大规模并行稀疏LU分解

[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation Pub Date : 1992-10-19 DOI:10.1109/FMPC.1992.234896

S. Kratzer

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引用次数: 6

摘要

稀疏LU分解的多正面算法已被表示为一种适用于大规模并行计算机的数据并行程序。采用了一种将数据和计算映射到处理器的新方法，即使对于非结构化稀疏矩阵，也能获得良好的处理器利用率。稀疏问题被分解成许多更小、更密集的子问题，通信和内存访问的开销很低。给出了在MasPar MP-1.>上对规则和不规则有限元网格矩阵进行分解的性能结果

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Massively parallel sparse LU factorization

The multifrontal algorithm for sparse LU factorization has been expressed as a data parallel program that is suitable for massively parallel computers. A new way of mapping data and computations to processors is used, and good processor utilization is obtained even for unstructured sparse matrices. The sparse problem is decomposed into many smaller, dense subproblems, with low overhead for communications and memory access. Performance results are provided for factorization of regular and irregular finite-element grid matrices on the MasPar MP-1.<>

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[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation

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