PARALLEL SPARSE CHOLESKY FACTORIZATION ON A SHARED MEMORY MULTIPROCESSOR

被引：1
|
作者：
ZHANG, G
ELMAN, HC
机构：
[1] UNIV MARYLAND,INST ADV COMP STUDIES,COLL PK,MD 20742
[2] UNIV MARYLAND,DEPT COMP SCI,COLL PK,MD 20742
来源：
PARALLEL COMPUTING | 1992年 / 18卷 / 09期
基金：
美国国家科学基金会;
关键词：
PARALLEL ALGORITHMS; SPARSE CHOLESKY FACTORIZATION; LINEAR ALGEBRA; SHARED MEMORY MULTIPROCESSOR;
D O I：
10.1016/0167-8191(92)90014-X
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Parallel implementations of Cholesky factorization for sparse symmetric positive definite matrices are considered on a shared memory multiprocessor computer. Two column-oriented schemes, known as the column-Cholesky algorithm and the fan-in algorithm, along with enhancements of each, are implemented and discussed. High parallel efficiency of the column-Cholesky algorithm and its enhancement is demonstrated for test problems. A detailed investigation of the performance of the fan-in algorithm and its enhancement, the compute-ahead fan-in algorithm, is made to study the effects of overhead associated with the fan-in based schemes.
引用
收藏
页码：1009 / 1022
页数：14
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