data System (ADS)

Moon, Hongsik

What is the impact of multicore and associated advanced technologies on computational software for science? Most researchers and students have multicore laptops or desktops for their research and they need computing power to run computational software packages. Computing power was initially derived from Central Processing Unit (CPU) clock speed. That changed when increases in clock speed became constrained by power requirements. Chip manufacturers turned to multicore CPU architectures and associated technological advancements to create the CPUs for the future. Most software applications benefited by the increased computing power the same way that increases in clock speed helped applications run faster. However, for Computational ElectroMagnetics (CEM) software developers, this change was not an obvious benefit - it appeared to be a detriment. Developers were challenged to find a way to correctly utilize the advancements in hardware so that their codes could benefit. The solution was parallelization and this dissertation details the investigation to address these challenges. Prior to multicore CPUs, advanced computer technologies were compared with the performance using benchmark software and the metric was FLoting-point Operations Per Seconds (FLOPS) which indicates system performance for scientific applications that make heavy use of floating-point calculations. Is FLOPS an effective metric for parallelized CEM simulation tools on new multicore system? Parallel CEM software needs to be benchmarked not only by FLOPS but also by the performance of other parameters related to type and utilization of the hardware, such as CPU, Random Access Memory (RAM), hard disk, network, etc. The codes need to be optimized for more than just FLOPs and new parameters must be included in benchmarking. In this dissertation, the parallel CEM software named High Order Basis Based Integral Equation Solver (HOBBIES) is introduced. This code was developed to address the needs of the changing computer hardware platforms in order to provide fast, accurate and efficient solutions to large, complex electromagnetic problems. The research in this dissertation proves that the performance of parallel code is intimately related to the configuration of the computer hardware and can be maximized for different hardware platforms. To benchmark and optimize the performance of parallel CEM software, a variety of large, complex projects are created and executed on a variety of computer platforms. The computer platforms used in this research are detailed in this dissertation. The projects run as benchmarks are also described in detail and results are presented. The parameters that affect parallel CEM software on High Performance Computing Clusters (HPCC) are investigated. This research demonstrates methods to maximize the performance of parallel CEM software code.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

A Selective Overview of Variable Selection in High Dimensional Feature Space

PubMed Central

Fan, Jianqing

2010-01-01

High dimensional statistical problems arise from diverse fields of scientific research and technological development. Variable selection plays a pivotal role in contemporary statistical learning and scientific discoveries. The traditional idea of best subset selection methods, which can be regarded as a specific form of penalized likelihood, is computationally too expensive for many modern statistical applications. Other forms of penalized likelihood methods have been successfully developed over the last decade to cope with high dimensionality. They have been widely applied for simultaneously selecting important variables and estimating their effects in high dimensional statistical inference. In this article, we present a brief account of the recent developments of theory, methods, and implementations for high dimensional variable selection. What limits of the dimensionality such methods can handle, what the role of penalty functions is, and what the statistical properties are rapidly drive the advances of the field. The properties of non-concave penalized likelihood and its roles in high dimensional statistical modeling are emphasized. We also review some recent advances in ultra-high dimensional variable selection, with emphasis on independence screening and two-scale methods. PMID:21572976

Science and technology integration for increased human potential and societal outcomes.

PubMed

Roco, Mihail C

2004-05-01

Unifying science based on the material unity of nature at the nanoscale provides a new foundation for knowledge, innovation, and integration of technology. Revolutionary and synergistic advances at the interfaces between previously separated fields of science, engineering and areas of relevance are ready to create nano-bio-info-cogno (NBIC) transforming tools. Developments in systems approach, mathematics, and computation in conjunction with NBIC allow us to understand the natural world and scientific research as closely coupled, complex, hierarchical entities. At this unique moment of scientific and technical achievement, improvement of human performance at individual and group levels, as well as development of suitable revolutionary products, becomes possible and these are primary goals for converging new technologies. NBIC addresses long-term advances in key areas of human activity, including working, learning, aging, group interaction, organizations, and human evolution ((Roco and Bainbridge, 2003)). Fundamentally new tools, technologies, and products will be integrated into individual and social human architecture. This introductory chapter of the Annals outlines research and education trends, funding activities, and the potential of development of revolutionary products and services.

Advanced IR sensing technology research in the city of Tomsk, USSR

NASA Astrophysics Data System (ADS)

Vavilov, Vladimir P.; Ivanov, A. I.; Isakov, A. V.; Reino, V. V.; Shiryaev, Vladimir V.; Tsvyk, Ruvim S.

1990-03-01

Some large scientific organisations in the city of Tomsk, Siberia, USSR are involved into the researchings on the advanced IR sensing technology. They are Polytechnic Institute founded in 1896, Uriiversity of Tomsk founded in 1888, Institute of Atmosphere's Optics, Academy of Sciences arid Institute of Automatized Control Systems and Radio electronics. Main fields are as follows: 1) thermal (IR) nondestructive testing of materials, machines and systems; 2) optoelectronics; 3) laser optics, transmission of infrared through the atmosphere and investigation of energy distribution in laser beams. Researching equipment includes Western and Russian industrial thermovisers, lasers, personal computers, IR detectors etc and some borne-made devices and components. There are optical arid JR detectors Lndustry in Tomsk that allows i.e produce spheric and aspheric mirrors and lenses, JR filters, cadmium-mercury-teilur and indium anlymonide T1 receivers arid to develop the scanning and measuring devices on the base mentioned above. Seine projects to develop the specific Tomsk thermoviser so far have nOt come true so the main accent was made onto the computerized thermographic systems suitable for solution of particular scientific problems.

A Freeware Path to Neutron Computed Tomography

NASA Astrophysics Data System (ADS)

Schillinger, Burkhard; Craft, Aaron E.

Neutron computed tomography has become a routine method at many neutron sources due to the availability of digital detection systems, powerful computers and advanced software. The commercial packages Octopus by Inside Matters and VGStudio by Volume Graphics have been established as a quasi-standard for high-end computed tomography. However, these packages require a stiff investment and are available to the users only on-site at the imaging facility to do their data processing. There is a demand from users to have image processing software at home to do further data processing; in addition, neutron computed tomography is now being introduced even at smaller and older reactors. Operators need to show a first working tomography setup before they can obtain a budget to build an advanced tomography system. Several packages are available on the web for free; however, these have been developed for X-rays or synchrotron radiation and are not immediately useable for neutron computed tomography. Three reconstruction packages and three 3D-viewers have been identified and used even for Gigabyte datasets. This paper is not a scientific publication in the classic sense, but is intended as a review to provide searchable help to make the described packages usable for the tomography community. It presents the necessary additional preprocessing in ImageJ, some workarounds for bugs in the software, and undocumented or badly documented parameters that need to be adapted for neutron computed tomography. The result is a slightly complicated, but surprisingly high-quality path to neutron computed tomography images in 3D, but not a replacement for the even more powerful commercial software mentioned above.

THE VIRTUAL INSTRUMENT: SUPPORT FOR GRID-ENABLED MCELL SIMULATIONS

PubMed Central

Casanova, Henri; Berman, Francine; Bartol, Thomas; Gokcay, Erhan; Sejnowski, Terry; Birnbaum, Adam; Dongarra, Jack; Miller, Michelle; Ellisman, Mark; Faerman, Marcio; Obertelli, Graziano; Wolski, Rich; Pomerantz, Stuart; Stiles, Joel

2010-01-01

Ensembles of widely distributed, heterogeneous resources, or Grids, have emerged as popular platforms for large-scale scientific applications. In this paper we present the Virtual Instrument project, which provides an integrated application execution environment that enables end-users to run and interact with running scientific simulations on Grids. This work is performed in the specific context of MCell, a computational biology application. While MCell provides the basis for running simulations, its capabilities are currently limited in terms of scale, ease-of-use, and interactivity. These limitations preclude usage scenarios that are critical for scientific advances. Our goal is to create a scientific “Virtual Instrument” from MCell by allowing its users to transparently access Grid resources while being able to steer running simulations. In this paper, we motivate the Virtual Instrument project and discuss a number of relevant issues and accomplishments in the area of Grid software development and application scheduling. We then describe our software design and report on the current implementation. We verify and evaluate our design via experiments with MCell on a real-world Grid testbed. PMID:20689618

A survey of GPU-based medical image computing techniques

PubMed Central

Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming

2012-01-01

Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080

Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

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

Jin, Yier

As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from thismore » project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.« less

Enabling campus grids with open science grid technology

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

Weitzel, Derek; Bockelman, Brian; Swanson, David

2011-01-01

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

A Computational framework for telemedicine.

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

Foster, I.; von Laszewski, G.; Thiruvathukal, G. K.

1998-07-01

Emerging telemedicine applications require the ability to exploit diverse and geographically distributed resources. Highspeed networks are used to integrate advanced visualization devices, sophisticated instruments, large databases, archival storage devices, PCs, workstations, and supercomputers. This form of telemedical environment is similar to networked virtual supercomputers, also known as metacomputers. Metacomputers are already being used in many scientific application areas. In this article, we analyze requirements necessary for a telemedical computing infrastructure and compare them with requirements found in a typical metacomputing environment. We will show that metacomputing environments can be used to enable a more powerful and unified computational infrastructure formore » telemedicine. The Globus metacomputing toolkit can provide the necessary low level mechanisms to enable a large scale telemedical infrastructure. The Globus toolkit components are designed in a modular fashion and can be extended to support the specific requirements for telemedicine.« less

End-to-end Cyberinfrastructure and Data Services for Earth System Science Education and Research: Unidata's Plans and Directions

NASA Astrophysics Data System (ADS)

Ramamurthy, M.

2005-12-01

A revolution is underway in the role played by cyberinfrastructure and data services in the conduct of research and education. We live in an era of an unprecedented data volume from diverse sources, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. For example, modern remote-sensing systems like hyperspectral satellite instruments generate terabytes of data each day. Environmental problems such as global change and water cycle transcend disciplinary as well as geographic boundaries, and their solution requires integrated earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing new pedagogical techniques such as enquiry-based learning and hands-on activities. Needless to add, today's education and research enterprise depends heavily on robust, flexible and scalable cyberinfrastructure, especially on the ready availability of quality data and appropriate tools to manipulate and integrate those data. Fortuitously, rapid advances in computing and communication technologies have also revolutionized how data, tools and services are being incorporated into the teaching and scientific enterprise. The exponential growth in the use of the Internet in education and research, largely due to the advent of the World Wide Web, is by now well documented. On the other hand, how some of the other technological and community trends that have shaped the use of cyberinfrastructure, especially data services, is less well understood. For example, the computing industry is converging on an approach called Web services that enables a standard and yet revolutionary way of building applications and methods to connect and exchange information over the Web. This new approach, based on XML - a widely accepted format for exchanging data and corresponding semantics over the Internet - enables applications, computer systems, and information processes to work together in a fundamentally different way. Likewise, the advent of digital libraries, grid computing platforms, interoperable frameworks, standards and protocols, open-source software, and community atmospheric models have been important drivers in shaping the use of a new generation of end-to-end cyberinfrastructure for solving some of the most challenging scientific and educational problems. In this talk, I will present an overview of the scientific, technological, and educational drivers and discuss recent developments in cyberinfrastructure and Unidata's role and directions in providing robust, end-to-end data services for solving geoscientific problems and advancing student learning.

End-to-end Cyberinfrastructure and Data Services for Earth System Science Education and Research: A vision for the future

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.

2006-05-01

We live in an era of an unprecedented data volumes, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. For instance, a new generation of satellite instruments is being designed for GOES-R and NPOESS programs to deliver terabytes of data each day. Similarly, high-resolution, coupled models run over a wide range of temporal scales are generating data at unprecedented rates. Complex environmental problems such as El Nino/Southern Oscillation, climate change, and water cycle transcend not only disciplinary but also geographic boundaries, with their impacts and implications touching every region and community of the world. The understanding and solution to these inherently global scientific and social problems requires integrated observations that cover all areas of the globe, international sharing and flow of data, and earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing new pedagogical techniques such as enquiry-based learning and hands-on activities. Needless to add, today's education and research enterprise depends heavily on easy to use, robust, flexible and scalable cyberinfrastructure, especially on the ready availability of quality data and appropriate tools to manipulate and integrate those data. Fortunately, rapid advances in computing, communication and information technologies have provided solutions that can are being applied to advance teaching, research, and service. The exponential growth in the use of the Internet in education and research, largely due to the advent of the World Wide Web, is well documented. On the other hand, how other technological and community trends have shaped the development and application of cyberinfrastructure, especially in the data services area, is less well understood. For example, the computing industry is converging on an approach called Web services that enables a standard and yet revolutionary way of building applications and methods to connect and exchange information over the Web. This new approach, based on XML - a widely accepted format for exchanging data and corresponding semantics over the Internet - enables applications, computer systems, and information processes to work together in fundamentally different ways. Likewise, the advent of digital libraries, grid computing platforms, interoperable frameworks, standards and protocols, open-source software, and community atmospheric models have been important drivers in shaping the use of a new generation of end-to-end cyberinfrastructure for solving some of the most challenging scientific and educational problems. In this talk, I will present an overview of the scientific, technological, and educational landscape, discuss recent developments in cyberinfrastructure, and Unidata's role in and vision for providing easy-to use, robust, end-to-end data services for solving geoscientific problems and advancing student learning.

Transitioning Rationally Designed Catalytic Materials to Real 'Working' Catalysts Produced at Commercial Scale: Nanoparticle Materials

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

Schaidle, Joshua A.; Habas, Susan E.; Baddour, Frederick G.

Catalyst design, from idea to commercialization, requires multi-disciplinary scientific and engineering research and development over 10-20 year time periods. Historically, the identification of new or improved catalyst materials has largely been an empirical trial-and-error process. However, advances in computational capabilities (new tools and increased processing power) coupled with new synthetic techniques have started to yield rationally-designed catalysts with controlled nano-structures and tailored properties. This technological advancement represents an opportunity to accelerate the catalyst development timeline and to deliver new materials that outperform existing industrial catalysts or enable new applications, once a number of unique challenges associated with the scale-up ofmore » nano-structured materials are overcome.« less

Spinoff 2011

NASA Technical Reports Server (NTRS)

2012-01-01

Topics include: Bioreactors Drive Advances in Tissue Engineering; Tooling Techniques Enhance Medical Imaging; Ventilator Technologies Sustain Critically Injured Patients; Protein Innovations Advance Drug Treatments, Skin Care; Mass Analyzers Facilitate Research on Addiction; Frameworks Coordinate Scientific Data Management; Cameras Improve Navigation for Pilots, Drivers; Integrated Design Tools Reduce Risk, Cost; Advisory Systems Save Time, Fuel for Airlines; Modeling Programs Increase Aircraft Design Safety; Fly-by-Wire Systems Enable Safer, More Efficient Flight; Modified Fittings Enhance Industrial Safety; Simulation Tools Model Icing for Aircraft Design; Information Systems Coordinate Emergency Management; Imaging Systems Provide Maps for U.S. Soldiers; High-Pressure Systems Suppress Fires in Seconds; Alloy-Enhanced Fans Maintain Fresh Air in Tunnels; Control Algorithms Charge Batteries Faster; Software Programs Derive Measurements from Photographs; Retrofits Convert Gas Vehicles into Hybrids; NASA Missions Inspire Online Video Games; Monitors Track Vital Signs for Fitness and Safety; Thermal Components Boost Performance of HVAC Systems; World Wind Tools Reveal Environmental Change; Analyzers Measure Greenhouse Gasses, Airborne Pollutants; Remediation Technologies Eliminate Contaminants; Receivers Gather Data for Climate, Weather Prediction; Coating Processes Boost Performance of Solar Cells; Analyzers Provide Water Security in Space and on Earth; Catalyst Substrates Remove Contaminants, Produce Fuel; Rocket Engine Innovations Advance Clean Energy; Technologies Render Views of Earth for Virtual Navigation; Content Platforms Meet Data Storage, Retrieval Needs; Tools Ensure Reliability of Critical Software; Electronic Handbooks Simplify Process Management; Software Innovations Speed Scientific Computing; Controller Chips Preserve Microprocessor Function; Nanotube Production Devices Expand Research Capabilities; Custom Machines Advance Composite Manufacturing; Polyimide Foams Offer Superior Insulation; Beam Steering Devices Reduce Payload Weight; Models Support Energy-Saving Microwave Technologies; Materials Advance Chemical Propulsion Technology; and High-Temperature Coatings Offer Energy Savings.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

Breast Biopsy System

NASA Technical Reports Server (NTRS)

1994-01-01

Charge Coupled Devices (CCDs) are high technology silicon chips that connect light directly into electronic or digital images, which can be manipulated or enhanced by computers. When Goddard Space Flight Center (GSFC) scientists realized that existing CCD technology could not meet scientific requirements for the Hubble Space Telescope Imagining Spectrograph, GSFC contracted with Scientific Imaging Technologies, Inc. (SITe) to develop an advanced CCD. SITe then applied many of the NASA-driven enhancements to the manufacture of CCDs for digital mammography. The resulting device images breast tissue more clearly and efficiently. The LORAD Stereo Guide Breast Biopsy system incorporates SITe's CCD as part of a digital camera system that is replacing surgical biopsy in many cases. Known as stereotactic needle biopsy, it is performed under local anesthesia with a needle and saves women time, pain, scarring, radiation exposure and money.

Data Access, Interoperability and Sustainability: Key Challenges for the Evolution of Science Capabilities

NASA Astrophysics Data System (ADS)

Walton, A. L.

2015-12-01

In 2016, the National Science Foundation (NSF) will support a portfolio of activities and investments focused upon challenges in data access, interoperability, and sustainability. These topics are fundamental to science questions of increasing complexity that require multidisciplinary approaches and expertise. Progress has become tractable because of (and sometimes complicated by) unprecedented growth in data (both simulations and observations) and rapid advances in technology (such as instrumentation in all aspects of the discovery process, together with ubiquitous cyberinfrastructure to connect, compute, visualize, store, and discover). The goal is an evolution of capabilities for the research community based on these investments, scientific priorities, technology advances, and policies. Examples from multiple NSF directorates, including investments by the Advanced Cyberinfrastructure Division, are aimed at these challenges and can provide the geosciences research community with models and opportunities for participation. Implications for the future are highlighted, along with the importance of continued community engagement on key issues.

Computing at the speed limit (supercomputers)

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

Bernhard, R.

1982-07-01

The author discusses how unheralded efforts in the United States, mainly in universities, have removed major stumbling blocks to building cost-effective superfast computers for scientific and engineering applications within five years. These computers would have sustained speeds of billions of floating-point operations per second (flops), whereas with the fastest machines today the top sustained speed is only 25 million flops, with bursts to 160 megaflops. Cost-effective superfast machines can be built because of advances in very large-scale integration and the special software needed to program the new machines. VLSI greatly reduces the cost per unit of computing power. The developmentmore » of such computers would come at an opportune time. Although the US leads the world in large-scale computer technology, its supremacy is now threatened, not surprisingly, by the Japanese. Publicized reports indicate that the Japanese government is funding a cooperative effort by commercial computer manufacturers to develop superfast computers-about 1000 times faster than modern supercomputers. The US computer industry, by contrast, has balked at attempting to boost computer power so sharply because of the uncertain market for the machines and the failure of similar projects in the past to show significant results.« less

Collaborative Visualization Project: shared-technology learning environments for science learning

NASA Astrophysics Data System (ADS)

Pea, Roy D.; Gomez, Louis M.

1993-01-01

Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.

Nuclear Physics Exascale Requirements Review: An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Nuclear Physics, June 15 - 17, 2016, Gaithersburg, Maryland

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

Carlson, Joseph; Savage, Martin J.; Gerber, Richard

Imagine being able to predict — with unprecedented accuracy and precision — the structure of the proton and neutron, and the forces between them, directly from the dynamics of quarks and gluons, and then using this information in calculations of the structure and reactions of atomic nuclei and of the properties of dense neutron stars (NSs). Also imagine discovering new and exotic states of matter, and new laws of nature, by being able to collect more experimental data than we dream possible today, analyzing it in real time to feed back into an experiment, and curating the data with fullmore » tracking capabilities and with fully distributed data mining capabilities. Making this vision a reality would improve basic scientific understanding, enabling us to precisely calculate, for example, the spectrum of gravity waves emitted during NS coalescence, and would have important societal applications in nuclear energy research, stockpile stewardship, and other areas. This review presents the components and characteristics of the exascale computing ecosystems necessary to realize this vision.« less

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

Enabling scientific workflows in virtual reality

USGS Publications Warehouse

Kreylos, O.; Bawden, G.; Bernardin, T.; Billen, M.I.; Cowgill, E.S.; Gold, R.D.; Hamann, B.; Jadamec, M.; Kellogg, L.H.; Staadt, O.G.; Sumner, D.Y.

2006-01-01

To advance research and improve the scientific return on data collection and interpretation efforts in the geosciences, we have developed methods of interactive visualization, with a special focus on immersive virtual reality (VR) environments. Earth sciences employ a strongly visual approach to the measurement and analysis of geologic data due to the spatial and temporal scales over which such data ranges, As observations and simulations increase in size and complexity, the Earth sciences are challenged to manage and interpret increasing amounts of data. Reaping the full intellectual benefits of immersive VR requires us to tailor exploratory approaches to scientific problems. These applications build on the visualization method's strengths, using both 3D perception and interaction with data and models, to take advantage of the skills and training of the geological scientists exploring their data in the VR environment. This interactive approach has enabled us to develop a suite of tools that are adaptable to a range of problems in the geosciences and beyond. Copyright ?? 2008 by the Association for Computing Machinery, Inc.

The End of the Rainbow? Color Schemes for Improved Data Graphics

NASA Astrophysics Data System (ADS)

Light, Adam; Bartlein, Patrick J.

2004-10-01

Modern computer displays and printers enable the widespread use of color in scientific communication, but the expertise for designing effective graphics has not kept pace with the technology for producing them. Historically, even the most prestigious publications have tolerated high defect rates in figures and illustrations, and technological advances that make creating and reproducing graphics easier do not appear to have decreased the frequency of errors. Flawed graphics consequently beget more flawed graphics as authors emulate published examples. Color has the potential to enhance communication, but design mistakes can result in color figures that are less effective than gray scale displays of the same data. Empirical research on human subjects can build a fundamental understanding of visual perception and scientific methods can be used to evaluate existing designs, but creating effective data graphics is a design task and not fundamentally a scientific pursuit. Like writing well, creating good data graphics requires a combination of formal knowledge and artistic sensibility tempered by experience: a combination of ``substance, statistics, and design''.

Study of Fluid Experiment System (FES)/CAST/Holographic Ground System (HGS)

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Cummings, Rick; Jones, Brian

1992-01-01

The use of holographic and schlieren optical techniques for studying the concentration gradients in solidification processes has been used by several investigators over the years. The HGS facility at MSFC has been primary resource in researching this capability. Consequently, scientific personnel have been able to utilize these techniques in both ground based research and in space experiments. An important event in the scientific utilization of the HGS facilities was the TGS Crystal Growth and the casting and solidification technology (CAST) experiments that were flown on the International Microgravity Laboratory (IML) mission in March of this year. The preparation and processing of these space observations are the primary experiments reported in this work. This project provides some ground-based studies to optimize on the holographic techniques used to acquire information about the crystal growth processes flown on IML. Since the ground-based studies will be compared with the space-based experimental results, it is necessary to conduct sufficient ground based studies to best determine how the experiment worked in space. The current capabilities in computer based systems for image processing and numerical computation have certainly assisted in those efforts. As anticipated, this study has certainly shown that these advanced computing capabilities are helpful in the data analysis of such experiments.

Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft

NASA Technical Reports Server (NTRS)

Kifle, Muli; Andro, Monty; Tran, Quang K.; Fujikawa, Gene; Chu, Pong P.

2003-01-01

Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.

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

PubMed

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

2017-01-01

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

Intelligent Microscopes: Recent And Near-Future Advances

NASA Astrophysics Data System (ADS)

Prewitt, Judith M. S.

1980-02-01

Robert Hooke conjectured about fluid circulation in plants as well as in animals in Micrographia in a passage that is equally important as a commentary on the dependence, not of technology on science, but of science on technology: It seems very probable that Nature has ... very many appropriated instruments and contrivances, whereby to bring her designs and end to pass, which 'tis not improbable but that some diligent observer, if helped with better Microscopes, may in time detect.This paper, written in the form of a scientific poem, reviews the current and near- future state-of-the-art of automated intelligent microscopes based on computer science and technology. The basic concepts of computer intelligence for cytology and histology are presented and elaborated. Limitations of commercial devices and research proto- types are examined (Dx), and remedies are suggested (Rx). The course of action pro- posed and being undertaken constitutes an original contribution toward advancing the state-of-the-science, in the hope of advancing the state-of-the-art of medicine.With rapid, contemporary advances in both science and technology, it may now be appropriate to modify Hooke's passage:It seems very probable that Nature has ... very many appropriated instruments and contrivances, whereby to bring her designs and end to pass, which 'tis not improbable but that some diligent observer, if helped with Intelligent Microscopes, may in time detect.

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

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

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

Parallel algorithms for mapping pipelined and parallel computations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

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

Geveci, Berk; Maynard, Robert

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respectivemore » features into a new visualization toolkit called VTK-m.« less

The dual frontier: Patented inventions and prior scientific advance.

PubMed

Ahmadpoor, Mohammad; Jones, Benjamin F

2017-08-11

The extent to which scientific advances support marketplace inventions is largely unknown. We study 4.8 million U.S. patents and 32 million research articles to determine the minimum citation distance between patented inventions and prior scientific advances. We find that most cited research articles (80%) link forward to a future patent. Similarly, most patents (61%) link backward to a prior research article. Linked papers and patents typically stand 2 to 4 degrees distant from the other domain. Yet, advances directly along the patent-paper boundary are notably more impactful within their own domains. The distance metric further provides a typology of the fields, institutions, and individuals involved in science-to-technology linkages. Overall, the findings are consistent with theories that emphasize substantial and fruitful connections between patenting and prior scientific inquiry. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

OPENING REMARKS: Scientific Discovery through Advanced Computing

NASA Astrophysics Data System (ADS)

Strayer, Michael

2006-01-01

Good morning. Welcome to SciDAC 2006 and Denver. I share greetings from the new Undersecretary for Energy, Ray Orbach. Five years ago SciDAC was launched as an experiment in computational science. The goal was to form partnerships among science applications, computer scientists, and applied mathematicians to take advantage of the potential of emerging terascale computers. This experiment has been a resounding success. SciDAC has emerged as a powerful concept for addressing some of the biggest challenges facing our world. As significant as these successes were, I believe there is also significance in the teams that achieved them. In addition to their scientific aims these teams have advanced the overall field of computational science and set the stage for even larger accomplishments as we look ahead to SciDAC-2. I am sure that many of you are expecting to hear about the results of our current solicitation for SciDAC-2. I’m afraid we are not quite ready to make that announcement. Decisions are still being made and we will announce the results later this summer. Nearly 250 unique proposals were received and evaluated, involving literally thousands of researchers, postdocs, and students. These collectively requested more than five times our expected budget. This response is a testament to the success of SciDAC in the community. In SciDAC-2 our budget has been increased to about 70 million for FY 2007 and our partnerships have expanded to include the Environment and National Security missions of the Department. The National Science Foundation has also joined as a partner. These new partnerships are expected to expand the application space of SciDAC, and broaden the impact and visibility of the program. We have, with our recent solicitation, expanded to turbulence, computational biology, and groundwater reactive modeling and simulation. We are currently talking with the Department’s applied energy programs about risk assessment, optimization of complex systems - such as the national and regional electricity grid, carbon sequestration, virtual engineering, and the nuclear fuel cycle. The successes of the first five years of SciDAC have demonstrated the power of using advanced computing to enable scientific discovery. One measure of this success could be found in the President’s State of the Union address in which President Bush identified ‘supercomputing’ as a major focus area of the American Competitiveness Initiative. Funds were provided in the FY 2007 President’s Budget request to increase the size of the NERSC-5 procurement to between 100-150 teraflops, to upgrade the LCF Cray XT3 at Oak Ridge to 250 teraflops and acquire a 100 teraflop IBM BlueGene/P to establish the Leadership computing facility at Argonne. We believe that we are on a path to establish a petascale computing resource for open science by 2009. We must develop software tools, packages, and libraries as well as the scientific application software that will scale to hundreds of thousands of processors. Computer scientists from universities and the DOE’s national laboratories will be asked to collaborate on the development of the critical system software components such as compilers, light-weight operating systems and file systems. Standing up these large machines will not be business as usual for ASCR. We intend to develop a series of interconnected projects that identify cost, schedule, risks, and scope for the upgrades at the LCF at Oak Ridge, the establishment of the LCF at Argonne, and the development of the software to support these high-end computers. The critical first step in defining the scope of the project is to identify a set of early application codes for each leadership class computing facility. These codes will have access to the resources during the commissioning phase of the facility projects and will be part of the acceptance tests for the machines. Applications will be selected, in part, by breakthrough science, scalability, and ability to exercise key hardware and software components. Possible early applications might include climate models; studies of the magnetic properties of nanoparticles as they relate to ultra-high density storage media; the rational design of chemical catalysts, the modeling of combustion processes that will lead to cleaner burning coal, and fusion and astrophysics research. I have presented just a few of the challenges that we look forward to on the road to petascale computing. Our road to petascale science might be paraphrased by the quote from e e cummings, ‘somewhere I have never traveled, gladly beyond any experience . . .’

Advancing Systems Biology in the International Conference on Intelligent Biology and Medicine (ICIBM) 2015.

PubMed

Zhao, Zhongming; Liu, Yunlong; Huang, Yufei; Huang, Kun; Ruan, Jianhua

2016-08-26

The 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) was held on November 13-15, 2015 in Indianapolis, Indiana, USA. ICIBM 2015 included eight scientific sessions, three tutorial sessions, one poster session, and four keynote presentations that covered the frontier research in broad areas related to bioinformatics, systems biology, big data science, biomedical informatics, pharmacogenomics, and intelligent computing. Here, we present a summary of the 10 research articles that were selected from ICIBM 2015 and included in the supplement to BMC Systems Biology.

Community detection in complex networks using proximate support vector clustering

NASA Astrophysics Data System (ADS)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

Lobachevsky Year at Kazan University: Center of Science, Education, Intellectual-Cognitive Tourism "Kazan - GeoNa - 2020+" and "Kazan-Moon-2020+" projects

NASA Astrophysics Data System (ADS)

Gusev, A.; Trudkova, N.

2017-09-01

Center "GeoNa" will enable scientists and teachers of the Russian universities to join to advanced achievements of a science, information technologies; to establish scientific communications with foreign colleagues in sphere of the high technology, educational projects and Intellectual-Cognitive Tourism. The Project "Kazan - Moon - 2020+" is directed on the decision of fundamental problems of celestial mechanics, selenodesy and geophysics of the Moon(s) connected to carrying out of complex theoretical researches and computer modelling.

Joint the Center for Applied Scientific Computing

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

Gamblin, Todd; Bremer, Timo; Van Essen, Brian

The Center for Applied Scientific Computing serves as Livermore Lab’s window to the broader computer science, computational physics, applied mathematics, and data science research communities. In collaboration with academic, industrial, and other government laboratory partners, we conduct world-class scientific research and development on problems critical to national security. CASC applies the power of high-performance computing and the efficiency of modern computational methods to the realms of stockpile stewardship, cyber and energy security, and knowledge discovery for intelligence applications.

A blueprint for demonstrating quantum supremacy with superconducting qubits.

PubMed

Neill, C; Roushan, P; Kechedzhi, K; Boixo, S; Isakov, S V; Smelyanskiy, V; Megrant, A; Chiaro, B; Dunsworth, A; Arya, K; Barends, R; Burkett, B; Chen, Y; Chen, Z; Fowler, A; Foxen, B; Giustina, M; Graff, R; Jeffrey, E; Huang, T; Kelly, J; Klimov, P; Lucero, E; Mutus, J; Neeley, M; Quintana, C; Sank, D; Vainsencher, A; Wenner, J; White, T C; Neven, H; Martinis, J M

2018-04-13

A key step toward demonstrating a quantum system that can address difficult problems in physics and chemistry will be performing a computation beyond the capabilities of any classical computer, thus achieving so-called quantum supremacy. In this study, we used nine superconducting qubits to demonstrate a promising path toward quantum supremacy. By individually tuning the qubit parameters, we were able to generate thousands of distinct Hamiltonian evolutions and probe the output probabilities. The measured probabilities obey a universal distribution, consistent with uniformly sampling the full Hilbert space. As the number of qubits increases, the system continues to explore the exponentially growing number of states. Extending these results to a system of 50 qubits has the potential to address scientific questions that are beyond the capabilities of any classical computer. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Enabling large-scale viscoelastic calculations via neural network acceleration

NASA Astrophysics Data System (ADS)

Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.

2017-12-01

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics (LQCD)

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

Negele, John W.

Building on the success of two preceding generations of Scientific Discovery through Advanced Computing (SciDAC) projects, this grant supported the MIT component (P.I. John Negele) of a multi-institutional SciDAC-3 project that also included Brookhaven National Laboratory, the lead laboratory with P. I. Frithjof Karsch serving as Project Director, Thomas Jefferson National Accelerator Facility with P. I. David Richards serving as Co-director, University of Washington with P. I. Martin Savage, University of North Carolina with P. I. Rob Fowler, and College of William and Mary with P. I. Andreas Stathopoulos. Nationally, this multi-institutional project coordinated the software development effort that themore » nuclear physics lattice QCD community needs to ensure that lattice calculations can make optimal use of forthcoming leadership-class and dedicated hardware, including that at the national laboratories, and to exploit future computational resources in the Exascale era.« less

Statistical Methodologies to Integrate Experimental and Computational Research

NASA Technical Reports Server (NTRS)

Parker, P. A.; Johnson, R. T.; Montgomery, D. C.

2008-01-01

Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.

ISMB 2016 offers outstanding science, networking, and celebration

PubMed Central

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392

ISMB 2016 offers outstanding science, networking, and celebration.

PubMed

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

SPIRE, the ``Spin Triangle'': Athens, Hamburg, Buenos Aires: Advancing Nanospintronics and Nanomagnetism

NASA Astrophysics Data System (ADS)

Smith, Arthur R.

2012-02-01

Future technological advances at the frontier of `elec'tronics will increasingly rely on the use of the spin property of the electron at ever smaller length scales. As a result, it is critical to make substantial efforts towards understanding and ultimately controlling spin and magnetism at the nanoscale. In SPIRE, the goal is to achieve these important scientific advancements through a unique combination of experimental and theoretical techniques, as well as complementary expertise and coherent efforts across three continents. The key experimental tool of choice is spin-polarized scanning tunneling microscopy -- the premier method for accessing the spin structure of surfaces and nanostructures with resolution down to the atomic scale. At the same time, atom and molecule deposition and manipulation schemes are added in order to both atomically engineer, and precisely investigate, novel nanoscale spin structures. These efforts are being applied to an array of physical systems, including single magnetic atomic layers, self-assembled 2-D molecular arrays, single adatoms and molecules, and alloyed spintronic materials. Efforts are aimed at exploring complex spin structures and phenomena occurring in these systems. At the same time, the problems are approached, and in some cases guided, by the use of leading theoretical tools, including analytical approaches such as renormalization group theory, and computational approaches such as first principles density functional theory. The scientific goals of the project are achieved by a collaborative effort with the international partners, engaging students at all levels who, through their research experiences both at home and abroad, gain international research outlooks as well as understandings of cultural differences, by working on intriguing problems of mutual interest. A novel scientific journalism internship program based at Ohio University furthers the project's broader impacts.

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.

Laboratory directed research and development fy1999 annual report

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

Al-Ayat, R A

2000-04-11

The Lawrence Livermore National Laboratory (LLNL) was founded in 1952 and has been managed since its inception by the University of California (UC) for the U.S. Department of Energy (DOE). Because of this long association with UC, the Laboratory has been able to recruit a world-class workforce, establish an atmosphere of intellectual freedom and innovation, and achieve recognition in relevant fields of knowledge as a scientific and technological leader. This environment and reputation are essential for sustained scientific and technical excellence. As a DOE national laboratory with about 7,000 employees, LLNL has an essential and compelling primary mission to ensuremore » that the nation's nuclear weapons remain safe, secure, and reliable and to prevent the spread and use of nuclear weapons worldwide. The Laboratory receives funding from the DOE Assistant Secretary for Defense Programs, whose focus is stewardship of our nuclear weapons stockpile. Funding is also provided by the Deputy Administrator for Defense Nuclear Nonproliferation, many Department of Defense sponsors, other federal agencies, and the private sector. As a multidisciplinary laboratory, LLNL has applied its considerable skills in high-performance computing, advanced engineering, and the management of large research and development projects to become the science and technology leader in those areas of its mission responsibility. The Laboratory Directed Research and Development (LDRD) Program was authorized by the U.S. Congress in 1984. The Program allows the Director of each DOE laboratory to fund advanced, creative, and innovative research and development (R&D) activities that will ensure scientific and technical vitality in the continually evolving mission areas at DOE and the Laboratory. In addition, the LDRD Program provides LLNL with the flexibility to nurture and enrich essential scientific and technical competencies, which attract the most qualified scientists and engineers. The LDRD Program also enables many collaborations with the scientific community in academia, national and international laboratories, and industry. The projects in the FY1999 LDRD portfolio were carefully selected to continue vigorous support of the strategic vision and the long-term goals of DOE and the Laboratory. Projects chosen for LDRD funding undergo stringent selection processes, which look for high-potential scientific return, emphasize strategic relevance, and feature technical peer reviews by external and internal experts. The FY1999 projects described in this annual report focus on supporting the Laboratory's national security needs: stewardship of the U.S. nuclear weapons stockpile, responsibility for the counter- and nonproliferation of weapons of mass destruction, development of high-performance computing, and support of DOE environmental research and waste management programs. In the past, LDRD investments have significantly enhanced LLNL scientific capabilities and greatly contributed to the Laboratory's ability to meet its national security programmatic requirements. Examples of past investments include technical precursors to the Accelerated Strategic Computing Initiative (ASCI), special-materials processing and characterization, and biodefense. Our analysis of the FY1999 portfolio shows that it strongly supports the Laboratory's national security mission. About 95% of the LDRD dollars have directly supported LLNL's national security activities in FY1999, which far exceeds the portion of LLNL's overall budget supported by National Security Programs, which is 63% for FY1999.« less

L3 Interactive Data Language

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

Hohn, Michael; Adams, Paul

2006-09-05

The L3 system is a computational steering environment for image processing and scientific computing. It consists of an interactive graphical language and interface. Its purpose is to help advanced users in controlling their computational software and assist in the management of data accumulated during numerical experiments. L3 provides a combination of features not found in other environments; these are: - textual and graphical construction of programs - persistence of programs and associated data - direct mapping between the scripts, the parameters, and the produced data - implicit hierarchial data organization - full programmability, including conditionals and functions - incremental executionmore » of programs The software includes the l3 language and the graphical environment. The language is a single-assignment functional language; the implementation consists of lexer, parser, interpreter, storage handler, and editing support, The graphical environment is an event-driven nested list viewer/editor providing graphical elements corresponding to the language. These elements are both the represenation of a users program and active interfaces to the values computed by that program.« less

From Interfaces to Bulk: Experimental-Computational Studies Across Time and Length Scales of Multi-Functional Ionic Polymers

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

Perahia, Dvora; Grest, Gary S.

Neutron experiments coupled with computational components have resulted in unprecedented understanding of the factors that impact the behavior of ionic structured polymers. Additionally, new computational tools to study macromolecules, were developed. In parallel, this DOE funding have enabled the education of the next generation of material researchers who are able to take the advantage neutron tools offer to the understanding and design of advanced materials. Our research has provided unprecedented insight into one of the major factors that limits the use of ionizable polymers, combining the macroscopic view obtained from the experimental techniques with molecular insight extracted from computational studiesmore » leading to transformative knowledge that will impact the design of nano-structured, materials. With the focus on model systems, of broad interest to the scientific community and to industry, the research addressed challenges that cut across a large number of polymers, independent of the specific chemical structure or the transported species.« less

High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

PubMed

Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

Scientific developments of liquid crystal-based optical memory: a review

NASA Astrophysics Data System (ADS)

Prakash, Jai; Chandran, Achu; Biradar, Ashok M.

2017-01-01

The memory behavior in liquid crystals (LCs), although rarely observed, has made very significant headway over the past three decades since their discovery in nematic type LCs. It has gone from a mere scientific curiosity to application in variety of commodities. The memory element formed by numerous LCs have been protected by patents, and some commercialized, and used as compensation to non-volatile memory devices, and as memory in personal computers and digital cameras. They also have the low cost, large area, high speed, and high density memory needed for advanced computers and digital electronics. Short and long duration memory behavior for industrial applications have been obtained from several LC materials, and an LC memory with interesting features and applications has been demonstrated using numerous LCs. However, considerable challenges still exist in searching for highly efficient, stable, and long-lifespan materials and methods so that the development of useful memory devices is possible. This review focuses on the scientific and technological approach of fascinating applications of LC-based memory. We address the introduction, development status, novel design and engineering principles, and parameters of LC memory. We also address how the amalgamation of LCs could bring significant change/improvement in memory effects in the emerging field of nanotechnology, and the application of LC memory as the active component for futuristic and interesting memory devices.

Scientific developments of liquid crystal-based optical memory: a review.

PubMed

Prakash, Jai; Chandran, Achu; Biradar, Ashok M

2017-01-01

The memory behavior in liquid crystals (LCs), although rarely observed, has made very significant headway over the past three decades since their discovery in nematic type LCs. It has gone from a mere scientific curiosity to application in variety of commodities. The memory element formed by numerous LCs have been protected by patents, and some commercialized, and used as compensation to non-volatile memory devices, and as memory in personal computers and digital cameras. They also have the low cost, large area, high speed, and high density memory needed for advanced computers and digital electronics. Short and long duration memory behavior for industrial applications have been obtained from several LC materials, and an LC memory with interesting features and applications has been demonstrated using numerous LCs. However, considerable challenges still exist in searching for highly efficient, stable, and long-lifespan materials and methods so that the development of useful memory devices is possible. This review focuses on the scientific and technological approach of fascinating applications of LC-based memory. We address the introduction, development status, novel design and engineering principles, and parameters of LC memory. We also address how the amalgamation of LCs could bring significant change/improvement in memory effects in the emerging field of nanotechnology, and the application of LC memory as the active component for futuristic and interesting memory devices.

A Primer on Observational Measurement.

PubMed

Girard, Jeffrey M; Cohn, Jeffrey F

2016-08-01

Observational measurement plays an integral role in a variety of scientific endeavors within biology, psychology, sociology, education, medicine, and marketing. The current article provides an interdisciplinary primer on observational measurement; in particular, it highlights recent advances in observational methodology and the challenges that accompany such growth. First, we detail the various types of instrument that can be used to standardize measurements across observers. Second, we argue for the importance of validity in observational measurement and provide several approaches to validation based on contemporary validity theory. Third, we outline the challenges currently faced by observational researchers pertaining to measurement drift, observer reactivity, reliability analysis, and time/expense. Fourth, we describe recent advances in computer-assisted measurement, fully automated measurement, and statistical data analysis. Finally, we identify several key directions for future observational research to explore.

78 FR 24223 - National Center for Advancing Translational Sciences; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-24

... Advancing Translational Sciences; Notice of Closed Meeting Pursuant to section 10(d) of the Federal Advisory... clearly unwarranted invasion of personal privacy. Name of Committee: National Center for Advancing...: Barbara J. Nelson, Ph.D., Scientific Review Officer, Office of Grants Management & Scientific Review...

Cognitive Implications of Nominalizations in the Advancement of Scientific Discourse

ERIC Educational Resources Information Center

Bello, Iria

2016-01-01

Nominalizations are well-known features of scientific writing. Scholars have been intrigued by their form and by their functions. While these features have been widely studied, the cognitive side of nominalizations in scientific texts still needs further attention. Nominalizations contribute to the advancement of discourse and at the same time add…

Climate Models

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.

2012-01-01

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

Community Capacity Building as a vital mechanism for enhancing the growth and efficacy of a sustainable scientific software ecosystem: experiences running a real-time bi-coastal "Open Science for Synthesis" Training Institute for young Earth and Environmental scientists

NASA Astrophysics Data System (ADS)

Schildhauer, M.; Jones, M. B.; Bolker, B.; Lenhardt, W. C.; Hampton, S. E.; Idaszak, R.; Rebich Hespanha, S.; Ahalt, S.; Christopherson, L.

2014-12-01

Continuing advances in computational capabilities, access to Big Data, and virtual collaboration technologies are creating exciting new opportunities for accomplishing Earth science research at finer resolutions, with much broader scope, using powerful modeling and analytical approaches that were unachievable just a few years ago. Yet, there is a perceptible lag in the abilities of the research community to capitalize on these new possibilities, due to lacking the relevant skill-sets, especially with regards to multi-disciplinary and integrative investigations that involve active collaboration. UC Santa Barbara's National Center for Ecological Analysis and Synthesis (NCEAS), and the University of North Carolina's Renaissance Computing Institute (RENCI), were recipients of NSF OCI S2I2 "Conceptualization awards", charged with helping define the needs of the research community relative to enabling science and education through "sustained software infrastructure". Over the course of our activities, a consistent request from Earth scientists was for "better training in software that enables more effective, reproducible research." This community-based feedback led to creation of an "Open Science for Synthesis" Institute— a innovative, three-week, bi-coastal training program for early career researchers. We provided a mix of lectures, hands-on exercises, and working group experience on topics including: data discovery and preservation; code creation, management, sharing, and versioning; scientific workflow documentation and reproducibility; statistical and machine modeling techniques; virtual collaboration mechanisms; and methods for communicating scientific results. All technologies and quantitative tools presented were suitable for advancing open, collaborative, and reproducible synthesis research. In this talk, we will report on the lessons learned from running this ambitious training program, that involved coordinating classrooms among two remote sites, and included developing original synthesis research activities as part of the course. We also report on the feedback provided by participants as to the learning approaches and topical issues they found most engaging, and why.

Scientific Visualization & Modeling for Earth Systems Science Education

NASA Technical Reports Server (NTRS)

Chaudhury, S. Raj; Rodriguez, Waldo J.

2003-01-01

Providing research experiences for undergraduate students in Earth Systems Science (ESS) poses several challenges at smaller academic institutions that might lack dedicated resources for this area of study. This paper describes the development of an innovative model that involves students with majors in diverse scientific disciplines in authentic ESS research. In studying global climate change, experts typically use scientific visualization techniques applied to remote sensing data collected by satellites. In particular, many problems related to environmental phenomena can be quantitatively addressed by investigations based on datasets related to the scientific endeavours such as the Earth Radiation Budget Experiment (ERBE). Working with data products stored at NASA's Distributed Active Archive Centers, visualization software specifically designed for students and an advanced, immersive Virtual Reality (VR) environment, students engage in guided research projects during a structured 6-week summer program. Over the 5-year span, this program has afforded the opportunity for students majoring in biology, chemistry, mathematics, computer science, physics, engineering and science education to work collaboratively in teams on research projects that emphasize the use of scientific visualization in studying the environment. Recently, a hands-on component has been added through science student partnerships with school-teachers in data collection and reporting for the GLOBE Program (GLobal Observations to Benefit the Environment).

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2014-01-01

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

Nonlinear three-dimensional verification of the SPECYL and PIXIE3D magnetohydrodynamics codes for fusion plasmas

NASA Astrophysics Data System (ADS)

Bonfiglio, D.; Chacón, L.; Cappello, S.

2010-08-01

With the increasing impact of scientific discovery via advanced computation, there is presently a strong emphasis on ensuring the mathematical correctness of computational simulation tools. Such endeavor, termed verification, is now at the center of most serious code development efforts. In this study, we address a cross-benchmark nonlinear verification study between two three-dimensional magnetohydrodynamics (3D MHD) codes for fluid modeling of fusion plasmas, SPECYL [S. Cappello and D. Biskamp, Nucl. Fusion 36, 571 (1996)] and PIXIE3D [L. Chacón, Phys. Plasmas 15, 056103 (2008)], in their common limit of application: the simple viscoresistive cylindrical approximation. SPECYL is a serial code in cylindrical geometry that features a spectral formulation in space and a semi-implicit temporal advance, and has been used extensively to date for reversed-field pinch studies. PIXIE3D is a massively parallel code in arbitrary curvilinear geometry that features a conservative, solenoidal finite-volume discretization in space, and a fully implicit temporal advance. The present study is, in our view, a first mandatory step in assessing the potential of any numerical 3D MHD code for fluid modeling of fusion plasmas. Excellent agreement is demonstrated over a wide range of parameters for several fusion-relevant cases in both two- and three-dimensional geometries.

Nonlinear three-dimensional verification of the SPECYL and PIXIE3D magnetohydrodynamics codes for fusion plasmas

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

Bonfiglio, Daniele; Chacon, Luis; Cappello, Susanna

2010-01-01

With the increasing impact of scientific discovery via advanced computation, there is presently a strong emphasis on ensuring the mathematical correctness of computational simulation tools. Such endeavor, termed verification, is now at the center of most serious code development efforts. In this study, we address a cross-benchmark nonlinear verification study between two three-dimensional magnetohydrodynamics (3D MHD) codes for fluid modeling of fusion plasmas, SPECYL [S. Cappello and D. Biskamp, Nucl. Fusion 36, 571 (1996)] and PIXIE3D [L. Chacon, Phys. Plasmas 15, 056103 (2008)], in their common limit of application: the simple viscoresistive cylindrical approximation. SPECYL is a serial code inmore » cylindrical geometry that features a spectral formulation in space and a semi-implicit temporal advance, and has been used extensively to date for reversed-field pinch studies. PIXIE3D is a massively parallel code in arbitrary curvilinear geometry that features a conservative, solenoidal finite-volume discretization in space, and a fully implicit temporal advance. The present study is, in our view, a first mandatory step in assessing the potential of any numerical 3D MHD code for fluid modeling of fusion plasmas. Excellent agreement is demonstrated over a wide range of parameters for several fusion-relevant cases in both two- and three-dimensional geometries.« less

Scientific Workflows + Provenance = Better (Meta-)Data Management

NASA Astrophysics Data System (ADS)

Ludaescher, B.; Cuevas-Vicenttín, V.; Missier, P.; Dey, S.; Kianmajd, P.; Wei, Y.; Koop, D.; Chirigati, F.; Altintas, I.; Belhajjame, K.; Bowers, S.

2013-12-01

The origin and processing history of an artifact is known as its provenance. Data provenance is an important form of metadata that explains how a particular data product came about, e.g., how and when it was derived in a computational process, which parameter settings and input data were used, etc. Provenance information provides transparency and helps to explain and interpret data products. Other common uses and applications of provenance include quality control, data curation, result debugging, and more generally, 'reproducible science'. Scientific workflow systems (e.g. Kepler, Taverna, VisTrails, and others) provide controlled environments for developing computational pipelines with built-in provenance support. Workflow results can then be explained in terms of workflow steps, parameter settings, input data, etc. using provenance that is automatically captured by the system. Scientific workflows themselves provide a user-friendly abstraction of the computational process and are thus a form of ('prospective') provenance in their own right. The full potential of provenance information is realized when combining workflow-level information (prospective provenance) with trace-level information (retrospective provenance). To this end, the DataONE Provenance Working Group (ProvWG) has developed an extension of the W3C PROV standard, called D-PROV. Whereas PROV provides a 'least common denominator' for exchanging and integrating provenance information, D-PROV adds new 'observables' that described workflow-level information (e.g., the functional steps in a pipeline), as well as workflow-specific trace-level information ( timestamps for each workflow step executed, the inputs and outputs used, etc.) Using examples, we will demonstrate how the combination of prospective and retrospective provenance provides added value in managing scientific data. The DataONE ProvWG is also developing tools based on D-PROV that allow scientists to get more mileage from provenance metadata. DataONE is a federation of member nodes that store data and metadata for discovery and access. By enriching metadata with provenance information, search and reuse of data is enhanced, and the 'social life' of data (being the product of many workflow runs, different people, etc.) is revealed. We are currently prototyping a provenance repository (PBase) to demonstrate what can be achieved with advanced provenance queries. The ProvExplorer and ProPub tools support advanced ad-hoc querying and visualization of provenance as well as customized provenance publications (e.g., to address privacy issues, or to focus provenance to relevant details). In a parallel line of work, we are exploring ways to add provenance support to widely-used scripting platforms (e.g. R and Python) and then expose that information via D-PROV.

Evolution and convergence of the patterns of international scientific collaboration.

PubMed

Coccia, Mario; Wang, Lili

2016-02-23

International research collaboration plays an important role in the social construction and evolution of science. Studies of science increasingly analyze international collaboration across multiple organizations for its impetus in improving research quality, advancing efficiency of the scientific production, and fostering breakthroughs in a shorter time. However, long-run patterns of international research collaboration across scientific fields and their structural changes over time are hardly known. Here we show the convergence of international scientific collaboration across research fields over time. Our study uses a dataset by the National Science Foundation and computes the fraction of papers that have international institutional coauthorships for various fields of science. We compare our results with pioneering studies carried out in the 1970s and 1990s by applying a standardization method that transforms all fractions of internationally coauthored papers into a comparable framework. We find, over 1973-2012, that the evolution of collaboration patterns across scientific disciplines seems to generate a convergence between applied and basic sciences. We also show that the general architecture of international scientific collaboration, based on the ranking of fractions of international coauthorships for different scientific fields per year, has tended to be unchanged over time, at least until now. Overall, this study shows, to our knowledge for the first time, the evolution of the patterns of international scientific collaboration starting from initial results described by literature in the 1970s and 1990s. We find a convergence of these long-run collaboration patterns between the applied and basic sciences. This convergence might be one of contributing factors that supports the evolution of modern scientific fields.

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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.

Application of infrared thermography in computer aided diagnosis

NASA Astrophysics Data System (ADS)

Faust, Oliver; Rajendra Acharya, U.; Ng, E. Y. K.; Hong, Tan Jen; Yu, Wenwei

2014-09-01

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care.

Whole earth modeling: developing and disseminating scientific software for computational geophysics.

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2016-12-01

Historically, a great deal of specialized scientific software for modeling and data analysis has been developed by individual researchers or small groups of scientists working on their own specific research problems. As the magnitude of available data and computer power has increased, so has the complexity of scientific problems addressed by computational methods, creating both a need to sustain existing scientific software, and expand its development to take advantage of new algorithms, new software approaches, and new computational hardware. To that end, communities like the Computational Infrastructure for Geodynamics (CIG) have been established to support the use of best practices in scientific computing for solid earth geophysics research and teaching. Working as a scientific community enables computational geophysicists to take advantage of technological developments, improve the accuracy and performance of software, build on prior software development, and collaborate more readily. The CIG community, and others, have adopted an open-source development model, in which code is developed and disseminated by the community in an open fashion, using version control and software repositories like Git. One emerging issue is how to adequately identify and credit the intellectual contributions involved in creating open source scientific software. The traditional method of disseminating scientific ideas, peer reviewed publication, was not designed for review or crediting scientific software, although emerging publication strategies such software journals are attempting to address the need. We are piloting an integrated approach in which authors are identified and credited as scientific software is developed and run. Successful software citation requires integration with the scholarly publication and indexing mechanisms as well, to assign credit, ensure discoverability, and provide provenance for software.

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, Esmond; Evans, Katherine J.; Caldwell, Peter

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, E.; Evans, K.; Caldwell, P.

This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Computation Directorate Annual Report 2003

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

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

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

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Advances in the Remote Monitoring of Balloon Flights

NASA Astrophysics Data System (ADS)

Breeding, S.

At the National Scientific Balloon Facility (NSBF), we must staff the Long Duration Balloon (LDB) control center 24 hours a day during LDB flights. This requires three daily shifts of two operators (balloon control and tdrss scheduling). In addition to this we also have one engineer on-call as LDB Lead to resolve technical issues and one manager on-call for flight management. These on-call periods are typically 48 to 72 hours in length. In the past the on-call staff had to travel to the LDB control center in order to monitor the status of a flight in any detail. This becomes problematic as flight durations push out beyond 20 to 30 day lengths, as these staff members are not available for business travel during these periods. This paper describes recent advances which allow for the remote monitoring of scientific balloon flight ground station computer displays. This allows balloon flight managers and lead engineers to check flight status and performance from any location with a network or telephone connection. This capability frees key personnel from the NSBF base during flights. It also allows other interested parties to check on the flight status at their convenience.

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

Wu, Chase Qishi; Zhu, Michelle Mengxia

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

PREFACE: 9th World Congress on Computational Mechanics and 4th Asian Pacific Congress on Computational Mechanics

NASA Astrophysics Data System (ADS)

Khalili, N.; Valliappan, S.; Li, Q.; Russell, A.

2010-07-01

The use for mathematical models of natural phenomena has underpinned science and engineering for centuries, but until the advent of modern computers and computational methods, the full utility of most of these models remained outside the reach of the engineering communities. Since World War II, advances in computational methods have transformed the way engineering and science is undertaken throughout the world. Today, theories of mechanics of solids and fluids, electromagnetism, heat transfer, plasma physics, and other scientific disciplines are implemented through computational methods in engineering analysis, design, manufacturing, and in studying broad classes of physical phenomena. The discipline concerned with the application of computational methods is now a key area of research, education, and application throughout the world. In the early 1980's, the International Association for Computational Mechanics (IACM) was founded to promote activities related to computational mechanics and has made impressive progress. The most important scientific event of IACM is the World Congress on Computational Mechanics. The first was held in Austin (USA) in 1986 and then in Stuttgart (Germany) in 1990, Chiba (Japan) in 1994, Buenos Aires (Argentina) in 1998, Vienna (Austria) in 2002, Beijing (China) in 2004, Los Angeles (USA) in 2006 and Venice, Italy; in 2008. The 9th World Congress on Computational Mechanics is held in conjunction with the 4th Asian Pacific Congress on Computational Mechanics under the auspices of Australian Association for Computational Mechanics (AACM), Asian Pacific Association for Computational Mechanics (APACM) and International Association for Computational Mechanics (IACM). The 1st Asian Pacific Congress was in Sydney (Australia) in 2001, then in Beijing (China) in 2004 and Kyoto (Japan) in 2007. The WCCM/APCOM 2010 publications consist of a printed book of abstracts given to delegates, along with 247 full length peer reviewed papers published with free access online in IOP Conference Series: Materials Science and Engineering. The editors acknowledge the help of the paper reviewers in maintaining a high standard of assessment and the co-operation of the authors in complying with the requirements of the editors and the reviewers. We also would like to take this opportunity to thank the members of the Local Organising Committee and the International Scientific Committee for helping make WCCM/APCOM 2010 a successful event. We also thank The University of New South Wales, The University of Newcastle, the Centre for Infrastructure Engineering and Safety (CIES), IACM, APCAM, AACM for their financial support, along with the United States Association for Computational Mechanics for the Travel Awards made available. N. Khalili S. Valliappan Q. Li A. Russell 19 July 2010 Sydney, Australia

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.

Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus.

PubMed

Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

2015-02-15

Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains and three-dimensional protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL). dkovats@iscb.org or rost@in.tum.de. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

2008 ALCF annual report.

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

Drugan, C.

2009-12-07

The word 'breakthrough' aptly describes the transformational science and milestones achieved at the Argonne Leadership Computing Facility (ALCF) throughout 2008. The number of research endeavors undertaken at the ALCF through the U.S. Department of Energy's (DOE) Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program grew from 9 in 2007 to 20 in 2008. The allocation of computer time awarded to researchers on the Blue Gene/P also spiked significantly - from nearly 10 million processor hours in 2007 to 111 million in 2008. To support this research, we expanded the capabilities of Intrepid, an IBM Blue Gene/P systemmore » at the ALCF, to 557 teraflops (TF) for production use. Furthermore, we enabled breakthrough levels of productivity and capability in visualization and data analysis with Eureka, a powerful installation of NVIDIA Quadro Plex S4 external graphics processing units. Eureka delivered a quantum leap in visual compute density, providing more than 111 TF and more than 3.2 terabytes of RAM. On April 21, 2008, the dedication of the ALCF realized DOE's vision to bring the power of the Department's high performance computing to open scientific research. In June, the IBM Blue Gene/P supercomputer at the ALCF debuted as the world's fastest for open science and third fastest overall. No question that the science benefited from this growth and system improvement. Four research projects spearheaded by Argonne National Laboratory computer scientists and ALCF users were named to the list of top ten scientific accomplishments supported by DOE's Advanced Scientific Computing Research (ASCR) program. Three of the top ten projects used extensive grants of computing time on the ALCF's Blue Gene/P to model the molecular basis of Parkinson's disease, design proteins at atomic scale, and create enzymes. As the year came to a close, the ALCF was recognized with several prestigious awards at SC08 in November. We provided resources for Linear Scaling Divide-and-Conquer Electronic Structure Calculations for Thousand Atom Nanostructures, a collaborative effort between Argonne, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory that received the ACM Gordon Bell Prize Special Award for Algorithmic Innovation. The ALCF also was named a winner in two of the four categories in the HPC Challenge best performance benchmark competition.« less

Integrating Data Base into the Elementary School Science Program.

ERIC Educational Resources Information Center

Schlenker, Richard M.

This document describes seven science activities that combine scientific principles and computers. The objectives for the activities are to show students how the computer can be used as a tool to store and arrange scientific data, provide students with experience using the computer as a tool to manage scientific data, and provide students with…

Analysis Report for Exascale Storage Requirements for Scientific Data.

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

Ruwart, Thomas M.

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

A high performance scientific cloud computing environment for materials simulations

NASA Astrophysics Data System (ADS)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

PubMed Central

Ahmed, Zeeshan; Dandekar, Thomas

2018-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool ‘Mining Scientific Literature (MSL)’, which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system’s output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format. PMID:29721305

Predicting Cost/Performance Trade-Offs for Whitney: A Commodity Computing Cluster

NASA Technical Reports Server (NTRS)

Becker, Jeffrey C.; Nitzberg, Bill; VanderWijngaart, Rob F.; Kutler, Paul (Technical Monitor)

1997-01-01

Recent advances in low-end processor and network technology have made it possible to build a "supercomputer" out of commodity components. We develop simple models of the NAS Parallel Benchmarks version 2 (NPB 2) to explore the cost/performance trade-offs involved in building a balanced parallel computer supporting a scientific workload. We develop closed form expressions detailing the number and size of messages sent by each benchmark. Coupling these with measured single processor performance, network latency, and network bandwidth, our models predict benchmark performance to within 30%. A comparison based on total system cost reveals that current commodity technology (200 MHz Pentium Pros with 100baseT Ethernet) is well balanced for the NPBs up to a total system cost of around $1,000,000.

The computation in diagnostics for tokamaks: systems, designs, approaches

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał; Linczuk, Paweł; Czarski, Tomasz; Wojeński, Andrzej; Chernyshova, Maryna; Poźniak, Krzysztof; Kolasiński, Piotr; Kasprowicz, Grzegorz; Zabołotny, Wojciech; Kowalska-Strzeciwilk, Ewa; Malinowski, Karol; Gaska, Michał

2017-08-01

The requirements given for GEM (Gaseous Electron Multiplier) detector based acquisition system for plasma impurities diagnostics triggered a need for the development of a specialized software and hardware architecture. The amount of computations with latency and throughput restrictions cause that an advanced solution is sought for. In order to provide a mechanism fitting the designated tokamaks, an insight into existing solutions was necessary. In the article there is discussed architecture of systems used for plasma diagnostics and in related scientific fields. The developed solution is compared and contrasted with other diagnostic and control systems. Particular attention is payed to specific requirements for plasma impurities diagnostics in tokamak thermal fusion reactor. Subsequently, the details are presented that justified the choice of the system architecture and the discussion on various approaches is given.

Xarray: multi-dimensional data analysis in Python

NASA Astrophysics Data System (ADS)

Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

2017-04-01

xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.

A Look at the Impact of High-End Computing Technologies on NASA Missions

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Dunbar, Jill; Hardman, John; Bailey, F. Ron; Wheeler, Lorien; Rogers, Stuart

2012-01-01

From its bold start nearly 30 years ago and continuing today, the NASA Advanced Supercomputing (NAS) facility at Ames Research Center has enabled remarkable breakthroughs in the space agency s science and engineering missions. Throughout this time, NAS experts have influenced the state-of-the-art in high-performance computing (HPC) and related technologies such as scientific visualization, system benchmarking, batch scheduling, and grid environments. We highlight the pioneering achievements and innovations originating from and made possible by NAS resources and know-how, from early supercomputing environment design and software development, to long-term simulation and analyses critical to design safe Space Shuttle operations and associated spinoff technologies, to the highly successful Kepler Mission s discovery of new planets now capturing the world s imagination.

Reducing the Requirements and Cost of Astronomical Telescopes

NASA Technical Reports Server (NTRS)

Smith, W. Scott; Whitakter, Ann F. (Technical Monitor)

2002-01-01

Limits on astronomical telescope apertures are being rapidly approached. These limits result from logistics, increasing complexity, and finally budgetary constraints. In an historical perspective, great strides have been made in the area of aperture, adaptive optics, wavefront sensors, detectors, stellar interferometers and image reconstruction. What will be the next advances? Emerging data analysis techniques based on communication theory holds the promise of yielding more information from observational data based on significant computer post-processing. This paper explores some of the current telescope limitations and ponders the possibilities increasing the yield of scientific data based on the migration computer post-processing techniques to higher dimensions. Some of these processes hold the promise of reducing the requirements on the basic telescope hardware making the next generation of instruments more affordable.

Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

ERIC Educational Resources Information Center

Pallant, Amy; Lee, Hee-Sun

2015-01-01

Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation…

Parallel processing for scientific computations

NASA Technical Reports Server (NTRS)

Alkhatib, Hasan S.

1995-01-01

The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

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.

University of Rochester, Laboratory for Laser Energetics

NASA Astrophysics Data System (ADS)

1987-01-01

In FY86 the Laboratory has produced a list of accomplishments in which it takes pride. LLE has met every laser-fusion program milestone to date in a program of research for direct-drive ultraviolet laser fusion originally formulated in 1981. LLE scientists authored or co-authored 135 scientific papers during 1985 to 1986. The collaborative experiments with NRL, LANL, and LLNL have led to a number of important ICF results. The cryogenic target system developed by KMS Fusion for LLE will be used in future high-density experiments on OMEGA to demonstrate the compression of thermonuclear fuel to 100 to 200 times that of solid (20 to 40 g/cm) in a test of the direct-drive concept, as noted in the National Academy of Sciences' report. The excellence of the advanced technology efforts at LLE is illustrated by the establishment of the Ultrafast Science Center by the Department of Defense through the Air Force Office of Scientific Research. Research in the Center will concentrate on bridging the gap between high-speed electronics and ultrafast optics by providing education, research, and development in areas critical to future communications and high-speed computer systems. The Laboratory for Laser Energetics continues its pioneering work on the interaction of intense radiation with matter. This includes inertial-fusion and advanced optical and optical electronics research; training people in the technology and applications of high-power, short-pulse lasers; and interacting with the scientific community, business, industry, and government to promote the growth of laser technology.

Grid computing technology for hydrological applications

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

Using Java for distributed computing in the Gaia satellite data processing

NASA Astrophysics Data System (ADS)

O'Mullane, William; Luri, Xavier; Parsons, Paul; Lammers, Uwe; Hoar, John; Hernandez, Jose

2011-10-01

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1,000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.

Cloud parallel processing of tandem mass spectrometry based proteomics data.

PubMed

Mohammed, Yassene; Mostovenko, Ekaterina; Henneman, Alex A; Marissen, Rob J; Deelder, André M; Palmblad, Magnus

2012-10-05

Data analysis in mass spectrometry based proteomics struggles to keep pace with the advances in instrumentation and the increasing rate of data acquisition. Analyzing this data involves multiple steps requiring diverse software, using different algorithms and data formats. Speed and performance of the mass spectral search engines are continuously improving, although not necessarily as needed to face the challenges of acquired big data. Improving and parallelizing the search algorithms is one possibility; data decomposition presents another, simpler strategy for introducing parallelism. We describe a general method for parallelizing identification of tandem mass spectra using data decomposition that keeps the search engine intact and wraps the parallelization around it. We introduce two algorithms for decomposing mzXML files and recomposing resulting pepXML files. This makes the approach applicable to different search engines, including those relying on sequence databases and those searching spectral libraries. We use cloud computing to deliver the computational power and scientific workflow engines to interface and automate the different processing steps. We show how to leverage these technologies to achieve faster data analysis in proteomics and present three scientific workflows for parallel database as well as spectral library search using our data decomposition programs, X!Tandem and SpectraST.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

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

PubMed

Ourselin, Sébastien; Emberton, Mark; Vercauteren, Tom

2016-10-01

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

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MedlinePlus

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Introduction to the LaRC central scientific computing complex

NASA Technical Reports Server (NTRS)

Shoosmith, John N.

1993-01-01

The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

OMPC: an Open-Source MATLAB®-to-Python Compiler

PubMed Central

Jurica, Peter; van Leeuwen, Cees

2008-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB®, the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB®-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB® functions into Python programs. The imported MATLAB® modules will run independently of MATLAB®, relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB®. OMPC is available at http://ompc.juricap.com. PMID:19225577

Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing

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

Bethel, E. Wes; Greenwald, Martin; Kleese van Dam, Kerstin

Scientific user facilities—particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more—operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity inmore » the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.« less

Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing

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

Bethel, E. Wes; Greenwald, Martin; Kleese van Dam, Kersten

Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sources, sequencing facilities, and more---operated by the U.S. Department of Energy (DOE) Office of Science (SC) generate ever increasing volumes of data at unprecedented rates from experiments, observations, and simulations. At the same time there is a growing community of experimentalists that require real-time data analysis feedback, to enable them to steer their complex experimental instruments to optimized scientific outcomes and new discoveries. Recent efforts in DOE-SC have focused on articulating the data-centric challenges and opportunities facing these science communities. Key challenges include difficulties coping with data size, rate, and complexity inmore » the context of both real-time and post-experiment data analysis and interpretation. Solutions will require algorithmic and mathematical advances, as well as hardware and software infrastructures that adequately support data-intensive scientific workloads. This paper presents the summary findings of a workshop held by DOE-SC in September 2015, convened to identify the major challenges and the research that is needed to meet those challenges.« less

New NASA 3D Animation Shows Seven Days of Simulated Earth Weather

NASA Image and Video Library

2014-08-11

This visualization shows early test renderings of a global computational model of Earth's atmosphere based on data from NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5). This particular run, called Nature Run 2, was run on a supercomputer, spanned 2 years of simulation time at 30 minute intervals, and produced Petabytes of output. The visualization spans a little more than 7 days of simulation time which is 354 time steps. The time period was chosen because a simulated category-4 typhoon developed off the coast of China. The 7 day period is repeated several times during the course of the visualization. Credit: NASA's Scientific Visualization Studio Read more or download here: svs.gsfc.nasa.gov/goto?4180 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Prolegomena to the field

NASA Astrophysics Data System (ADS)

Chen, Su Shing; Caulfield, H. John

1994-03-01

Adaptive Computing, vs. Classical Computing, is emerging to be a field which is the culmination during the last 40 and more years of various scientific and technological areas, including cybernetics, neural networks, pattern recognition networks, learning machines, selfreproducing automata, genetic algorithms, fuzzy logics, probabilistic logics, chaos, electronics, optics, and quantum devices. This volume of "Critical Reviews on Adaptive Computing: Mathematics, Electronics, and Optics" is intended as a synergistic approach to this emerging field. There are many researchers in these areas working on important results. However, we have not seen a general effort to summarize and synthesize these results in theory as well as implementation. In order to reach a higher level of synergism, we propose Adaptive Computing as the field which comprises of the above mentioned computational paradigms and various realizations. The field should include both the Theory (or Mathematics) and the Implementation. Our emphasis is on the interplay of Theory and Implementation. The interplay, an adaptive process itself, of Theory and Implementation is the only "holistic" way to advance our understanding and realization of brain-like computation. We feel that a theory without implementation has the tendency to become unrealistic and "out-of-touch" with reality, while an implementation without theory runs the risk to be superficial and obsolete.

Role of High-End Computing in Meeting NASA's Science and Engineering Challenges

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Tu, Eugene L.; Van Dalsem, William R.

2006-01-01

Two years ago, NASA was on the verge of dramatically increasing its HEC capability and capacity. With the 10,240-processor supercomputer, Columbia, now in production for 18 months, HEC has an even greater impact within the Agency and extending to partner institutions. Advanced science and engineering simulations in space exploration, shuttle operations, Earth sciences, and fundamental aeronautics research are occurring on Columbia, demonstrating its ability to accelerate NASA s exploration vision. This talk describes how the integrated production environment fostered at the NASA Advanced Supercomputing (NAS) facility at Ames Research Center is accelerating scientific discovery, achieving parametric analyses of multiple scenarios, and enhancing safety for NASA missions. We focus on Columbia s impact on two key engineering and science disciplines: Aerospace, and Climate. We also discuss future mission challenges and plans for NASA s next-generation HEC environment.

Debating complexity in modeling

USGS Publications Warehouse

Hunt, Randall J.; Zheng, Chunmiao

1999-01-01

As scientists trying to understand the natural world, how should our effort be apportioned? We know that the natural world is characterized by complex and interrelated processes. Yet do we need to explicitly incorporate these intricacies to perform the tasks we are charged with? In this era of expanding computer power and development of sophisticated preprocessors and postprocessors, are bigger machines making better models? Put another way, do we understand the natural world better now with all these advancements in our simulation ability? Today the public's patience for long-term projects producing indeterminate results is wearing thin. This increases pressure on the investigator to use the appropriate technology efficiently. On the other hand, bringing scientific results into the legal arena opens up a new dimension to the issue: to the layperson, a tool that includes more of the complexity known to exist in the real world is expected to provide the more scientifically valid answer.

Scientific Computing Paradigm

NASA Technical Reports Server (NTRS)

VanZandt, John

1994-01-01

The usage model of supercomputers for scientific applications, such as computational fluid dynamics (CFD), has changed over the years. Scientific visualization has moved scientists away from looking at numbers to looking at three-dimensional images, which capture the meaning of the data. This change has impacted the system models for computing. This report details the model which is used by scientists at NASA's research centers.

Commentary: Considerations in Pedagogy and Assessment in the Use of Computers to Promote Learning about Scientific Models

ERIC Educational Resources Information Center

Adams, Stephen T.

2004-01-01

Although one role of computers in science education is to help students learn specific science concepts, computers are especially intriguing as a vehicle for fostering the development of epistemological knowledge about the nature of scientific knowledge--what it means to "know" in a scientific sense (diSessa, 1985). In this vein, the…

High-End Scientific Computing

EPA Pesticide Factsheets

EPA uses high-end scientific computing, geospatial services and remote sensing/imagery analysis to support EPA's mission. The Center for Environmental Computing (CEC) assists the Agency's program offices and regions to meet staff needs in these areas.

Grid Computing and Collaboration Technology in Support of Fusion Energy Sciences

NASA Astrophysics Data System (ADS)

Schissel, D. P.

2004-11-01

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

Three-Dimensional User Interfaces for Immersive Virtual Reality

NASA Technical Reports Server (NTRS)

vanDam, Andries

1997-01-01

The focus of this grant was to experiment with novel user interfaces for immersive Virtual Reality (VR) systems, and thus to advance the state of the art of user interface technology for this domain. Our primary test application was a scientific visualization application for viewing Computational Fluid Dynamics (CFD) datasets. This technology has been transferred to NASA via periodic status reports and papers relating to this grant that have been published in conference proceedings. This final report summarizes the research completed over the past year, and extends last year's final report of the first three years of the grant.

Deserts in the Deluge: TerraPopulus and Big Human-Environment Data.

PubMed

Manson, S M; Kugler, T A; Haynes, D

2016-01-01

Terra Populus, or TerraPop, is a cyberinfrastructure project that integrates, preserves, and disseminates massive data collections describing characteristics of the human population and environment over the last six decades. TerraPop has made a number of GIScience advances in the handling of big spatial data to make information interoperable between formats and across scientific communities. In this paper, we describe challenges of these data, or 'deserts in the deluge' of data, that are common to spatial big data more broadly, and explore computational solutions specific to microdata, raster, and vector data models.

Mapping the Sloan Digital Sky Survey's Global Impact

NASA Astrophysics Data System (ADS)

Chen, Chaomei; Zhang, Jian; Vogeley, Michael S.

2009-07-01

The scientific capacity of a country is essential in todayâ's increasingly globalized science and technology ecosystem. Scientific capacity has four increasingly advanced levels of capabilities: absorbing, applying, creating, and retaining scientific knowledge. Moving to a advanced level requires additional skills and training. For example, it requires more specialized skills to apply scientific knowledge than to absorb knowledge. Similarly, making new discoveries requires more knowledge than applying existing procedures. Research has shown the importance of addressing specific, local problems while tapping into globally available expertise and resources. Accessing scientific knowledge is the first step towards absorbing knowledge. Low-income countries have increased their access to scientific literature on the Internet, but to what extent has this access led to more advanced levels of scientific capacity? Interdisciplinary and international collaboration may hold the key to creating and retaining knowledge. For example, creative ideas tend to be associated with inspirations originated from a diverse range of perspectives On the other hand, not all collaborations are productive. Assessing global science and technology needs to address both successes and failures and reasons behind them.

Advanced X-ray Astrophysics Facility (AXAF): Science working group report. [space shuttle payload

NASA Technical Reports Server (NTRS)

1980-01-01

The Advanced X-Ray Astrophysics Facility (AXAF) mission concept is examined from a scientific viewpoint. A brief description of the development of X-ray astronomy and a summary description of AXAF, the scientific objectives of the facility, a description of representative scientific instruments, requirements for X-ray ground testing, and a summary of studies related to spacecraft and support subsystems, are included.

The Global Ethics Corner: Foundations, Beliefs, and the Teaching of Biomedical and Scientific Ethics around the World

ERIC Educational Resources Information Center

Jakubowski, Henry; Xie, Jianping; Kumar Mitra, Arup; Ghooi, Ravindra; Hosseinkhani, Saman; Alipour, Mohsen; Hajipour, Behnam; Obiero, George

2017-01-01

The profound advances in the biomolecular sciences over the last decades have enabled similar advances in biomedicine. These advances have increasingly challenged our abilities to deploy them in an equitable and ethically acceptable manner. As such, it has become necessary and important to teach biomedical and scientific ethics to our students who…

PRACE - The European HPC Infrastructure

NASA Astrophysics Data System (ADS)

Stadelmeyer, Peter

2014-05-01

The mission of PRACE (Partnership for Advanced Computing in Europe) is to enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process. This talk gives a general overview about PRACE and the PRACE research infrastructure (RI). PRACE is established as an international not-for-profit association and the PRACE RI is a pan-European supercomputing infrastructure which offers access to computing and data management resources at partner sites distributed throughout Europe. Besides a short summary about the organization, history, and activities of PRACE, it is explained how scientists and researchers from academia and industry from around the world can access PRACE systems and which education and training activities are offered by PRACE. The overview also contains a selection of PRACE contributions to societal challenges and ongoing activities. Examples of the latter are beside others petascaling, application benchmark suite, best practice guides for efficient use of key architectures, application enabling / scaling, new programming models, and industrial applications. The Partnership for Advanced Computing in Europe (PRACE) is an international non-profit association with its seat in Brussels. The PRACE Research Infrastructure provides a persistent world-class high performance computing service for scientists and researchers from academia and industry in Europe. The computer systems and their operations accessible through PRACE are provided by 4 PRACE members (BSC representing Spain, CINECA representing Italy, GCS representing Germany and GENCI representing France). The Implementation Phase of PRACE receives funding from the EU's Seventh Framework Programme (FP7/2007-2013) under grant agreements RI-261557, RI-283493 and RI-312763. For more information, see www.prace-ri.eu

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Defining Computational Thinking for Mathematics and Science Classrooms

ERIC Educational Resources Information Center

Weintrop, David; Beheshti, Elham; Horn, Michael; Orton, Kai; Jona, Kemi; Trouille, Laura; Wilensky, Uri

2016-01-01

Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include "computational thinking" as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new…

The Co-evolution of Climate Models and the Intergovernmental Panel on Climate Change

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2010-12-01

As recently as the 1950s, global climate models, or GCMs, did not exist, and the notion that man-made carbon dioxide might lead to significant climate change was not regarded as a serious possibility by most experts. Today, of course, the prospect or threat of exactly this type of climate change dominates the science and ranks among the most pressing issues confronting all mankind. Indeed, the prevailing scientific view throughout the first half of the twentieth century was that adding carbon dioxide to the atmosphere would have only a negligible effect on climate. The science of climate change caused by atmospheric carbon dioxide changes has thus undergone a genuine revolution. An extraordinarily rapid development of global climate models has also characterized this period, especially in the three decades since about 1980. In these three decades, the number of GCMs has greatly increased, and their physical and computational aspects have both markedly improved. Modeling progress has been enabled by many scientific advances, of course, but especially by a massive increase in available computer power, with supercomputer speeds increasing by roughly a factor of a million in the three decades from about 1980 to 2010. This technological advance has permitted a rapid increase in the physical comprehensiveness of GCMs as well as in spatial computational resolution. In short, GCMs have dramatically evolved over time, in exactly the same recent period as popular interest and scientific concern about anthropogenic climate change have markedly increased. In parallel, a unique international organization, the Intergovernmental Panel on Climate Change, or IPCC, has also recently come into being and also evolved rapidly. Today, the IPCC has become widely respected and globally influential. The IPCC was founded in 1988, and its history is thus even shorter than that of GCMs. Yet, its stature today is such that a series of IPCC reports assessing climate change science has already been endorsed by many leading scientific professional societies and academies of science worldwide. These reports are considered as definitive summaries of the state of the science. In 2007, in recognition of its exceptional accomplishments, the IPCC shared the Nobel Peace Prize equally with Al Gore. The present era is characterized not only by the reality and seriousness of human-caused climate change, but also by a young yet powerful science that enables us to understand much about the climate change that has occurred already and that awaits in the future. The development of GCMs is a critical part of the scientific story, and the development of the IPCC is a key factor in connecting the science to the perceptions and priorities of the global public and policymakers. GCMs and the IPCC have co-evolved and strongly influenced one another, as both scientists and the world at large have worked to confront the challenge of climate change.

Ermittlung von Wortstaemmen in russischen wissenschaftlichen Fachsprachen mit Hilfe des Computers (Establishing Word Stems in Scientific Russian With the Aid of a Computer)

ERIC Educational Resources Information Center

Halbauer, Siegfried

1976-01-01

It was considered that students of intensive scientific Russian courses could learn vocabulary more efficiently if they were taught word stems and how to combine them with prefixes and suffixes to form scientific words. The computer programs developed to identify the most important stems is discussed. (Text is in German.) (FB)

Scientific Visualization: The Modern Oscilloscope for "Seeing the Unseeable" (LBNL Summer Lecture Series)

ScienceCinema

Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division and Scientific Visualization Group

2018-05-07

Summer Lecture Series 2008: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

The future of cerebral surgery: a kaleidoscope of opportunities.

PubMed

Elder, James B; Hoh, Daniel J; Oh, Bryan C; Heller, A Chris; Liu, Charles Y; Apuzzo, Michael L J

2008-06-01

The emerging future of cerebral surgery will witness the refined evolution of current techniques, as well as the introduction of numerous novel concepts. Clinical practice and basic science research will benefit greatly from their application. The sum of these efforts will result in continued minimalism and improved accuracy and efficiency of neurosurgical diagnostic and therapeutic methodologies.Initially, the refinement of current technologies will further enhance various aspects of cerebral surgery. Advances in computing power and information technology will speed data acquisition, storage, and transfer. Miniaturization of current devices will impact diverse areas, such as modulation of endoscopy and endovascular techniques. The increased penetrance of surgical technologies such as stereotactic radiosurgery, neuronavigation, intraoperative imaging, and implantable electrodes for neurodegenerative disorders and epilepsy will enhance the knowledge and experience in these areas and facilitate refinements and advances in these technologies. Further into the future, technologies that are currently relatively remote to surgical events will fundamentally alter the complexity and scale at which a neurological disease may be treated or investigated. Seemingly futuristic concepts will become ubiquitous in the daily experience of the neurosurgeon. These include diverse fields such as nanotechnology, virtual reality, and robotics. Ultimately, combining advances in multiple fields will yield progress in diverse realms such as brain tumor therapy, neuromodulation for psychiatric diseases, and neuroprosthetics. Operating room equipment and design will benefit from each of the aforementioned advances. In this work, we discuss new developments in three parts. In Part I, concepts in minimalism important for future cerebral surgery are discussed. These include concrete and abstract ideas in miniaturization, as well as recent and future work in microelectromechanical systems and nanotechnology. Part II presents advances in computational sciences and technological fields dependent on these developments. Future breakthroughs in the components of the "computer," including data storage, electrical circuitry, and computing hardware and techniques, are discussed. Additionally, important concepts in the refinement of virtual environments and the brain-machine interface are presented, as their incorporation into cerebral surgery is closely linked to advances in computing and electronics. Finally, Part III offers insights into the future evolution of surgical and nonsurgical diagnostic and therapeutic modalities that are important for the future cerebral surgeon. A number of topics relevant to cerebral surgery are discussed, including the operative environment, imaging technologies, endoscopy, robotics, neuromodulation, stem cell therapy, radiosurgery, and technical methods of restoration of neural function. Cerebral surgery in the near and distant future will reflect the application of these emerging technologies. As this article indicates, the key to maximizing the impact of these advancements in the clinical arena is continued collaboration between scientists and neurosurgeons, as well as the emergence of a neurosurgeon whose scientific grounding and technical focus are far removed from those of his predecessors.

Scientific Visualization, Seeing the Unseeable

ScienceCinema

LBNL

2017-12-09

June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in bo... June 24, 2008 Berkeley Lab lecture: Scientific visualization transforms abstract data into readily comprehensible images, provide a vehicle for "seeing the unseeable," and play a central role in both experimental and computational sciences. Wes Bethel, who heads the Scientific Visualization Group in the Computational Research Division, presents an overview of visualization and computer graphics, current research challenges, and future directions for the field.

The Individual Virtual Eye: a Computer Model for Advanced Intraocular Lens Calculation

PubMed Central

Einighammer, Jens; Oltrup, Theo; Bende, Thomas; Jean, Benedikt

2010-01-01

Purpose To describe the individual virtual eye, a computer model of a human eye with respect to its optical properties. It is based on measurements of an individual person and one of its major application is calculating intraocular lenses (IOLs) for cataract surgery. Methods The model is constructed from an eye's geometry, including axial length and topographic measurements of the anterior corneal surface. All optical components of a pseudophakic eye are modeled with computer scientific methods. A spline-based interpolation method efficiently includes data from corneal topographic measurements. The geometrical optical properties, such as the wavefront aberration, are simulated with real ray-tracing using Snell's law. Optical components can be calculated using computer scientific optimization procedures. The geometry of customized aspheric IOLs was calculated for 32 eyes and the resulting wavefront aberration was investigated. Results The more complex the calculated IOL is, the lower the residual wavefront error is. Spherical IOLs are only able to correct for the defocus, while toric IOLs also eliminate astigmatism. Spherical aberration is additionally reduced by aspheric and toric aspheric IOLs. The efficient implementation of time-critical numerical ray-tracing and optimization procedures allows for short calculation times, which may lead to a practicable method integrated in some device. Conclusions The individual virtual eye allows for simulations and calculations regarding geometrical optics for individual persons. This leads to clinical applications like IOL calculation, with the potential to overcome the limitations of those current calculation methods that are based on paraxial optics, exemplary shown by calculating customized aspheric IOLs.

Towards Test Driven Development for Computational Science with pFUnit

NASA Technical Reports Server (NTRS)

Rilee, Michael L.; Clune, Thomas L.

2014-01-01

Developers working in Computational Science & Engineering (CSE)/High Performance Computing (HPC) must contend with constant change due to advances in computing technology and science. Test Driven Development (TDD) is a methodology that mitigates software development risks due to change at the cost of adding comprehensive and continuous testing to the development process. Testing frameworks tailored for CSE/HPC, like pFUnit, can lower the barriers to such testing, yet CSE software faces unique constraints foreign to the broader software engineering community. Effective testing of numerical software requires a comprehensive suite of oracles, i.e., use cases with known answers, as well as robust estimates for the unavoidable numerical errors associated with implementation with finite-precision arithmetic. At first glance these concerns often seem exceedingly challenging or even insurmountable for real-world scientific applications. However, we argue that this common perception is incorrect and driven by (1) a conflation between model validation and software verification and (2) the general tendency in the scientific community to develop relatively coarse-grained, large procedures that compound numerous algorithmic steps.We believe TDD can be applied routinely to numerical software if developers pursue fine-grained implementations that permit testing, neatly side-stepping concerns about needing nontrivial oracles as well as the accumulation of errors. We present an example of a successful, complex legacy CSE/HPC code whose development process shares some aspects with TDD, which we contrast with current and potential capabilities. A mix of our proposed methodology and framework support should enable everyday use of TDD by CSE-expert developers.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

A 3D bioprinting exemplar of the consequences of the regulatory requirements on customized processes.

PubMed

Hourd, Paul; Medcalf, Nicholas; Segal, Joel; Williams, David J

2015-01-01

Computer-aided 3D printing approaches to the industrial production of customized 3D functional living constructs for restoration of tissue and organ function face significant regulatory challenges. Using the manufacture of a customized, 3D-bioprinted nasal implant as a well-informed but hypothetical exemplar, we examine how these products might be regulated. Existing EU and USA regulatory frameworks do not account for the differences between 3D printing and conventional manufacturing methods or the ability to create individual customized products using mechanized rather than craft approaches. Already subject to extensive regulatory control, issues related to control of the computer-aided design to manufacture process and the associated software system chain present additional scientific and regulatory challenges for manufacturers of these complex 3D-bioprinted advanced combination products.

Investigating the impact of the cielo cray XE6 architecture on scientific application codes.

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

Rajan, Mahesh; Barrett, Richard; Pedretti, Kevin Thomas Tauke

2010-12-01

Cielo, a Cray XE6, is the Department of Energy NNSA Advanced Simulation and Computing (ASC) campaign's newest capability machine. Rated at 1.37 PFLOPS, it consists of 8,944 dual-socket oct-core AMD Magny-Cours compute nodes, linked using Cray's Gemini interconnect. Its primary mission objective is to enable a suite of the ASC applications implemented using MPI to scale to tens of thousands of cores. Cielo is an evolutionary improvement to a successful architecture previously available to many of our codes, thus enabling a basis for understanding the capabilities of this new architecture. Using three codes strategically important to the ASC campaign, andmore » supplemented with some micro-benchmarks that expose the fundamental capabilities of the XE6, we report on the performance characteristics and capabilities of Cielo.« less

OMPC: an Open-Source MATLAB-to-Python Compiler.

PubMed

Jurica, Peter; van Leeuwen, Cees

2009-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

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

Heroux, Michael; Lethin, Richard

Programming models and environments play the essential roles in high performance computing of enabling the conception, design, implementation and execution of science and engineering application codes. Programmer productivity is strongly influenced by the effectiveness of our programming models and environments, as is software sustainability since our codes have lifespans measured in decades, so the advent of new computing architectures, increased concurrency, concerns for resilience, and the increasing demands for high-fidelity, multi-physics, multi-scale and data-intensive computations mean that we have new challenges to address as part of our fundamental R&D requirements. Fortunately, we also have new tools and environments that makemore » design, prototyping and delivery of new programming models easier than ever. The combination of new and challenging requirements and new, powerful toolsets enables significant synergies for the next generation of programming models and environments R&D. This report presents the topics discussed and results from the 2014 DOE Office of Science Advanced Scientific Computing Research (ASCR) Programming Models & Environments Summit, and subsequent discussions among the summit participants and contributors to topics in this report.« less

Parallel computing works

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

Not Available

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

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

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study.

PubMed

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-03-28

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study

PubMed Central

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-01-01

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation. PMID:28350358

A PICKSC Science Gateway for enabling the common plasma physicist to run kinetic software

NASA Astrophysics Data System (ADS)

Hu, Q.; Winjum, B. J.; Zonca, A.; Youn, C.; Tsung, F. S.; Mori, W. B.

2017-10-01

Computer simulations offer tremendous opportunities for studying plasmas, ranging from simulations for students that illuminate fundamental educational concepts to research-level simulations that advance scientific knowledge. Nevertheless, there is a significant hurdle to using simulation tools. Users must navigate codes and software libraries, determine how to wrangle output into meaningful plots, and oftentimes confront a significant cyberinfrastructure with powerful computational resources. Science gateways offer a Web-based environment to run simulations without needing to learn or manage the underlying software and computing cyberinfrastructure. We discuss our progress on creating a Science Gateway for the Particle-in-Cell and Kinetic Simulation Software Center that enables users to easily run and analyze kinetic simulations with our software. We envision that this technology could benefit a wide range of plasma physicists, both in the use of our simulation tools as well as in its adaptation for running other plasma simulation software. Supported by NSF under Grant ACI-1339893 and by the UCLA Institute for Digital Research and Education.

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

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

Phillips, R.L.

1995-12-31

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

Artificial Intelligence in Medical Practice: The Question to the Answer?

PubMed

Miller, D Douglas; Brown, Eric W

2018-02-01

Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

An infrastructure for the integration of geoscience instruments and sensors on the Grid

NASA Astrophysics Data System (ADS)

Pugliese, R.; Prica, M.; Kourousias, G.; Del Linz, A.; Curri, A.

2009-04-01

The Grid, as a computing paradigm, has long been in the attention of both academia and industry[1]. The distributed and expandable nature of its general architecture result to scalability and more efficient utilisation of the computing infrastructures. The scientific community, including that of geosciences, often handles problems with very high requirements in data processing, transferring, and storing[2,3]. This has raised the interest on Grid technologies but these are often viewed solely as an access gateway to HPC. Suitable Grid infrastructures could provide the geoscience community with additional benefits like those of sharing, remote access and control of scientific systems. These systems can be scientific instruments, sensors, robots, cameras and any other device used in geosciences. The solution for practical, general, and feasible Grid-enabling of such devices requires non-intrusive extensions on core parts of the current Grid architecture. We propose an extended version of an architecture[4] that can serve as the solution to the problem. The solution we propose is called Grid Instrument Element (IE) [5]. It is an addition to the existing core Grid parts; the Computing Element (CE) and the Storage Element (SE) that serve the purposes that their name suggests. The IE that we will be referring to, and the related technologies have been developed in the EU project on the Deployment of Remote Instrumentation Infrastructure (DORII1). In DORII, partners of various scientific communities including those of Earthquake, Environmental science, and Experimental science, have adopted the technology of the Instrument Element in order to integrate to the Grid their devices. The Oceanographic and coastal observation and modelling Mediterranean Ocean Observing Network (OGS2), a DORII partner, is in the process of deploying the above mentioned Grid technologies on two types of observational modules: Argo profiling floats and a novel Autonomous Underwater Vehicle (AUV). In this paper i) we define the need for integration of instrumentation in the Grid, ii) we introduce the solution of the Instrument Element, iii) we demonstrate a suitable end-user web portal for accessing Grid resources, iv) we describe from the Grid-technological point of view the process of the integration to the Grid of two advanced environmental monitoring devices. References [1] M. Surridge, S. Taylor, D. De Roure, and E. Zaluska, "Experiences with GRIA—Industrial Applications on a Web Services Grid," e-Science and Grid Computing, First International Conference on e-Science and Grid Computing, 2005, pp. 98-105. [2] A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke, "The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets," Journal of Network and Computer Applications, vol. 23, 2000, pp. 187-200. [3] B. Allcock, J. Bester, J. Bresnahan, A.L. Chervenak, I. Foster, C. Kesselman, S. Meder, V. Nefedova, D. Quesnel, and S. Tuecke, "Data management and transfer in high-performance computational grid environments," Parallel Computing, vol. 28, 2002, pp. 749-771. [4] E. Frizziero, M. Gulmini, F. Lelli, G. Maron, A. Oh, S. Orlando, A. Petrucci, S. Squizzato, and S. Traldi, "Instrument Element: A New Grid component that Enables the Control of Remote Instrumentation," Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)-Volume 00, IEEE Computer Society Washington, DC, USA, 2006. [5] R. Ranon, L. De Marco, A. Senerchia, S. Gabrielli, L. Chittaro, R. Pugliese, L. Del Cano, F. Asnicar, and M. Prica, "A Web-based Tool for Collaborative Access to Scientific Instruments in Cyberinfrastructures." 1 The DORII project is supported by the European Commission within the 7th Framework Programme (FP7/2007-2013) under grant agreement no. RI-213110. URL: http://www.dorii.eu 2 Istituto Nazionale di Oceanografia e di Geofisica Sperimentale. URL: http://www.ogs.trieste.it

Placing Science into Its Human Context: Using Scientific Autobiography to Teach Chemistry

NASA Astrophysics Data System (ADS)

Carroll, Felix A.; Seeman, Jeffrey I.

2001-12-01

Scientific autobiography and biography can improve chemistry learning by helping students relate otherwise abstract concepts to important events in the lives of fellow human beings. In advanced courses, reading scientific autobiography and biography can help students see how scientific collaboration, advances in instrumentation, and major events in human lives influence the development of chemical ideas over time. In addition, studying many years of an individual's research program can demonstrate the progress of science, the connectivity of research findings, and the validity of experimental results over many decades. This paper describes the use of an autobiography of an eminent chemist in an advanced undergraduate chemistry course. This approach not only enhances the teaching of chemical concepts, but it also provides students with expanded opportunities for cooperative and self-directed learning activities.

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

NASA Astrophysics Data System (ADS)

Strayer, Michael

2005-01-01

Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds immense promise. In this environment, I believe it is necessary to institute a system of science based performance metrics to help quantify our progress towards science goals and scientific computing. As a final comment I would like to reaffirm that the shifting landscapes of science will force changes to our computational sciences, and leave you with the quote from Richard Hamming, 'The purpose of computing is insight, not numbers'.

An Overview of the Computational Physics and Methods Group at Los Alamos National Laboratory

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

Baker, Randal Scott

CCS Division was formed to strengthen the visibility and impact of computer science and computational physics research on strategic directions for the Laboratory. Both computer science and computational science are now central to scientific discovery and innovation. They have become indispensable tools for all other scientific missions at the Laboratory. CCS Division forms a bridge between external partners and Laboratory programs, bringing new ideas and technologies to bear on today’s important problems and attracting high-quality technical staff members to the Laboratory. The Computational Physics and Methods Group CCS-2 conducts methods research and develops scientific software aimed at the latest andmore » emerging HPC systems.« less

[Earth Science Technology Office's Computational Technologies Project

NASA Technical Reports Server (NTRS)

Fischer, James (Technical Monitor); Merkey, Phillip

2005-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Public Education and Outreach Through Full-Dome Video Technology

NASA Astrophysics Data System (ADS)

Pollock, John

2009-03-01

My long-term goal is to enhance public understanding of complex systems that can be best demonstrated through richly detailed computer graphic animation displayed with full-dome video technology. My current focus is on health science advances that focus on regenerative medicine, which helps the body heal itself. Such topics facilitate science learning and health literacy. My team develops multi-media presentations that bring the scientific and medical advances to the public through immersive high-definition video animation. Implicit in treating the topics of regenerative medicine will be the need to address stem cell biology. The topics are clarified and presented from a platform of facts and balanced ethical consideration. The production process includes communicating scientific information about the excitement and importance of stem cell research. Principles of function are emphasized over specific facts or terminology by focusing on a limited, but fundamental set of concepts. To achieve this, visually rich, biologically accurate 3D computer graphic environments are created to illustrate the cells, tissues and organs of interest. A suite of films are produced, and evaluated in pre- post-surveys assessing attitudes, knowledge and learning. Each film uses engaging interactive demonstrations to illustrate biological functions, the things that go wrong due to disease and disability, and the remedy provided by regenerative medicine. While the images are rich and detailed, the language is accessible and appropriate to the audience. The digital, high-definition video is also re-edited for presentation in other ``flat screen'' formats, increasing our distribution potential. Show content is also presented in an interactive web space (www.sepa.duq.edu) with complementing teacher resource guides and student workbooks and companion video games.

The Development of Nanotechnologies and Advanced Materials Industry in Science and Entrepreneurship: Scientific Indicators. A Case Study of Latvia (Part Three)

NASA Astrophysics Data System (ADS)

Geipele, S.; Geipele, I.; Kauskale, L.; Zeltins, N.; Staube, T.; Pudzis, E.

2017-10-01

The present scientific paper is the third part and continuation of the indepth scientific study of the developed system of engineering economic indicators, where the authors obtain results from the scientific research presented in a series of works on the development of the nanotechnologies and advanced materials industry in science and entrepreneurship in Latvia. Part three determines the crucial scientific indicators of the development of nano-field at the macro, micro, and meso development levels of the economic environment in Latvia. The paper provides the interaction of new identified indicators of nanofield in terms of further scientific and practical activities. Latvia is analysed in comparison with other countries in the world.

48 CFR 35.002 - General.

Code of Federal Regulations, 2013 CFR

2013-10-01

... programs is to advance scientific and technical knowledge and apply that knowledge to the extent necessary... are directed toward objectives for which the work or methods cannot be precisely described in advance... to encourage the best sources from the scientific and industrial community to become involved in the...