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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

In Situ Visualization for Computational Science

In situ visualization, i.e., visualizing simulation data as it is generated, is an emerging processing paradigm in response to trends in the area of high-performance computing. This paradigm holds great promise in its ability to access increased spatio-temporal resolution and leverage extensive computational power. However, the paradigm is also widely viewed as limiting when it comes to exploration-oriented use cases and further will require visualization systems to become more and more complicated and constrained. Additionally, there are many open research topics with in situ visualization. The Dagstuhl seminar 18271 "In Situ Visualization for Computational Science" brought together researchers and practitioners from three communities (computational science, high-performance computing, and scientific visualization) to share interesting findings, to identify lines of open research, and to determine a medium-term research agenda that addresses the most pressing problems. This report summarizes the outcomes and findings of the seminar.

Bauer, Andy↗
NASA NTRS1982

Computer Science Research at Langley

A workshop was held at Langley Research Center, November 2-5, 1981, to highlight ongoing computer science research at Langley and to identify additional areas of research based upon the computer user requirements. A panel discussion was held in each of nine application areas, and these are summarized in the proceedings. Slides presented by the invited speakers are also included. A survey of scientific, business, data reduction, and microprocessor computer users helped identify areas of focus for the workshop. Several areas of computer science which are of most concern to the Langley computer users were identified during the workshop discussions. These include graphics, distributed processing, programmer support systems and tools, database management, and numerical methods.

Voigt, S. J.↗
NASA NTRS1984

Research in applied mathematics, numerical analysis, and computer science

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Source record↗
DOE OSTI2018

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments— including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers—is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.

computational science and engineering↗
DOE OSTI2024

The U.S. Department of Energy Computational Science Graduate Fellowship, 1991-2021: Follow-Up Study Shows Major Impact on Recipients and the Scientific Workforce

Since 1991, the U.S. Department of Energy Computational Science Graduate Fellowship (DOE CSGF) has addressed DOE National Laboratory needs as well as demands in the national workforce for trained professionals in computational science and engineering. Sponsored by the Department of Energy's Office of Science and the National Nuclear Security Administration, the DOE CSGF supports doctoral students in the pursuit of novel scientific or engineering discoveries using high-performance computing (HPC) resources. To meet the program’s core requirements, recipients participate in multidisciplinary studies, carry out at least one 12-week DOE laboratory research practicum, and contribute to an annual program review where the fellows present their research for sponsor review. The Krell Institute, which as managed the fellowship on behalf of the DOE since 1997, has commissioned several follow-up studies to examine the DOE CSGF recipients’ characteristics, fellows’ outcomes and professional accomplishments, alumni’s career paths and achievements, and recipients’ impact on national priorities through research and education.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The U.S. Department of Energy Computational Science Graduate Fellowship, 1991-2021: Follow-Up Study Shows Major Impact on Recipients and the Scientific Workforce

Since 1991, the U.S. Department of Energy Computational Science Graduate Fellowship (DOE CSGF) has addressed DOE National Laboratory needs as well as demands in the national workforce for trained professionals in computational science and engineering. Sponsored by the Department of Energy's Office of Science and the National Nuclear Security Administration, the DOE CSGF supports doctoral students in the pursuit of novel scientific or engineering discoveries using high-performance computing (HPC) resources. To meet the program’s core requirements, recipients participate in multidisciplinary studies, carry out at least one 12-week DOE laboratory research practicum, and contribute to an annual program review where the fellows present their research for sponsor review. The Krell Institute, which as managed the fellowship on behalf of the DOE since 1997, has commissioned several follow-up studies to examine the DOE CSGF recipients’ characteristics, fellows’ outcomes and professional accomplishments, alumni’s career paths and achievements, and recipients’ impact on national priorities through research and education.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

The growth of the UniTree mass storage system at the NASA Center for Computational Sciences

In October 1992, the NASA Center for Computational Sciences made its Convex-based UniTree system generally available to users. The ensuing months saw the growth of near-online data from nil to nearly three terabytes, a doubling of the number of CPU's on the facility's Cray YMP (the primary data source for UniTree), and the necessity for an aggressive regimen for repacking sparse tapes and hierarchical 'vaulting' of old files to freestanding tape. Connectivity was enhanced as well with the addition of UltraNet HiPPI. This paper describes the increasing demands placed on the storage system's performance and throughput that resulted from the significant augmentation of compute-server processor power and network speed.

Tarshish, Adina↗
NASA NTRS1994

Research in progress in applied mathematics, numerical analysis, fluid mechanics, and computer science

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1993 through March 31, 1994. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.

Source record↗
NASA NTRS1991

A research program in empirical computer science

During the grant reporting period our primary activities have been to begin preparation for the establishment of a research program in experimental computer science. The focus of research in this program will be safety-critical systems. Many questions that arise in the effort to improve software dependability can only be addressed empirically. For example, there is no way to predict the performance of the various proposed approaches to building fault-tolerant software. Performance models, though valuable, are parameterized and cannot be used to make quantitative predictions without experimental determination of underlying distributions. In the past, experimentation has been able to shed some light on the practical benefits and limitations of software fault tolerance. It is common, also, for experimentation to reveal new questions or new aspects of problems that were previously unknown. A good example is the Consistent Comparison Problem that was revealed by experimentation and subsequently studied in depth. The result was a clear understanding of a previously unknown problem with software fault tolerance. The purpose of a research program in empirical computer science is to perform controlled experiments in the area of real-time, embedded control systems. The goal of the various experiments will be to determine better approaches to the construction of the software for computing systems that have to be relied upon. As such it will validate research concepts from other sources, provide new research results, and facilitate the transition of research results from concepts to practical procedures that can be applied with low risk to NASA flight projects. The target of experimentation will be the production software development activities undertaken by any organization prepared to contribute to the research program. Experimental goals, procedures, data analysis and result reporting will be performed for the most part by the University of Virginia.

Knight, J. C.↗
NASA NTRS1986

Research in computer science

Various graduate research activities in the field of computer science are reported. Among the topics discussed are: (1) failure probabilities in multi-version software; (2) Gaussian Elimination on parallel computers; (3) three dimensional Poisson solvers on parallel/vector computers; (4) automated task decomposition for multiple robot arms; (5) multi-color incomplete cholesky conjugate gradient methods on the Cyber 205; and (6) parallel implementation of iterative methods for solving linear equations.

Ortega, J. M.↗
DOE OSTI2026

Computational Science at the National Laboratory of the Rockies

Computational methods underpin advancing the science and engineering of energy technologies and developing a knowledge base to optimize energy systems. NLR's Computational Science Center (CSC) proudly focuses on providing the service of computing, advancing the science of computing, and enabling DOE missions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Storage and network bandwidth requirements through the year 2000 for the NASA Center for Computational Sciences

The data storage and retrieval demands of space and Earth sciences researchers have made the NASA Center for Computational Sciences (NCCS) Mass Data Storage and Delivery System (MDSDS) one of the world's most active Convex UniTree systems. Science researchers formed the NCCS's Computer Environments and Research Requirements Committee (CERRC) to relate their projected supercomputing and mass storage requirements through the year 2000. Using the CERRC guidelines and observations of current usage, some detailed projections of requirements for MDSDS network bandwidth and mass storage capacity and performance are presented.

Salmon, Ellen↗
NASA NTRS1985

Research in computer science

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.

Ortega, J. M.↗
NASA NTRS1986

First 3 years of operation of RIACS (Research Institute for Advanced Computer Science) (1983-1985)

The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.

Denning, P. J.↗
DOE OSTI2019

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme — Edge Neural Network — for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2019

PCS: A Productive Computational Science Platform

As modern supercomputers continue to be increasingly heterogeneous with diverse computational accelerators, software becomes a critical aspect necessary to fully exploit these accelerators while not increasing the effort and time required to make variable scientific discovery in the face of complicated programming environments introduced by these accelerators. This paper presents PCS, a productive computational science platform for cluster-scale heterogeneous computing. The PCS platform by design follows a basic principle that, multiple programming models in a unified programming environment, is essential to facilitate large-scale, accelerator-aware, heterogeneous computing for next- generation scientific applications. We propose a new scheme - Edge Neural Network - for managing regularity in large dataflow graphs using higher-order bulk synchronous operators, providing a foundation for formalizing computational models for cluster-wide dataflow programming of heterogeneous clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hands-On Computer Science: The Array of Things Experimental Urban Instrument

Chicago's Array of Things (AoT) project is aptly described as a technology experiment or a "smart city" prototype. The concept of such an extensible "instrument" arose within a larger translational research vision applying computer science and engineering research for the multidimensional benefit of people and communities in cities. The AoT project hypothesized that wireless intelligent sensor networks could enable both quantitative social science and urban monitoring while also stimulating youth interest in science and technology. Successful deployment of such sensor networks could provide open data from urban measurements not only in support of diverse research questions-in environmental dynamics, urban architecture, engineering, and social sciences-but also informing community groups and city planners. Further, the AoT project and its successor SAGE project are a computer science and engineering experiment, but its success is inextricably tied to community engagement and experiential education. Simply put, community acceptance is a prerequisite to installing and testing the instrument.

97 MATHEMATICS AND COMPUTING↗