Amtran - do-it-yourself computing.
Performance capability of new self-programming system, Amtran, for use with IBM 1620
DECODER↗
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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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Generic Divide and Conquer Internet-Based Computing
The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.
Follen, Gregory J.↗
The Efficiency of Various Computers and Optimizations in Performing Finite Element Computations
With the advent of computers with many processors, it becomes unclear how to best exploit this advantage. For example, matrices can be inverted by applying several processors to each vector operation, or one processor can be applied to each matrix. The former approach has diminishing returns beyond a handful of processors, but how many processors depends on the computer architecture. Applying one processor to each matrix is feasible with enough ram memory and scratch disk space, but the speed at which this is done is found to vary by a factor of three depending on how it is done. The cost of the computer must also be taken into account. A computer with many processors and fast interprocessor communication is much more expensive than the same computer and processors with slow interprocessor communication. Consequently, for problems that require several matrices to be inverted, the best speed per dollar for computers is found to be several small workstations that are networked together, such as in a Beowulf cluster. Since these machines typically have two processors per node, each matrix is most efficiently inverted with no more than two processors assigned to it.
Marcus, Martin H.↗
Challenges of Future High-End Computing
The next major milestone in high performance computing is a sustained rate of one Pflop/s (also written one petaflops, or 10(circumflex)15 floating-point operations per second). In addition to prodigiously high computational performance, such systems must of necessity feature very large main memories, as well as comparably high I/O bandwidth and huge mass storage facilities. The current consensus of scientists who have studied these issues is that "affordable" petaflops systems may be feasible by the year 2010, assuming that certain key technologies continue to progress at current rates. One important question is whether applications can be structured to perform efficiently on such systems, which are expected to incorporate many thousands of processors and deeply hierarchical memory systems. To answer these questions, advanced performance modeling techniques, including simulation of future architectures and applications, may be required. It may also be necessary to formulate "latency tolerant algorithms" and other completely new algorithmic approaches for certain applications. This talk will give an overview of these challenges.
Bailey, David↗
Computer-acquired performance data from a chemically vapor-deposited-tungsten, niobium planar diode
Computer analysis of performance of chemically vapor-deposited tungsten, niobium thermionic converter based on temperatures of emitter, collector and cesium reservoir
Smith, A. L.↗
JACC.shared: Leveraging HPC Metaprogramming and Performance Portability for Computations That Use Shared Memory GPUs
In this work, we present JACC.shared, a new feature of Julia for ACCelerators (JACC), which is the performanceportable and metaprogramming model of the just-in-time and LLVM-based Julia language. This new feature allows JACC applications to leverage the high-performance computing (HPC) capabilities of high-bandwidth, on-chip GPU memory. Historically, exploiting high-bandwidth, shared-memory GPUs has not been a priority for high-level programming solutions. JACC.shared covers that gap for the first time, thereby providing a highlevel, portable, and easy-to-use solution for programmers to exploit this memory and supporting all current major accelerator architectures. Well-known HPC and AI workloads, such as multi/hyperspectral imaging and AI convolutions, have been used to evaluate JACC.shared on two exascale GPU architectures hosted by some of the most powerful US Department of Energy supercomputers: Perlmutter (NVIDIA A100) and Frontier (AMD MI250X). The performance evaluation reports speedup of up to 3.5× by adding only one line of code to the base codes, thus providing important accelerators in a simple, portable, and transparent way and elevating the programming productivity and performance-portability capabilities for Julia/JACC HPC, AI, and scientific applications.
Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗
GPS composite clock software performance
Computer software for ensembling all the space vehicle (SV) and ground clocks of the Global Positioning Systems (GPS) was implemented at the Master Control Station (MCS) on 17 June 1990. Improved GPS time stability and steering control are predicted. The perceptions of both Air Force and outside users are assessed. Current performance is compared with theoretical predictions.
Satin, Arthur L.↗
Hardware Evaluation: Abstract Machine Models and Proxy Architectures for Exascale Computing
The strategic and economic impacts of high performance computing (HPC) systems, over the last several decades, have enabled dramatic improvements in manufacturing, design, development, and research, across almost every sector of the U.S. economy, including genetic analysis for agriculture and medicine, oil exploration, electronics, aircraft, and automotive design, and of course national defense technologies. HPC has repeatedly compounded reductions in time-to-solution and time-to-market in each of these areas. In recognition of these strategic and economic impacts, the Department of Energy (DOE) created the Exascale Computing Project (ECP) as a broad-based technology project focusing on simultaneously co-evolving high-performance computing architecture, system software, and application software. While many details of the exascale architectures are undefined, communicating the form and direction of this co-evolution of advances, in each of these three components, across the project, presents a need for a common language through which these advances can be shared. In this document we present a series of abstract representations designed to allow application developers to focus on the aspects of the machine that are important or relevant to performance and code structure. These abstract machine models (AMMs) describe the proposed architectures at the component and system level and are intended as communication aids between application developers and hardware architects during the co-design process. In addition to providing a common language for communication, the constraints of protecting the intellectual property of ECP’s vendor partners requires that the architectural advances be presented in an abstract sense, rather than exposing the specifics of an individual vendor’s designs, while still providing enough detail such that application developers will be able to reason about the performance trade-offs in the design space of their applications.
97 MATHEMATICS AND COMPUTING↗
Exascale applications: skin in the game
As noted in Wikipedia, skin in the game refers to having ‘incurred risk by being involved in achieving a goal’, where ‘ skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion’. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.
97 MATHEMATICS AND COMPUTING↗
A Visual Analytics Paradigm Enabling Trillion-Edge Graph Exploration
We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with ~one trillion edges and ~50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with ~25 billion edges in less than two hours and 2) support database query and visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.
graph visualization↗
The new challenge of computational aeroscience
This paper discusses NASA's Computational Aerosciences (CAS) Project of the High Performance Computing and Communications Program (HPCCP). The project is aimed at developing advanced, multidisciplinary simulation capabilities for aerospace vehicle and propulsion system design. It is also aimed at overcoming computational performance barriers by accelerating the development of parallel computer technology. The goals and approach of the CAS Project are described and the challenges to its implementation are addressed. Specific vehicle class simulations to be demonstrated and the principal mutidisciplinary modeling approaches to be emphasized are described. The computational speed and memory requirements for representative multidisciplinary applications are estimated. Finally, the state of parallel computer technology including programming issues and the results of performance measurements are explored.
Bailey, F. R.↗
Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing
Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.
use cases↗
Spinor $GW$ Bethe-Salpeter calculations in BerkeleyGW: Implementation, symmetries, benchmarking, and performance
Computing the GW quasiparticle band structure and Bethe-Salpeter equation (BSE) absorption spectra for materials with spin-orbit coupling have commonly been done by treating GW corrections and spin-orbit coupling (SOC) as separate perturbations to density-functional theory. However, accurate treatment of materials with strong spin-orbit coupling (such as many topological materials of recent interest, and thermoelectrics) often requires a nonperturbative approach using spinor wave functions in the Kohn-Sham equation and GW/BSE. Such calculations have only recently become available, in particular for the BSE. Here, we have implemented this approach in the plane-wave pseudopotential GW/BSE code BerkeleyGW, which is highly parallelized and widely used in the electronic-structure community. We present reference results for quasiparticle band structures and optical absorption spectra of solids with different strengths of spin-orbit coupling, including Si, Ge, GaAs, GaSb, CdSe, Au, and Bi 2 Se 3 . The calculated quasiparticle band gaps of these systems are found to agree with experiment to within a few tens of meV. SOC splittings are found to be generally in better agreement with experiment, including quasiparticle corrections to band energies. The absorption spectrum of GaAs is not significantly impacted by the inclusion of spin-orbit coupling due to its relatively small value (0.2 eV) in the Λ direction, while the absorption spectrum of GaSb calculated with the spinor GW/BSE captures the large spin-orbit splitting of peaks in the spectrum. For the prototypical topological insulator Bi 2 Se 3 , we find a drastic change in the low-energy band structure compared to that of DFT, with the spinorial treatment of the GW approximation correctly capturing the parabolic nature of the valence and conduction bands after including off-diagonal self-energy matrix elements. We present the detailed methodology, approach to spatial symmetries for spinors, comparison against other codes, and performance compared to spinless GW/BSE calculations and perturbative approaches to SOC. This work aims to spur further development of spinor GW/BSE methodology in excited-state research software and enables a more accurate and detailed exploration of electronic and optical properties of materials containing elements with large atomic numbers.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 within 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.
Computational Science↗
Comparison of computer-acquired performance data from several fixed spaced planar diodes
Computer acquired I-V characteristics of thermionic fixed spaced planar diodes
Lancashire, R. B.↗
Simulation and modeling of the deep space receiver interaction with channel decoding performance
Computer models were developed in an attempt to reproduce the sequential decoder computation curve of Deep Space Network (DSN) ground station receivers, by simulation of the binary data output of the Gaussian channel with the carrier phaselock loop and the subcarrier demodulator assembly. Simulations were run at bit rates equal to the powers of 2 from 8 to 2,048, and agreement with DSN data was generally good above 32 bits per second. Simulation results at data rates of 8, 16, and 32 bits per second did not closely match experimental data. This simulation provides a more accurate prediction of DSN computation lengths than either current mathematical models or simulations without both the subcarrier demodulator and carrier loop.
Jones, H. W., Jr.↗
Development of code evaluation criteria for assessing predictive capability and performance
Computational Fluid Dynamics (CFD), because of its unique ability to predict complex three-dimensional flows, is being applied with increasing frequency in the aerospace industry. Currently, no consistent code validation procedure is applied within the industry. Such a procedure is needed to increase confidence in CFD and reduce risk in the use of these codes as a design and analysis tool. This final contract report defines classifications for three levels of code validation, directly relating the use of CFD codes to the engineering design cycle. Evaluation criteria by which codes are measured and classified are recommended and discussed. Criteria for selecting experimental data against which CFD results can be compared are outlined. A four phase CFD code validation procedure is described in detail. Finally, the code validation procedure is demonstrated through application of the REACT CFD code to a series of cases culminating in a code to data comparison on the Space Shuttle Main Engine High Pressure Fuel Turbopump Impeller.
Lin, Shyi-Jang↗
In Situ Visualization for Computational Science (Dagstuhl Seminar 18271)
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.
97 MATHEMATICS AND COMPUTING↗