Performance Analysis of Parallel Supernodal Sparse LU Factorization.

Grigori, L. ; Li, X. S.

Technical Information Center Oak Ridge Tennessee

关键词: Parallel processing;    Factorization;    Implementation;    Matrices;    Performance;   

RP-ID  :  DE2004822182

学科分类：工程和技术（综合）

美国|英语

来源: National Technical Reports Library

【 摘 要 】

We investigate performance characteristics for the LU factorization of large matrices with various sparsity patterns. We consider supernodal right-looking parallel factorization on a bi-dimensional grid of processors, making use of static pivoting. We develop a performance model and we validate it using the implementation in SuperLU-DIST, the real matrices and the IBM Power3 machine at NERSC. We use this model to obtain performance bounds on parallel computers, to perform scalability analysis and to identify performance bottlenecks. We also discuss the role of load balance and data distribution in this approach.