Search NASA⌕ Search

SEARCH · Search NASA

Results for “computing systems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Berthing mechanism final test report and program assessment

The purpose is to document the testing performed on both hardware and software developed under the Space Station Berthing Mechanisms Program. Testing of the mechanism occurred at three locations. Several system components, e.g., actuators and computer systems, were functionally tested before assembly. A series of post assembly tests were performed. The post assembly tests, as well as the dynamic testing of the mechanism, are presented.

Source record↗
NASA NTRS1989

State-of-the-art surveys on computational mechanics

Topics considered include advances in finite difference techniques for computational fluid dynamics, the spectral element methods for the incompressible Navier-Stokes equations, a review of recent developments in time integration, and advances and trends in element-by-element techniques. Also examined are the algebraic multigrid methods applied to problems in computational structural mechanics, grid generation for the solution of partial differential equations, advances in adaptive improvements, and new computing systems and their impact on computational mechanics.

Noor, Ahmed K.↗
NASA NTRS1991

Semiannual report, 1 April - 30 September 1991

The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software for parallel computers. Research in these areas is discussed.

Source record↗
NASA NTRS1991

An overview of computer viruses in a research environment

The threat of attack by computer viruses is in reality a very small part of a much more general threat, specifically threats aimed at subverting computer security. Here, computer viruses are examined as a malicious logic in a research and development environment. A relation is drawn between the viruses and various models of security and integrity. Current research techniques aimed at controlling the threats posed to computer systems by threatening viruses in particular and malicious logic in general are examined. Finally, a brief examination of the vulnerabilities of research and development systems that malicious logic and computer viruses may exploit is undertaken.

Bishop, Matt↗
NASA NTRS1996

Technology Directions for the 21st Century

The Office of Space Communications (OSC) is tasked by NASA to conduct a planning process to meet NASA's science mission and other communications and data processing requirements. A set of technology trend studies was undertaken by Science Applications International Corporation (SAIC) for OSC to identify quantitative data that can be used to predict performance of electronic equipment in the future to assist in the planning process. Only commercially available, off-the-shelf technology was included. For each technology area considered, the current state of the technology is discussed, future applications that could benefit from use of the technology are identified, and likely future developments of the technology are described. The impact of each technology area on NASA operations is presented together with a discussion of the feasibility and risk associated with its development. An approximate timeline is given for the next 15 to 25 years to indicate the anticipated evolution of capabilities within each of the technology areas considered. This volume contains four chapters: one each on technology trends for database systems, computer software, neural and fuzzy systems, and artificial intelligence. The principal study results are summarized at the beginning of each chapter.

Crimi, Giles F.↗
NASA NTRS2009

Robust Software Architecture for Robots

Robust Real-Time Reconfigurable Robotics Software Architecture (R4SA) is the name of both a software architecture and software that embodies the architecture. The architecture was conceived in the spirit of current practice in designing modular, hard, realtime aerospace systems. The architecture facilitates the integration of new sensory, motor, and control software modules into the software of a given robotic system. R4SA was developed for initial application aboard exploratory mobile robots on Mars, but is adaptable to terrestrial robotic systems, real-time embedded computing systems in general, and robotic toys.

Aghazanian, Hrand↗
NASA NTRS1978

ODIN system technology module library, 1972 - 1973

ODIN/RLV is a digital computing system for the synthesis and optimization of reusable launch vehicle preliminary designs. The system consists of a library of technology modules in the form of independent computer programs and an executive program, ODINEX, which operates on the technology modules. The technology module library contains programs for estimating all major military flight vehicle system characteristics, for example, geometry, aerodynamics, economics, propulsion, inertia and volumetric properties, trajectories and missions, steady state aeroelasticity and flutter, and stability and control. A general system optimization module, a computer graphics module, and a program precompiler are available as user aids in the ODIN/RLV program technology module library.

Hague, D. S.↗
DOE OSTI2025

Learning quantum computers' errors using interpretable neural networks

Learning and reducing the errors and noise in quantum computing systems is necessary for achieving quantum computation’s promise. However, rapid advances in experimental quantum computing are making this task increasingly difficult, because state-of-the-art systems now contain hundreds of qubits and many characterization techniques are hard to apply at this scale. Furthermore, complex kinds of errors in these systems, such as crosstalk and non-Markovian effects, must be understood and decreased, but these errors are challenging to study with most existing methods. In this project, we explored using neural networks for scalable characterization of complex errors in quantum computers. We proposed and demonstrated characterizing a quantum computer’s errors with neural networks that have interpretable parameters corresponding to the rates of different kinds of errors, within a sparse Lindbladian parameterization for errors. To enable scaling to many qubit systems, these networks then predict how these errors combine within quantum circuits and impact their outcomes using an efficient approximations. We demonstrated these networks ability to learn coherent crosstalk errors and context-dependent errors in a simulated 4-qubit system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Multi-node and Multi-core Performance Studies of a Monte Carlo code RMC

Over the past 15 years the architecture of high-performance computing systems has become increasingly heterogeneous with individual computing cores being subdivided into nodes and even auxiliary co-processing units such as graphics processing units or the Intel many integrated core co-processors. In fact, future computer platforms is moving toward a larger number of nodes and cores with lower memory available per node. Today, several production Monte Carlo codes use some types of hybrid parallelism strategy that makes use of shared-memory parallelism within a computing node and message-passing parallelism between nodes, which enables the codes to utilize available computing resources as much as possible, both among and within computing nodes on a cluster. The so-called hybrid parallelization is also possible with Reactor Monte Carlo Code RMC by activating both MPI and OpenMP parallel algorithms together. On HPC' which typically consists of several or several-ten thousand nodes equipping 16-32 computing intra-cores per node, simulation of RMC can be carried out in the hybrid parallelization with the MPI inter-node parallelization and the OpenMP intra-node parallelization. RMC has adopted a hybrid message-passing and shared-memory approach to parallelism, which enables the code to utilize available computing resources, both among and within computing nodes on a cluster. Shared-memory parallelism is especially valuable for large-model simulations because it enables multiple compute cores within a node to share common model information such as the geometry description, material, cross section and tally data, thus reducing the memory usage per processor. The calculation on the Tianhe-2 supercomputer took 6144 cores, resulting in a rate of 173,314,000 neutrons/minute for BEAVRS benchmark. While pin-wise full core H-M benchmark burnup calculations with millions of depletion regions was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 1,843,200 burnable regions per minute. Keeping up with the continuing trend for increases in the number of computing resources within modern HPC systems is a significant challenge for teams that develop and maintain high-performance MC radiation transport solvers. order to address this challenge, RMC has adopted a hybrid message-passing and shared-memory approach to parallelism, which enables the code to utilize available computing resources, both among and within computing nodes on a cluster. Shared-memory parallelism is especially valuable for large-model simulations because it enables multiple compute cores within a node to share common model information such as the geometry description, material and composition definitions, and cross section data, thus reducing the memory usage per processor. The parallel performance has been studied by using two complex and representative benchmarks, H-M and BEAVRS benchmark. All simulations were run on Intel Xeon E5-2692 12 core, 2.2 GHz processors at MilkyWay-2 Super Computer with up to 12,288 available computing cores. While employing MPI parallelism, excellent parallel efficiency is achieved even above 12,000 processors and RMC reaches the parallel efficiency of 96% on 12,288 cores for the pin-by-pin computation of the BEAVRS benchmark. While BEAVRS criticality benchmark was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 173,314,000 particles per minute. While pin-wise full core H-M benchmark burnup calculations with millions of depletion regions was selected using MPI/OpenMP parallelism, the speed of 6,144 cores reach 1,843,200 burnable regions per minute. Results from these studies demonstrate that RMC, using the hybrid parallel model described in this paper, is able to handle pin-wise full core burnup calculations with millions of depletion regions and scales well through thousands of processors. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1978

Computing technology in the 1980's

Advances in computing technology have been led by consistently improving semiconductor technology. The semiconductor industry has turned out ever faster, smaller, and less expensive devices since transistorized computers were first introduced 20 years ago. For the next decade, there appear to be new advances possible, with the rate of introduction of improved devices at least equal to the historic trends. The implication of these projections is that computers will enter new markets and will truly be pervasive in business, home, and factory as their cost diminishes and their computational power expands to new levels. The computer industry as we know it today will be greatly altered in the next decade, primarily because the raw computer system will give way to computer-based turn-key information and control systems.

Stone, H. S.↗
NASA NTRS1984

Ultrareliable fault-tolerant control systems

It is demonstrated that fault-tolerant computer systems, such as on the Shuttles, based on redundant, independent operation are a viable alternative in fault tolerant system designs. The ultrareliable fault-tolerant control system (UFTCS) was developed and tested in laboratory simulations of an UH-1H helicopter. UFTCS includes asymptotically stable independent control elements in a parallel, cross-linked system environment. Static redundancy provides the fault tolerance. A polling is performed among the computers, with results allowing for time-delay channel variations with tight bounds. When compared with the laboratory and actual flight data for the helicopter, the probability of a fault was, for the first 10 hr of flight given a quintuple computer redundancy, found to be 1 in 290 billion. Two weeks of untended Space Station operations would experience a fault probability of 1 in 24 million. Techniques for avoiding channel divergence problems are identified.

Webster, L. D.↗
NASA NTRS1991

Computer-aided design of flight control systems

A computer program is presented for facilitating the development and assessment of flight control systems, and application to a control design is discussed. The program is a computer-aided control-system design program based on direct digital synthesis of a proportional-integral-filter controller with scheduled linear-quadratic-Gaussian gains and command generator tracking of pilot inputs. The FlightCAD system concentrates on aircraft dynamics, flight-control systems, stability and performance, and has practical engineering applications.

Stengel, Robert F.↗
DOE OSTI2017

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Implicit Thermochemical Nonequilibrium Flow Simulations on Unstructured Grids using GPUs

Thermochemical nonequilibrium flow simulation capabilities have been previously implemented, verified, and validated for central processing unit (CPU) systems in NASA’s unstructured-grid computational fluid dynamics solver FUN3D. Many exascale-class high-performance computing systems will rely on graphics processing unit (GPU) architectures for high throughput and energy efficiency; thus, CPU-based scientific computing software unable to effectively utilize these systems must be updated. In this work, we present a CUDA C++ implementation of FUN3D’s thermochemical nonequilibrium flow simulation capabilities targeting NVIDIA Tesla GPUs. An overview of the porting and optimization strategy is described and performance comparisons with other recent architectures are presented. Scaling to thousands of GPUs is demonstrated, yielding computational performance equivalent to that of several million CPU cores. The implementation enables efficient, high-fidelity, scale-resolving simulations of thermochemical nonequilibrium flows for many applications including atmospheric entry, hypersonics, and combustion.

GPU↗
NASA NTRS1991

Y-MP floating point and Cholesky factorization

The floating point arithmetics implemented in the Cray 2 and Cray Y-MP computer systems are nearly identical, but large scale computations performed on the two systems have exhibited significant differences in accuracy. The difference in accuracy is analyzed for Cholesky factorization algorithm, and it is found that the source of the difference is the subtract magnitude operation of the Cray Y-MP. The results from numerical experiments for a range of problem sizes are presented, and an efficient method for improving the accuracy of the factorization obtained on the Y-MP is presented.

Carter, Russell↗