超立方体上的矢量解剖

T-H. Olesen, J. Petersen
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引用次数: 4

摘要

在具有矢量硬件的超立方体并行处理器上,采用高斯消元法对二维椭圆型偏微分方程的有限差分离散和有限元离散所产生的矩阵进行了分解排序求解。这些问题可以写成矩阵-向量的形式,Ax = f,其中矩阵a代替微分算子,x是解向量,f是源向量。域在节点之间进行划分,相邻的子域共享一条称为分隔符的条带。每个处理器都有它自己的源向量部分,并计算它自己的刚度矩阵a。只有当边缘需要消除时,大部分消除完成后才需要通信。首先在域边缘上进行反向替换,然后在每个节点上完全并行地进行替换,而不进行通信。Hypercube代码经过优化,可以与矢量硬件一起工作。给出了实例问题和时序,并与非矢量运行进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vectorized dissection on the hypercube
Dissection ordering is used with Gaussian elimination on a Hypercube parallel processor with vector hardware to solve matrices arising from finite-difference and finite-element discretizations of 2-D elliptic partial differential equations. These problems can be put into a matrix-vector form, Ax = f, where the matrix A takes the place of the differential operator, x is the solution vector, and f is the source vector. The domain is divided among the nodes with neighboring subdomains sharing a strip called a separator. Each processor is given its own part of the source vector and computes its own part of the stiffness matrix, A. The elimination starts out in parallel; communication is only needed after most of the elimination is finished when the edges need to be eliminated. Back substitution is initially done on the domain edges, and then totally in parallel without communication on each node. The Hypercube code involved was optimized to work with vector hardware. Example problems and timings are given with comparisons to nonvector runs.
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