Basic Matrix Subprograms for Distributed Memory Systems

A. Elster
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引用次数: 11

Abstract

Parallel systems are in general complicated to utilize eficiently. As they evolve in complexity, it hence becomes increasingly more important to provide libraries and language features that can spare the users from the knowledge of low-level system details. Our effort in this direction is to develop a set of basic matrix algorithms for distributed memory systems such as the hypercube. The goal is to be able to provide for distributed memory systems an environment similar to that which the Level-3 Basic Linear Algebra Subprograms (BLAS3) provide for the sequential and shared memory environments. These subprograms facilitate the development of eficient and portable algorithms that are rich in matrix-matrix multiplication, on which major software eflorts such as LAPACK have been built. To demonstrate the concept, some of these Level-3 algorithms are being developed on the Intel iPSC/2 hypercube. Central to this effort is the General Matrix-Matrix Multiplication routine PGEMM. The symmetric and triangular multiplications as well as, rank-tk updates (symmetric case), and the solution of triangular systems with multiple right hand sides, are also discussed.
分布式存储系统的基本矩阵子程序
一般来说,并行系统很难有效地利用。随着复杂性的发展,提供库和语言特性变得越来越重要,这些库和语言特性可以使用户免于了解底层系统细节。我们在这个方向上的努力是为分布式内存系统(如hypercube)开发一套基本矩阵算法。我们的目标是能够为分布式内存系统提供类似于3级基本线性代数子程序(BLAS3)为顺序和共享内存环境提供的环境。这些子程序促进了高效和可移植算法的开发,这些算法具有丰富的矩阵-矩阵乘法,在这些算法的基础上已经建立了诸如LAPACK之类的主要软件。为了演示这个概念,其中一些Level-3算法正在英特尔iPSC/2超立方体上开发。这项工作的核心是通用矩阵-矩阵乘法例程PGEMM。讨论了对称和三角乘法、秩-tk更新(对称情况)以及具有多个右边边的三角系统的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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