超级计算中的并行矩阵乘法算法

Xia Liao, Shengguo Li, Wei Yu, Yutong Lu
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引用次数: 1

摘要

目前,高性能计算正逐步实现超大规模计算,单节点性能已达到数T-flops。通信问题已成为并行矩阵乘法算法的主要问题之一。本文综述了国内外在超级计算机上对PMM算法的研究进展。我们首先强调了PMM(并行矩阵乘法)算法在高性能科学计算中的重要性,然后介绍了广泛使用的PMM算法的背景。本文从经典并行矩阵乘法和Strassen快速矩阵乘法两方面介绍了PMM算法的并行技术研究。此外,我们对每种算法进行了详细的复杂度分析比较。最后,对全文进行了总结,并对今后的工作方向进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel matrix multiplication algorithms in Supercomputing
Nowadays high-performance computing is gradually implementing Exa-scale computing, and the performance of single node has reached several T-flops. Communication problem has become one of the main concerns of parallel matrix multiplication algorithms. This paper surveys the research on PMM algorithms on supercomputers around the world. We first stress the significance of PMM (Parallel Matrix multiplication) algorithms in high performance scientific computing, followed by a background introduction on widely employed PMM algorithms. We introduce the researches on parallel techniques for PMM algorithms from two aspects: classical parallel matrix multiplication and Strassen’s fast matrix multiplication. Further, we present the detailed complexity analysis comparison of each algorithm. Finally, we summarize the paper and discuss potential directions of future work.
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