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  • Computer Programming and Software  (12)
  • Computer Operations and Hardware  (5)
  • 2000-2004  (17)
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  • 1
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    High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations (2003)
    In:  CASI
    Details
    Publication Date: 2018-06-06
    Description: Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.
    Keywords: Computer Operations and Hardware
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  • 2
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    Unstructured Adaptive Meshes: Bad for Your Memory? (2003)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This viewgraph presentation explores the need for a NASA Advanced Supercomputing (NAS) parallel benchmark for problems with irregular dynamical memory access. This benchmark is important and necessary because: 1) Problems with localized error source benefit from adaptive nonuniform meshes; 2) Certain machines perform poorly on such problems; 3) Parallel implementation may provide further performance improvement but is difficult. Some examples of problems which use irregular dynamical memory access include: 1) Heat transfer problem; 2) Heat source term; 3) Spectral element method; 4) Base functions; 5) Elemental discrete equations; 6) Global discrete equations. Nonconforming Mesh and Mortar Element Method are covered in greater detail in this presentation.
    Keywords: Computer Operations and Hardware
    Type: ADAPT03: Conference on Adaptive Methods for PDEs and Large-Scale Computation; Oct 11, 2003 - Oct 12, 2003; Troy, NY; United States
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  • 3
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    Parallel Conjugate Gradient: Effects of Ordering Strategies, Programming Paradigms, and Architectural Platforms (2000)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV) usually accounts for most of the floating-point operations within a CG iteration. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and SPMV using different programming paradigms and architectures. Results show that for this class of applications, ordering significantly improves overall performance, that cache reuse may be more important than reducing communication, and that it is possible to achieve message passing performance using shared memory constructs through careful data ordering and distribution. However, a multi-threaded implementation of CG on the Tera MTA does not require special ordering or partitioning to obtain high efficiency and scalability.
    Keywords: Computer Programming and Software
    Type: Parallel and Distributed Computing Systems; Aug 08, 2000 - Aug 10, 2000; Las Vegas, NV; United States
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  • 4
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    Parallel Computing Strategies for Irregular Algorithms (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-10
    Description: Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.
    Keywords: Computer Programming and Software
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  • 5
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    Effects of Ordering Strategies and Programming Paradigms on Sparse Matrix Computations (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-10
    Description: The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. For systems that are ill-conditioned, it is often necessary to use a preconditioning technique. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and ILU(O) preconditioned CG (PCG) using different programming paradigms and architectures. Results show that for this class of applications: ordering significantly improves overall performance on both distributed and distributed shared-memory systems, that cache reuse may be more important than reducing communication, that it is possible to achieve message-passing performance using shared-memory constructs through careful data ordering and distribution, and that a hybrid MPI+OpenMP paradigm increases programming complexity with little performance gains. A implementation of CG on the Cray MTA does not require special ordering or partitioning to obtain high efficiency and scalability, giving it a distinct advantage for adaptive applications; however, it shows limited scalability for PCG due to a lack of thread level parallelism.
    Keywords: Computer Programming and Software
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  • 6
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    Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations (2003)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: 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.
    Keywords: Computer Programming and Software
    Type: Supercomputing 2003; Nov 15, 2003 - Nov 21, 2003; Phoenix, AZ; United States
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  • 7
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    Tools and Techniques for Measuring and Improving Grid Performance (2001)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This viewgraph presentation provides information on NASA's geographically dispersed computing resources, and the various methods by which the disparate technologies are integrated within a nationwide computational grid. Many large-scale science and engineering projects are accomplished through the interaction of people, heterogeneous computing resources, information systems and instruments at different locations. The overall goal is to facilitate the routine interactions of these resources to reduce the time spent in design cycles, particularly for NASA's mission critical projects. The IPG (Information Power Grid) seeks to implement NASA's diverse computing resources in a fashion similar to the way in which electric power is made available.
    Keywords: Computer Programming and Software
    Type: APART Workshop; Nov 16, 2001; Denver, CO; United States
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  • 8
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    Memory-Intensive Benchmarks: IRAM vs. Cache-Based Machines (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The increasing gap between processor and memory performance has lead to new architectural models for memory-intensive applications. In this paper, we explore the performance of a set of memory-intensive benchmarks and use them to compare the performance of conventional cache-based microprocessors to a mixed logic and DRAM processor called VIRAM. The benchmarks are based on problem statements, rather than specific implementations, and in each case we explore the fundamental hardware requirements of the problem, as well as alternative algorithms and data structures that can help expose fine-grained parallelism or simplify memory access patterns. The benchmarks are characterized by their memory access patterns, their basic control structures, and the ratio of computation to memory operation.
    Keywords: Computer Operations and Hardware
    Type: IPDPS Conference; Apr 15, 2002 - Apr 19, 2002; Fort Lauderdale, FL; United States
    Format: text
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  • 9
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    Load Balancing Strategies for Multi-Block Overset Grid Applications (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The multi-block overset grid method is a powerful technique for high-fidelity computational fluid dynamics (CFD) simulations about complex aerospace configurations. The solution process uses a grid system that discretizes the problem domain by using separately generated but overlapping structured grids that periodically update and exchange boundary information through interpolation. For efficient high performance computations of large-scale realistic applications using this methodology, the individual grids must be properly partitioned among the parallel processors. Overall performance, therefore, largely depends on the quality of load balancing. In this paper, we present three different load balancing strategies far overset grids and analyze their effects on the parallel efficiency of a Navier-Stokes CFD application running on an SGI Origin2000 machine.
    Keywords: Computer Programming and Software
    Type: ISCA 18th International Conference on Computers and Their Applications; Mar 26, 2003 - Mar 28, 2003; Honolulu, HI; United States
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  • 10
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    A De-Centralized Scheduling and Load Balancing Algorithm for Heterogeneous Grid Environments (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: In the past two decades, numerous scheduling and load balancing techniques have been proposed for locally distributed multiprocessor systems. However, they all suffer from significant deficiencies when extended to a Grid environment: some use a centralized approach that renders the algorithm unscalable, while others assume the overhead involved in searching for appropriate resources to be negligible. Furthermore, classical scheduling algorithms do not consider a Grid node to be N-resource rich and merely work towards maximizing the utilization of one of the resources. In this paper we propose a new scheduling and load balancing algorithm for a generalized Grid model of N-resource nodes that not only takes into account the node and network heterogeneity, but also considers the overhead involved in coordinating among the nodes. Our algorithm is de-centralized, scalable, and overlaps the node coordination time of the actual processing of ready jobs, thus saving valuable clock cycles needed for making decisions. The proposed algorithm is studied by conducting simulations using the Message Passing Interface (MPI) paradigm.
    Keywords: Computer Programming and Software
    Type: Workshop on Scheduling and Resource Management for Cluster Computing; Aug 18, 2002 - Aug 21, 2002; Vancouver; Canada
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