看一下可扩展的密集线性代数库

J. Dongarra, R. V. D. Geijn, D. Walker
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引用次数: 103

摘要

讨论了在分布式内存并发计算机上执行密集线性代数计算的可扩展软件库的基本设计特征。方形块分散分解是一种灵活且通用的方法,可以分解大多数(如果不是全部的话)密集矩阵问题。库的面向对象接口允许编写更可移植的应用程序,并且易于学习和使用,因为并行实现的细节对用户是隐藏的。给出了在Intel Touchstone Delta系统上使用方形块分散分解进行LU分解的原型代码的实验并进行了分析。结果发现,该代码既可扩展又高效,对于考虑的最大问题,执行速度约为14 GFLOPS(双精度)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A look at scalable dense linear algebra libraries
Discusses the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object-oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization are presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.<>
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