矩阵-向量乘法并行算法的综合与推广

Q4 Engineering
Yukio Miyasaka, Akihiro Goda, A. Mittal, M. Fujita
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引用次数: 2

摘要

近年来,由于神经网络的应用越来越广泛,计算矩阵向量乘法的机会越来越多。提出了一种自动合成给定环境下最优并行算法的方法,并合成了一种特定大小的单向环连接4个节点的矩阵-向量乘法算法。本文提出了一种将综合算法推广到任意大小矩阵的方法。将32 × 32矩阵的综合算法推广到计算N × N矩阵-向量乘法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesis and Generalization of Parallel Algorithm for Matrix-vector Multiplication
Recently, there have been more chances to calculate matrix-vector multiplication due to the growing use of the neural network. We have proposed the method to automatically synthesize the optimum parallel algorithm for the given environment and synthesized an algorithm for matrix-vector multiplication of a specific size matrix with 4 nodes connected in a oneway ring. This paper proposes a method to generalize the synthesized algorithm to deal with any size matrix. We generalized the synthesized algorithm for the 32 × 32 matrix to calculate N × N matrix-vector multiplication.
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来源期刊
IPSJ Transactions on System LSI Design Methodology
IPSJ Transactions on System LSI Design Methodology Engineering-Electrical and Electronic Engineering
CiteScore
1.20
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0.00%
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