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

Scientific American Frontiers Teaching Guides for Shows 801-805, October 1997-April 1998.

ERIC Educational Resources Information Center

Connecticut Public Television, Hartford.

These teaching guides are meant to supplement the eighth season (1997-98) of the PBS Series "Scientific American Frontiers". Episode 801 is entitled "Expedition Panama: Science at the Smithsonian Tropical Research Institute" and the teaching guide contains information and activities on the ultrasonic communication of bats,…

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.

Center for Center for Technology for Advanced Scientific Component Software (TASCS)

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

Kostadin, Damevski

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technologymore » for Advanced Scientific Component Software (TASCS)1 tackles these these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.« less

Computational Science: A Research Methodology for the 21st Century

NASA Astrophysics Data System (ADS)

Orbach, Raymond L.

2004-03-01

Computational simulation - a means of scientific discovery that employs computer systems to simulate a physical system according to laws derived from theory and experiment - has attained peer status with theory and experiment. Important advances in basic science are accomplished by a new "sociology" for ultrascale scientific computing capability (USSCC), a fusion of sustained advances in scientific models, mathematical algorithms, computer architecture, and scientific software engineering. Expansion of current capabilities by factors of 100 - 1000 open up new vistas for scientific discovery: long term climatic variability and change, macroscopic material design from correlated behavior at the nanoscale, design and optimization of magnetic confinement fusion reactors, strong interactions on a computational lattice through quantum chromodynamics, and stellar explosions and element production. The "virtual prototype," made possible by this expansion, can markedly reduce time-to-market for industrial applications such as jet engines and safer, more fuel efficient cleaner cars. In order to develop USSCC, the National Energy Research Scientific Computing Center (NERSC) announced the competition "Innovative and Novel Computational Impact on Theory and Experiment" (INCITE), with no requirement for current DOE sponsorship. Fifty nine proposals for grand challenge scientific problems were submitted for a small number of awards. The successful grants, and their preliminary progress, will be described.

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

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.

Flocculation, Optics and Turbulence in the Community Sediment Transport Model System: Application of Oasis Results

DTIC Science & Technology

2012-09-30

Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 2 instrumented with a Sequoia Scientific LISST-100x Type B laser particle sizer and a Digital...work was presented at Ocean Sciences 2012 is a session co-chaired by Hill, Bowers, Sherwood, and Wayne Slade from Sequoia Scientific. Wayne

78 FR 41046 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-09

... Services Administration, notice is hereby given that the Advanced Scientific Computing Advisory Committee will be renewed for a two-year period beginning on July 1, 2013. The Committee will provide advice to the Director, Office of Science (DOE), on the Advanced Scientific Computing Research Program managed...

A Scientific Analysis of Galaxy Tangential Speed of Revolution Curves III

NASA Astrophysics Data System (ADS)

Taff, Laurence

2015-04-01

I last reported on my preliminary analysis of 350 + spiral, lenticular, irregular, polar ring, ring, and dwarf elliptical galaxies' tangential speed of revolution curves [TSRCs; and not rotation (sic) curves]. I now know that the consensus opinion in the literature--for which I can find no geometrical, numerical, statistical, nor scientific testing in 2,500 + publications--that the TSRC, vB(r), in the central bulges of these galaxies, is a linear function of the radial distance from the minor axis of symmetry r--is false. For the majority (>98%) vB(r) is rarely well represented by vB(r) = ωB r (for which the unique material model is an homogeneous, oblate, spheroid). Discovered via a scientific analysis of the gravitational potential energy computed directly from the observational data, vB(r) is almost exactly given by vB2(r) = (ωB r)2(1 + η r2) with | η | < 10-2 and frequently orders of magnitude less. The corresponding mass model is the simplest generalization: a two component homoeoid. The set of possible periodic orbits, based on circular trigonometric functions, becomes a set of periodic orbits based on the Jacobian elliptic functions. Once again it is possible to prove that the mass-to-light ratio can neither be a constant nor follow the de Vaucouleurs R1/4 rule.

Correction and Use of Biomedical Literature Affected by Scientific Misconduct

PubMed Central

Neale, Anne Victoria; Northrup, Justin; Dailey, Rhonda; Marks, Ellen; Abrams, Judith

2009-01-01

The purpose of this study was to identify and describe published research articles that were named in official findings of scientific misconduct and to investigate compliance with the administrative actions contained in these reports for corrections and retractions, as represented in PubMed. Between 1993 and 2001, 102 articles were named in either the NIH Guide for Grants and Contracts (“Findings of Scientific Misconduct”) or the U.S. Office of Research Integrity annual reports as needing retraction or correction. In 2002, 98 of the 102 articles were indexed in PubMed. Eighty-five of these 98 articles had indexed corrections: 47 were retracted; 26 had an erratum; 12 had a correction described in the “comment” field. Thirteen had no correction, but 10 were linked to the NIH Guide “Findings of Scientific Misconduct”, leaving only 3 articles with no indication of any sort of problem. As of May 2005, there were 5,393 citations to the 102 articles, with a median of 26 citations per article (range 0–592). Researchers should be alert to “Comments” linked to the NIH Guide as these are open access, and the “Findings of Scientific Misconduct’ reports are often more informative than the statements about the retraction or correction found in the journals. PMID:17703606

Differentiation of Ecuadorian National and CCN-51 cocoa beans and their mixtures by computer vision.

PubMed

Jimenez, Juan C; Amores, Freddy M; Solórzano, Eddyn G; Rodríguez, Gladys A; La Mantia, Alessandro; Blasi, Paolo; Loor, Rey G

2018-05-01

Ecuador exports two major types of cocoa beans, the highly regarded and lucrative National, known for its fine aroma, and the CCN-51 clone type, used in bulk for mass chocolate products. In order to discourage exportation of National cocoa adulterated with CCN-51, a fast and objective methodology for distinguishing between the two types of cocoa beans is needed. This study reports a methodology based on computer vision, which makes it possible to recognize these beans and determine the percentage of their mixture. The methodology was challenged with 336 samples of National cocoa and 127 of CCN-51. By excluding the samples with a low fermentation level and white beans, the model discriminated with a precision higher than 98%. The model was also able to identify and quantify adulterations in 75 export batches of National cocoa and separate out poorly fermented beans. A scientifically reliable methodology able to discriminate between Ecuadorian National and CCN-51 cocoa beans and their mixtures was successfully developed. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Verification of charge sign for high-energy particles measured by magnetic tracking system of PAMELA spectrometer

NASA Astrophysics Data System (ADS)

Lukyanov, A. D.; Alekseev, V. V.; Bogomolov, Yu V.; Dunaeva, O. A.; Malakhov, V. V.; Mayorov, A. G.; Rodenko, S. A.

2017-01-01

Analysis of experimental data of primary positrons and antiprotons fluxes obtained by PAMELA spectrometer, recently confirmed by AMS-02 spectrometer, for some reasons is of big interest for scientific community, especially for energies higher than 100 GV, where appearance of signal coming from dark matter particles is possible. In this work we present a method for verification of charge sign for high-energy antiprotons, measured by magnetic tracking system of PAMELA spectrometer, which can be immitated by protons due to scattering or finite instrumental resolution at high energies (so-called “spillover”). We base our approach on developing2 a set of distinctive features represented by differently computed rigidities and training AdaBoost classifier, which shows good classification accuracy on Monte-Carlo simulation data of 98% for rigidity up to 600 GV.

MUSC Environmental Biosciences Program First Quarter Report May - June, 2002

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

Lawrence C. Mohr

2002-07-31

In May 2002, the United States Department of Energy (DOE) signed Assistance Instrument Number DE-FC02-98CH11109 with the Medical University of South Carolina (MUSC) to support the Environmental Biosciences Program (EBP). This funding instrument replaces DOE Assistance Instrument Number DE-FC02-98CH10902. EBP is an integrated, multidisciplinary scientific program, employing a range of research initiatives to identify, study and resolve environmental health risk issues. These initiatives are consistent with the Medical University's role as a comprehensive state-supported health sciences institution and the nation's need for new and better approaches to the solution of a complex and expansive array of environment-related health problems. Themore » intrinsic capabilities of a comprehensive health sciences institution enable the Medical University to be a national resource for the scientific investigation of environmental health issues. EBP's success in convening worldwide scientific expertise is due in part to the inherent credibility the Medical University brings to the process of addressing these complex issues.« less

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.

STS-98 U.S. Lab Destiny rests in Atlantis' payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- The U.S. Lab Destiny rests in the payload bay of Space Shuttle Atlantis. A key element in the construction of the International Space Station, Destiny is 28 feet long and weighs 16 tons. This research and command-and-control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. Destiny will fly on STS-98, the seventh construction flight to the ISS. Launch of STS-98 is scheduled for Jan. 19 at 2:11 a.m. EST.

Structure-Activity Relationship Studies on the Mosquito Toxicity and Biting Deterrency of Callicarpenal Derivatives

DTIC Science & Technology

2009-01-01

peer-reviewed, scientific literature [1]. Also recognized by the CDC as effective insect repellents are those containing oil of lemon eucalyptus ...The United States Centers for Disease Control and Prevention (CDC) recommend the use of products containing active ingredients which have been...95% C.I.)a) Slope (SE) c2 1 5.13 (1.83–7.26) 23.91 (15.98–87.90) 2.46 (0.73) 0.32 2 5.87 (4.98–6.88) 12.49 (9.98–18.59) 5.01 (0.83) 0.56 3 19.62

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…

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.

The Function of Annotations in the Comprehension of Scientific Texts: Cognitive Load Effects and the Impact of Verbal Ability

ERIC Educational Resources Information Center

Wallen, Erik; Plass, Jan L.; Brunken, Roland

2005-01-01

Students participated in a study (n = 98) investigating the effectiveness of three types of annotations on three learning outcome measures. The annotations were designed to support the cognitive processes in the comprehension of scientific texts, with a function to aid either the process of selecting relevant information, organizing the…

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.

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

A Manual for a Laboratory Information Management System (LIMS) For Light Stable Isotopes - Version 7.0

DTIC Science & Technology

1998-01-01

A MANUAL FOR A LABORATORY INFORMATION MANAGEMENT SYSTEM (LIMS) FOR LIGHT STABLE ISOTOPES— VERSION 7.0 U.S. GEOLOGICAL SURVEY Open-File Report 98-284...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 A MANUAL FOR A LABORATORY INFORMATION MANAGEMENT SYSTEM (LIMS) FOR LIGHT STABLE...Europa Scientific ..................................................120 1 A MANUAL FOR A LABORATORY INFORMATION MANAGEMENT SYSTEM (LIMS) FOR LIGHT STABLE

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.

98. View of IBM digital computer model 7090 magnet core ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

98. View of IBM digital computer model 7090 magnet core installation. ITT Artic Services, Inc., Official photograph BMEWS Site II, Clear, AK, by unknown photographer, 17 September 1965. BMEWS, clear as negative no. A-6606. - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

An analysis of learning process based on scientific approach in physical chemsitry experiment

NASA Astrophysics Data System (ADS)

Arlianty, Widinda Normalia; Febriana, Beta Wulan; Diniaty, Artina

2017-03-01

This study aimed to analysis the quality of learning process based on scientific approach in physical chemistry experiment of Chemistry Education students, Islamic University of Indonesia. The research was descriptive qualitative. The samples of this research were 2nd semester student, class of 2015. Scientific data of learning process were collected by observation sheet and documentation of seven title experimental. The results showed that the achievement of scientific learning process on observing, questioning, experimenting and associating data were 73.98%; 81.79%; 80.74%; and 76.94% respectively, which categorized as medium. Furthermore, for aspect communicating had high category at 86.11% of level achievement.

STS-98 payload U.S. Lab Destiny is moved into Atlantis' payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- Workers check out the U.S. Lab Destiny after it has been installed in Atlantis''' payload bay at the pad. Destiny, a key element in the construction of the International Space Station, is 28 feet long and weighs 16 tons. This research and command-and- control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. STS-98 is the seventh construction flight to the ISS. Launch of STS-98 is scheduled for Jan. 19 at 2:11 a.m. EST.

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…

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.

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.

40 CFR 98.237 - Records that must be retained.

Code of Federal Regulations, 2013 CFR

2013-07-01

... emissions computer model runs used for engineering estimation of emissions. (e) The records required under § 98.3(g)(2)(i) shall include an explanation of how company records, engineering estimation, or best...

40 CFR 98.237 - Records that must be retained.

Code of Federal Regulations, 2014 CFR

2014-07-01

... emissions computer model runs used for engineering estimation of emissions. (e) The records required under § 98.3(g)(2)(i) shall include an explanation of how company records, engineering estimation, or best...

40 CFR 98.237 - Records that must be retained.

Code of Federal Regulations, 2012 CFR

2012-07-01

... emissions computer model runs used for engineering estimation of emissions. (e) The records required under § 98.3(g)(2)(i) shall include an explanation of how company records, engineering estimation, or best...

Beyond Keyword Search: Discovering Relevant Scientific Literature

DTIC Science & Technology

2011-06-01

Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases. In KDD, 2007. 18 [44] Thomson Reuters Web of Knowledge. http...stimulation 2001 98 14386-14391 10123 In vivo evidence for a cochlear amplifier in the hair-cell bundle of lizards 2001 98 2826-2831 22 Table 1 (cont...2000 97 4856-4861 12134 Arabidopsis RelA/SpoT homologs implicate (p)ppGpp in plant signal- ing 2000 97 3747-3752 12176 Cochlear mechanisms from a

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.

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

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.

Computers and Computation. Readings from Scientific American.

ERIC Educational Resources Information Center

Fenichel, Robert R.; Weizenbaum, Joseph

A collection of articles from "Scientific American" magazine has been put together at this time because the current period in computer science is one of consolidation rather than innovation. A few years ago, computer science was moving so swiftly that even the professional journals were more archival than informative; but today it is…

Scientific Inquiry Self-Efficacy and Computer Game Self-Efficacy as Predictors and Outcomes of Middle School Boys' and Girls' Performance in a Science Assessment in a Virtual Environment

NASA Astrophysics Data System (ADS)

Bergey, Bradley W.; Ketelhut, Diane Jass; Liang, Senfeng; Natarajan, Uma; Karakus, Melissa

2015-10-01

The primary aim of the study was to examine whether performance on a science assessment in an immersive virtual environment was associated with changes in scientific inquiry self-efficacy. A secondary aim of the study was to examine whether performance on the science assessment was equitable for students with different levels of computer game self-efficacy, including whether gender differences were observed. We examined 407 middle school students' scientific inquiry self-efficacy and computer game self-efficacy before and after completing a computer game-like assessment about a science mystery. Results from path analyses indicated that prior scientific inquiry self-efficacy predicted achievement on end-of-module questions, which in turn predicted change in scientific inquiry self-efficacy. By contrast, computer game self-efficacy was neither predictive of nor predicted by performance on the science assessment. While boys had higher computer game self-efficacy compared to girls, multi-group analyses suggested only minor gender differences in how efficacy beliefs related to performance. Implications for assessments with virtual environments and future design and research are discussed.

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

Hules, John

This 1998 annual report from the National Scientific Energy Research Computing Center (NERSC) presents the year in review of the following categories: Computational Science; Computer Science and Applied Mathematics; and Systems and Services. Also presented are science highlights in the following categories: Basic Energy Sciences; Biological and Environmental Research; Fusion Energy Sciences; High Energy and Nuclear Physics; and Advanced Scientific Computing Research and Other Projects.

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

The Versatile Terminal.

ERIC Educational Resources Information Center

Evans, C. D.

This paper describes the experiences of the industrial research laboratory of Kodak Ltd. in finding and providing a computer terminal most suited to its very varied requirements. These requirements include bibliographic and scientific data searching and access to a number of worldwide computing services for scientific computing work. The provision…

Amplify scientific discovery with artificial intelligence

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

Gil, Yolanda; Greaves, Mark T.; Hendler, James

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

A distributed computing environment with support for constraint-based task scheduling and scientific experimentation

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

Ahrens, J.P.; Shapiro, L.G.; Tanimoto, S.L.

1997-04-01

This paper describes a computing environment which supports computer-based scientific research work. Key features include support for automatic distributed scheduling and execution and computer-based scientific experimentation. A new flexible and extensible scheduling technique that is responsive to a user`s scheduling constraints, such as the ordering of program results and the specification of task assignments and processor utilization levels, is presented. An easy-to-use constraint language for specifying scheduling constraints, based on the relational database query language SQL, is described along with a search-based algorithm for fulfilling these constraints. A set of performance studies show that the environment can schedule and executemore » program graphs on a network of workstations as the user requests. A method for automatically generating computer-based scientific experiments is described. Experiments provide a concise method of specifying a large collection of parameterized program executions. The environment achieved significant speedups when executing experiments; for a large collection of scientific experiments an average speedup of 3.4 on an average of 5.5 scheduled processors was obtained.« less

Computer-Supported Aids to Making Sense of Scientific Articles: Cognitive, Motivational, and Attitudinal Effects

ERIC Educational Resources Information Center

Gegner, Julie A.; Mackay, Donald H. J.; Mayer, Richard E.

2009-01-01

High school students can access original scientific research articles on the Internet, but may have trouble understanding them. To address this problem of online literacy, the authors developed a computer-based prototype for guiding students' comprehension of scientific articles. High school students were asked to read an original scientific…

Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization

ERIC Educational Resources Information Center

Weiss, Charles J.

2017-01-01

The Scientific Computing for Chemists course taught at Wabash College teaches chemistry students to use the Python programming language, Jupyter notebooks, and a number of common Python scientific libraries to process, analyze, and visualize data. Assuming no prior programming experience, the course introduces students to basic programming and…

Computational chemistry in pharmaceutical research: at the crossroads.

PubMed

Bajorath, Jürgen

2012-01-01

Computational approaches are an integral part of pharmaceutical research. However, there are many of unsolved key questions that limit the scientific progress in the still evolving computational field and its impact on drug discovery. Importantly, a number of these questions are not new but date back many years. Hence, it might be difficult to conclusively answer them in the foreseeable future. Moreover, the computational field as a whole is characterized by a high degree of heterogeneity and so is, unfortunately, the quality of its scientific output. In light of this situation, it is proposed that changes in scientific standards and culture should be seriously considered now in order to lay a foundation for future progress in computational research.

[Earth and Space Sciences Project Services for NASA HPCC

NASA Technical Reports Server (NTRS)

Merkey, Phillip

2002-01-01

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.

Scholarly literature and the press: scientific impact and social perception of physics computing

NASA Astrophysics Data System (ADS)

Pia, M. G.; Basaglia, T.; Bell, Z. W.; Dressendorfer, P. V.

2014-06-01

The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the relationship between the scientific impact and the social perception of HEP physics research versus that of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing via press releases from the major HEP laboratories would be beneficial to the high energy physics community.

Software Reuse Methods to Improve Technological Infrastructure for e-Science

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

NASA Astrophysics Data System (ADS)

Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

Grid computing has widely evolved over the past years, and its capabilities have found their way even into business products and are no longer relegated to scientific applications. Today, grid computing technology is not restricted to a set of specific grid open source or industrial products, but rather it is comprised of a set of capabilities virtually within any kind of software to create shared and highly collaborative production environments. These environments are focused on computational (workload) capabilities and the integration of information (data) into those computational capabilities. An active grid computing application field is the fully virtualization of scientific instruments in order to increase their availability and decrease operational and maintaining costs. Computational and information grids allow to manage real-world objects in a service-oriented way using industrial world-spread standards.

78 FR 6087 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-29

... INFORMATION CONTACT: Melea Baker, Office of Advanced Scientific Computing Research; SC-21/Germantown Building... Theory and Experiment (INCITE) Public Comment (10-minute rule) Public Participation: The meeting is open...

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

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

Highly parallel computation

NASA Technical Reports Server (NTRS)

Denning, Peter J.; Tichy, Walter F.

1990-01-01

Highly parallel computing architectures are the only means to achieve the computation rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines and current research focuses on which architectures designated as multiple instruction multiple datastream (MIMD) and single instruction multiple datastream (SIMD) have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed.

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

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

Peisert, Sean; Potok, Thomas E.; Jones, Todd

At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues includedmore » research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the three topics and a representative of each of the four major DOE Office of Science Advanced Scientific Computing Research Facilities: the Argonne Leadership Computing Facility (ALCF), the Energy Sciences Network (ESnet), the National Energy Research Scientific Computing Center (NERSC), and the Oak Ridge Leadership Computing Facility (OLCF). The rest of the workshop consisted of topical breakout discussions and focused writing periods that produced much of this report.« less

Building Cognition: The Construction of Computational Representations for Scientific Discovery

ERIC Educational Resources Information Center

Chandrasekharan, Sanjay; Nersessian, Nancy J.

2015-01-01

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…

DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

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

Hey, Tony; Agarwal, Deborah; Borgman, Christine

The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

FY 1998 Scientific and Technical Reports, Articles, Papers, and Presentations

NASA Technical Reports Server (NTRS)

Waits, J. E. Turner (Compiler)

1999-01-01

This document presents formal NASA technical reports, papers published in technical journals, and presentations by MSFC (Marshall Space Flight Center) personnel in FY98. It also includes papers of MSFC contractors. After being announced in STAR, all of the NASA series reports may be obtained from the National Technical Information Service. The information in this report may be of value to the scientific and engineering community in determining what information has been published and what is available.

Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

ERIC Educational Resources Information Center

Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

2016-01-01

In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

ERIC Educational Resources Information Center

Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

An Interdisciplinary Guided Inquiry on Estuarine Transport Using a Computer Model in High School Classrooms

ERIC Educational Resources Information Center

Chan, Kit Yu Karen; Yang, Sylvia; Maliska, Max E.; Grunbaum, Daniel

2012-01-01

The National Science Education Standards have highlighted the importance of active learning and reflection for contemporary scientific methods in K-12 classrooms, including the use of models. Computer modeling and visualization are tools that researchers employ in their scientific inquiry process, and often computer models are used in…

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

ERIC Educational Resources Information Center

Younge, Andrew J.

2016-01-01

With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

ERIC Educational Resources Information Center

Tuncer, Murat

2013-01-01

Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

The Impact of Three-Dimensional Computational Modeling on Student Understanding of Astronomical Concepts: A Quantitative Analysis

ERIC Educational Resources Information Center

Hansen, John; Barnett, Michael; MaKinster, James; Keating, Thomas

2004-01-01

The increased availability of computational modeling software has created opportunities for students to engage in scientific inquiry through constructing computer-based models of scientific phenomena. However, despite the growing trend of integrating technology into science curricula, educators need to understand what aspects of these technologies…

Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob

2003-01-01

The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.

STS-98 Destiny in Atlantis's payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- At Launch Pad 39A, the U.S. Laboratory Destiny waits in Atlantis'''s payload bay for closure of the payload bay doors. Destiny, a key element in the construction of the International Space Station, is 28 feet long and weighs 16 tons. This research and command-and-control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. Destiny will be launched Feb. 7 on STS-98, the seventh construction flight to the ISS.

USRA/RIACS

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1992-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under a cooperative agreement with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing; Advanced Methods for Scientific Computing; Learning Systems; High Performance Networks and Technology; Graphics, Visualization, and Virtual Environments.

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

NASA Astrophysics Data System (ADS)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

A toolbox and a record for scientific model development

NASA Technical Reports Server (NTRS)

Ellman, Thomas

1994-01-01

Scientific computation can benefit from software tools that facilitate construction of computational models, control the application of models, and aid in revising models to handle new situations. Existing environments for scientific programming provide only limited means of handling these tasks. This paper describes a two pronged approach for handling these tasks: (1) designing a 'Model Development Toolbox' that includes a basic set of model constructing operations; and (2) designing a 'Model Development Record' that is automatically generated during model construction. The record is subsequently exploited by tools that control the application of scientific models and revise models to handle new situations. Our two pronged approach is motivated by our belief that the model development toolbox and record should be highly interdependent. In particular, a suitable model development record can be constructed only when models are developed using a well defined set of operations. We expect this research to facilitate rapid development of new scientific computational models, to help ensure appropriate use of such models and to facilitate sharing of such models among working computational scientists. We are testing this approach by extending SIGMA, and existing knowledge-based scientific software design tool.

Computer Series, 98. Electronics for Scientists: A Computer-Intensive Approach.

ERIC Educational Resources Information Center

Scheeline, Alexander; Mork, Brian J.

1988-01-01

Reports the design for a principles-before-details presentation of electronics for an instrumental analysis class. Uses computers for data collection and simulations. Requires one semester with two 2.5-hour periods and two lectures per week. Includes lab and lecture syllabi. (MVL)

The Petascale Data Storage Institute

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

Gibson, Garth; Long, Darrell; Honeyman, Peter

2013-07-01

Petascale computing infrastructures for scientific discovery make petascale demands on information storage capacity, performance, concurrency, reliability, availability, and manageability.The Petascale Data Storage Institute focuses on the data storage problems found in petascale scientific computing environments, with special attention to community issues such as interoperability, community buy-in, and shared tools.The Petascale Data Storage Institute is a collaboration between researchers at Carnegie Mellon University, National Energy Research Scientific Computing Center, Pacific Northwest National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratory, Los Alamos National Laboratory, University of Michigan, and the University of California at Santa Cruz.

The need for scientific software engineering in the pharmaceutical industry

NASA Astrophysics Data System (ADS)

Luty, Brock; Rose, Peter W.

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

The need for scientific software engineering in the pharmaceutical industry.

PubMed

Luty, Brock; Rose, Peter W

2017-03-01

Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency.

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

DOE PAGES

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

2015-02-19

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

75 FR 65639 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-26

...: Computational Biology Special Emphasis Panel A. Date: October 29, 2010. Time: 2 p.m. to 3:30 p.m. Agenda: To.... Name of Committee: Center for Scientific Review Special Emphasis Panel; Member Conflict: Computational...

The Effects of Inquiry-Based Computer Simulation with Cooperative Learning on Scientific Thinking and Conceptual Understanding of Gas Laws

ERIC Educational Resources Information Center

Abdullah, Sopiah; Shariff, Adilah

2008-01-01

The purpose of the study was to investigate the effects of inquiry-based computer simulation with heterogeneous-ability cooperative learning (HACL) and inquiry-based computer simulation with friendship cooperative learning (FCL) on (a) scientific reasoning (SR) and (b) conceptual understanding (CU) among Form Four students in Malaysian Smart…

64 slice-coronary computed tomography sensitivity and specificity in the evaluation of coronary artery bypass graft stenosis: A meta-analysis.

PubMed

Barbero, Umberto; Iannaccone, Mario; d'Ascenzo, Fabrizio; Barbero, Cristina; Mohamed, Abdirashid; Annone, Umberto; Benedetto, Sara; Celentani, Dario; Gagliardi, Marco; Moretti, Claudio; Gaita, Fiorenzo

2016-08-01

A non-invasive approach to define grafts patency and stenosis in the follow-up of coronary artery bypass graft (CABG) patients may be an interesting alternative to coronary angiography. 64-slice-coronary computed tomography is nowadays a diffused non-invasive method that permits an accurate evaluation of coronary stenosis, due to a high temporal and spatial resolution. However, its sensitivity and specificity in CABG evaluation has to be clearly defined, since published studies used different protocols and scanners. We collected all studies investigating patients with stable symptoms and previous CABG and reporting the comparison between diagnostic performances of invasive coronary angiography and 64-slice-coronary computed tomography. As a result, sensitivity and specificity of 64-slice-coronary computed tomography for CABG occlusion were 0.99 (95% CI 0.97-1.00) and 0.99 (95% CI: 0.99-1.00) with an area under the curve (AUC) of 0.99. 64-slice-coronary computed tomography sensitivity and specificity for the presence of any CABG stenosis >50% were 0.98 (95% CI: 0.97-0.99) and 0.98 (95% CI: 0.96-0.98), while AUC was 0.99. At meta-regression, neither the age nor the time from graft implantation had effect on sensitivity and specificity of 64-slice-coronary computed tomography detection of significant CABG stenosis or occlusion. In conclusion 64-slice-coronary computed tomography confirmed its high sensitivity and specificity in CABG stenosis or occlusion evaluation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

RIACS/USRA

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1993-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on 6 June 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Parallel Computing, Advanced Methods for Scientific Computing, High Performance Networks and Technology, and Learning Systems. Parallel compiler techniques, adaptive numerical methods for flows in complicated geometries, and optimization were identified as important problems to investigate for ARC's involvement in the Computational Grand Challenges of the next decade.

The emergence of spatial cyberinfrastructure.

PubMed

Wright, Dawn J; Wang, Shaowen

2011-04-05

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge.

The emergence of spatial cyberinfrastructure

PubMed Central

Wright, Dawn J.; Wang, Shaowen

2011-01-01

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge. PMID:21467227

Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

STS-98 payload U.S. Lab Destiny is moved into Atlantis' payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- Workers in the Payload Changeout Room begin moving the U.S. Lab Destiny to the orbiter'''s payload bay. The PCR is the enclosed, environmentally controlled portion of the rotating service structure that supports payload delivery at the launch pad and vertical installation in the orbiter payload bay. Destiny, a key element in the construction of the International Space Station, is 28 feet long and weighs 16 tons. This research and command-and- control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. STS-98 is the seventh construction flight to the ISS. Launch of STS-98 is scheduled for Jan. 19 at 2:11 a.m. EST.

Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

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

Prowell, Stacy J; Symons, Christopher T

2015-01-01

Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

Quantum Testbeds Stakeholder Workshop (QTSW) Report meeting purpose and agenda.

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

Hebner, Gregory A.

Quantum computing (QC) is a promising early-stage technology with the potential to provide scientific computing capabilities far beyond what is possible with even an Exascale computer in specific problems of relevance to the Office of Science. These include (but are not limited to) materials modeling, molecular dynamics, and quantum chromodynamics. However, commercial QC systems are not yet available and the technical maturity of current QC hardware, software, algorithms, and systems integration is woefully incomplete. Thus, there is a significant opportunity for DOE to define the technology building blocks, and solve the system integration issues to enable a revolutionary tool. Oncemore » realized, QC will have world changing impact on economic competitiveness, the scientific enterprise, and citizen well-being. Prior to this workshop, DOE / Office of Advanced Scientific Computing Research (ASCR) hosted a workshop in 2015 to explore QC scientific applications. The goal of that workshop was to assess the viability of QC technologies to meet the computational requirements in support of DOE’s science and energy mission and to identify the potential impact of these technologies.« less

Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

DOE PAGES

Haidar, Azzam; Jagode, Heike; Vaccaro, Phil; ...

2018-03-22

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

Investigating power capping toward energy-efficient scientific applications: Investigating Power Capping toward Energy-Efficient Scientific Applications

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

Haidar, Azzam; Jagode, Heike; Vaccaro, Phil

The emergence of power efficiency as a primary constraint in processor and system design poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers, which may house petascale or exascale-level computing systems. At these extreme scales, understanding and improving the energy efficiency of numerical libraries and their related applications becomes a crucial part of the successful implementation and operation of the computing system. In this paper, we study and investigate the practice of controlling a compute system's power usage, and we explore howmore » different power caps affect the performance of numerical algorithms with different computational intensities. Further, we determine the impact, in terms of performance and energy usage, that these caps have on a system running scientific applications. This analysis will enable us to characterize the types of algorithms that benefit most from these power management schemes. Our experiments are performed using a set of representative kernels and several popular scientific benchmarks. Lastly, we quantify a number of power and performance measurements and draw observations and conclusions that can be viewed as a roadmap to achieving energy efficiency in the design and execution of scientific algorithms.« less

A Computing Environment to Support Repeatable Scientific Big Data Experimentation of World-Wide Scientific Literature

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

Schlicher, Bob G; Kulesz, James J; Abercrombie, Robert K

A principal tenant of the scientific method is that experiments must be repeatable and relies on ceteris paribus (i.e., all other things being equal). As a scientific community, involved in data sciences, we must investigate ways to establish an environment where experiments can be repeated. We can no longer allude to where the data comes from, we must add rigor to the data collection and management process from which our analysis is conducted. This paper describes a computing environment to support repeatable scientific big data experimentation of world-wide scientific literature, and recommends a system that is housed at the Oakmore » Ridge National Laboratory in order to provide value to investigators from government agencies, academic institutions, and industry entities. The described computing environment also adheres to the recently instituted digital data management plan mandated by multiple US government agencies, which involves all stages of the digital data life cycle including capture, analysis, sharing, and preservation. It particularly focuses on the sharing and preservation of digital research data. The details of this computing environment are explained within the context of cloud services by the three layer classification of Software as a Service , Platform as a Service , and Infrastructure as a Service .« less

Idle waves in high-performance computing

NASA Astrophysics Data System (ADS)

Markidis, Stefano; Vencels, Juris; Peng, Ivy Bo; Akhmetova, Dana; Laure, Erwin; Henri, Pierre

2015-01-01

The vast majority of parallel scientific applications distributes computation among processes that are in a busy state when computing and in an idle state when waiting for information from other processes. We identify the propagation of idle waves through processes in scientific applications with a local information exchange between the two processes. Idle waves are nondispersive and have a phase velocity inversely proportional to the average busy time. The physical mechanism enabling the propagation of idle waves is the local synchronization between two processes due to remote data dependency. This study provides a description of the large number of processes in parallel scientific applications as a continuous medium. This work also is a step towards an understanding of how localized idle periods can affect remote processes, leading to the degradation of global performance in parallel scientific applications.

STS-98 Destiny in Atlantis's payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- The U.S. Laboratory Destiny rests once again in Atlantis'''s payload bay, at Launch Pad 39A. Closing of the payload bay doors is imminent. Destiny, a key element in the construction of the International Space Station, is 28 feet long and weighs 16 tons. This research and command-and-control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. Destiny will be launched Feb. 7 on STS-98, the seventh construction flight to the ISS.

KSC-00pp1950

NASA Image and Video Library

2000-12-22

In the Space Station Processing Facility, workers along the edge of the payload canister watch as the U.S. Lab Destiny is lowered into the canister. A key element in the construction of the International Space Station, Destiny is 28 feet long and weighs 16 tons. This research and command-and-control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. Destiny will fly on STS-98, the seventh construction flight to the ISS. Launch of STS-98 is scheduled for Jan. 19 at 2:11 a.m. EST

Comparisons of some large scientific computers

NASA Technical Reports Server (NTRS)

Credeur, K. R.

1981-01-01

In 1975, the National Aeronautics and Space Administration (NASA) began studies to assess the technical and economic feasibility of developing a computer having sustained computational speed of one billion floating point operations per second and a working memory of at least 240 million words. Such a powerful computer would allow computational aerodynamics to play a major role in aeronautical design and advanced fluid dynamics research. Based on favorable results from these studies, NASA proceeded with developmental plans. The computer was named the Numerical Aerodynamic Simulator (NAS). To help insure that the estimated cost, schedule, and technical scope were realistic, a brief study was made of past large scientific computers. Large discrepancies between inception and operation in scope, cost, or schedule were studied so that they could be minimized with NASA's proposed new compter. The main computers studied were the ILLIAC IV, STAR 100, Parallel Element Processor Ensemble (PEPE), and Shuttle Mission Simulator (SMS) computer. Comparison data on memory and speed were also obtained on the IBM 650, 704, 7090, 360-50, 360-67, 360-91, and 370-195; the CDC 6400, 6600, 7600, CYBER 203, and CYBER 205; CRAY 1; and the Advanced Scientific Computer (ASC). A few lessons learned conclude the report.

Diagnostic accuracy of dual-source computed tomography angiography for the detection of coronary in-stent restenosis: A systematic review and meta-analysis.

PubMed

Liu, Wen-Jun; Li, Gui-Zhen; Liu, Hai-Feng; Lei, Jun-Qiang

2018-04-01

We sought to perform a meta-analysis to comprehensively evaluate the diagnostic accuracy of dual-source computed tomography angiography (DSCTA) in detecting coronary in-stent restenosis (CISR) when compared to invasive coronary angiography. The stent-based research studies in which DSCTA was used as diagnostic tool for CISR, as recent as of October 2017, from several reputed scientific libraries (PubMed, Embase, Scopus, The Cochrane Library, and Web of Science) were evaluated. Study inclusion, data extraction, and risk bias assessment were conducted by two researchers independently. Pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under summary receiver operator characteristics (SROC) curve (AUC) were calculated to assess the diagnostic value. In addition, heterogeneity and subgroup analysis were also carried out. A total of 13 studies with a total of 894 patients and 1384 assessable stents were included. The pooled results of DSCTA diagnosing CISR were as follows: SEN 0.92 (95% confidence interval [CI] 0.87-0.96), SPE 0.91 (95% CI 0.87-0.94), PLR 9.83 (95% CI 6.93-13.94), NLR 0.09 (95% CI 0.05-0.15), DOR 114.73 (95% CI 64.12-205.28), and AUC 0.97 (95% CI 0.95-0.98), respectively. The subgroup analysis result suggested that DSTCA performed significantly better in CISR detection when the stent diameter was ≥3 mm compared with the stent diameter <3 mm: (0.98 [0.97-0.99] vs 0.82 [0.79-0.86]) with P < .05. This study revealed that DSCTA has excellent diagnostic performance for detecting CISR and may serve as an alternative for further patient evaluation with CISR, especially for stent diameter ≥3 mm. © 2018 Wiley Periodicals, Inc.

USSR Report: Cybernetics, Computers and Automation Technology. No. 69.

DTIC Science & Technology

1983-05-06

computers in multiprocessor and multistation design , control and scientific research automation systems. The results of comparing the efficiency of...Podvizhnaya, Scientific Research Institute of Control Computers, Severodonetsk] [Text] The most significant change in the design of the SM-2M compared to...UPRAVLYAYUSHCHIYE SISTEMY I MASHINY, Nov-Dec 82) 95 APPLICATIONS Kiev Automated Control System, Design Features and Prospects for Development (V. A

Artificial intelligence for the EChO mission planning tool

NASA Astrophysics Data System (ADS)

Garcia-Piquer, Alvaro; Ribas, Ignasi; Colomé, Josep

2015-12-01

The Exoplanet Characterisation Observatory (EChO) has as its main goal the measurement of atmospheres of transiting planets. This requires the observation of two types of events: primary and secondary eclipses. In order to yield measurements of sufficient Signal-to-Noise Ratio to fulfil the mission objectives, the events of each exoplanet have to be observed several times. In addition, several criteria have to be considered to carry out each observation, such as the exoplanet visibility, its event duration, and no overlapping with other tasks. It is expected that a suitable mission plan increases the efficiency of telescope operation, which will represent an important benefit in terms of scientific return and operational costs. Nevertheless, to obtain a long term mission plan becomes unaffordable for human planners due to the complexity of computing the huge number of possible combinations for finding an optimum solution. In this contribution we present a long term mission planning tool based on Genetic Algorithms, which are focused on solving optimization problems such as the planning of several tasks. Specifically, the proposed tool finds a solution that highly optimizes the defined objectives, which are based on the maximization of the time spent on scientific observations and the scientific return (e.g., the coverage of the mission survey). The results obtained on the large experimental set up support that the proposed scheduler technology is robust and can function in a variety of scenarios, offering a competitive performance which does not depend on the collection of exoplanets to be observed. Specifically, the results show that, with the proposed tool, EChO uses 94% of the available time of the mission, so the amount of downtime is small, and it completes 98% of the targets.

Validation of a modified table to map the 1998 Abbreviated Injury Scale to the 2008 scale and the use of adjusted severities.

PubMed

Tohira, Hideo; Jacobs, Ian; Mountain, David; Gibson, Nick; Yeo, Allen; Ueno, Masato; Watanabe, Hiroaki

2011-12-01

The Abbreviated Injury Scale 2008 (AIS 2008) is the most recent injury coding system. A mapping table from a previous AIS 98 to AIS 2008 is available. However, AIS 98 codes that are unmappable to AIS 2008 codes exist in this table. Furthermore, some AIS 98 codes can be mapped to multiple candidate AIS 2008 codes with different severities. We aimed to modify the original table to adjust the severities and to validate these changes. We modified the original table by adding links from unmappable AIS 98 codes to AIS 2008 codes. We applied the original table and our modified table to AIS 98 codes for major trauma patients. We also assigned candidate codes with different severities the weighted averages of their severities as an adjusted severity. The proportion of cases whose injury severity scores (ISSs) were computable were compared. We also compared the agreement of the ISS and New ISS (NISS) between manually determined AIS 2008 codes (MAN) and mapped codes by using our table (MAP) with unadjusted or adjusted severities. All and 72.3% of cases had their ISSs computed by our modified table and the original table, respectively. The agreement between MAN and MAP with respect to the ISS and NISS was substantial (intraclass correlation coefficient = 0.939 for ISS and 0.943 for NISS). Using adjusted severities, the agreements of the ISS and NISS improved to 0.953 (p = 0.11) and 0.963 (p = 0.007), respectively. Our modified mapping table seems to allow more ISSs to be computed than the original table. Severity scores exhibited substantial agreement between MAN and MAP. The use of adjusted severities improved these agreements further.

Accelerating scientific discovery : 2007 annual report.

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

Beckman, P.; Dave, P.; Drugan, C.

2008-11-14

As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis ofmore » Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide guidance for applications that are transitioning to petascale as well as to produce software that facilitates their development, such as the MPICH library, which provides a portable and efficient implementation of the MPI standard--the prevalent programming model for large-scale scientific applications--and the PETSc toolkit that provides a programming paradigm that eases the development of many scientific applications on high-end computers.« less

Krikalev on middeck with laptop computer

NASA Image and Video Library

1998-12-06

S88-E-5041 (12-06-98) --- Sergei Krikalev, mission specialist representing the Russian Space Agency (RSA), works on a laptop computer on Endeavour's middeck. The scene was photographed shortly after the successful mating of Unity with the shuttle's docking system.

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

PubMed

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

2013-01-28

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

High-performance scientific computing in the cloud

NASA Astrophysics Data System (ADS)

Jorissen, Kevin; Vila, Fernando; Rehr, John

2011-03-01

Cloud computing has the potential to open up high-performance computational science to a much broader class of researchers, owing to its ability to provide on-demand, virtualized computational resources. However, before such approaches can become commonplace, user-friendly tools must be developed that hide the unfamiliar cloud environment and streamline the management of cloud resources for many scientific applications. We have recently shown that high-performance cloud computing is feasible for parallelized x-ray spectroscopy calculations. We now present benchmark results for a wider selection of scientific applications focusing on electronic structure and spectroscopic simulation software in condensed matter physics. These applications are driven by an improved portable interface that can manage virtual clusters and run various applications in the cloud. We also describe a next generation of cluster tools, aimed at improved performance and a more robust cluster deployment. Supported by NSF grant OCI-1048052.

Activities of the Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1994-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

The future of scientific workflows

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

Deelman, Ewa; Peterka, Tom; Altintas, Ilkay

Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less

STS-98 payload U.S. Lab Destiny is moved into Atlantis' payload bay

NASA Technical Reports Server (NTRS)

2001-01-01

KENNEDY SPACE CENTER, Fla. -- Technicians in the Payload Changeout Room work to secure the U.S. Lab Destiny in the orbiter'''s payload bay. The PCR is the enclosed, environmentally controlled portion of the rotating service structure that supports payload delivery at the launch pad and vertical installation in the orbiter payload bay. Destiny, a key element in the construction of the International Space Station, is 28 feet long and weighs 16 tons. This research and command-and- control center is the most sophisticated and versatile space laboratory ever built. It will ultimately house a total of 23 experiment racks for crew support and scientific research. STS-98 is the seventh construction flight to the ISS. Launch of STS-98 is scheduled for Jan. 19 at 2:11 a.m. EST.

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

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

Potok, Thomas; Schuman, Catherine; Patton, Robert

The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshopmore » we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.« less

Computational science: shifting the focus from tools to models

PubMed Central

Hinsen, Konrad

2014-01-01

Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication of big data sets or complex models. As a consequence, these crucial pieces of information no longer enter the scientific record. Moreover, they have become prisoners of scientific software: many models exist only as software implementations, and the data are often stored in proprietary formats defined by the software. In this article, I argue that this emphasis on software tools over models and data is detrimental to science in the long term, and I propose a means by which this can be reversed. PMID:25309728

Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

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

Gerber, Richard; Hack, James; Riley, Katherine

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, andmore » deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.« less

The International Conference on Vector and Parallel Computing (2nd)

DTIC Science & Technology

1989-01-17

Computation of the SVD of Bidiagonal Matrices" ...................................... 11 " Lattice QCD -As a Large Scale Scientific Computation...vectorizcd for the IBM 3090 Vector Facility. In addition, elapsed times " Lattice QCD -As a Large Scale Scientific have been reduced by using 3090...benchmarked Lattice QCD on a large number ofcompu- come from the wavefront solver routine. This was exten- ters: CrayX-MP and Cray 2 (vector

Multi-threading: A new dimension to massively parallel scientific computation

NASA Astrophysics Data System (ADS)

Nielsen, Ida M. B.; Janssen, Curtis L.

2000-06-01

Multi-threading is becoming widely available for Unix-like operating systems, and the application of multi-threading opens new ways for performing parallel computations with greater efficiency. We here briefly discuss the principles of multi-threading and illustrate the application of multi-threading for a massively parallel direct four-index transformation of electron repulsion integrals. Finally, other potential applications of multi-threading in scientific computing are outlined.

Comment on "Most computational hydrology is not reproducible, so is it really science?" by Christopher Hutton et al.

NASA Astrophysics Data System (ADS)

Añel, Juan A.

2017-03-01

Nowadays, the majority of the scientific community is not aware of the risks and problems associated with an inadequate use of computer systems for research, mostly for reproducibility of scientific results. Such reproducibility can be compromised by the lack of clear standards and insufficient methodological description of the computational details involved in an experiment. In addition, the inappropriate application or ignorance of copyright laws can have undesirable effects on access to aspects of great importance of the design of experiments and therefore to the interpretation of results.