Six Pass MapReduce Implementation of Strassen's Algorithm for Matrix Multiplication

Prakash V. Ramanan
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引用次数: 4

Abstract

Consider the multiplication of two n x n matrices. A straight-forward sequential algorithm for computing the product takes Θ(n3) time. Strassen [21] presented an algorithm that takes Θ(nlg 7) time; lg denotes logarithm to the base 2; lg 7 is about 2.81. Now, consider the implementation of these two algorithms (straightforward and Strassen) in the mapReduce framework. Several papers have studied mapReduce implementations of the straight-forward algorithm; this algorithm can be implemented using a constant number (typically, one or two) of mapReduce passes. In this paper, we study the mapReduce implementation of Strassen's algorithm. If we unwind the recursion, Strassen's algorithm consists of three parts, Parts I--III. Direct mapReduce implementations of the three parts take lg n, 1 and lg n passes, respectively; total number of passes is 2 lg n + 1. In a previous paper [7], we showed that Part I can be implemented in 2 passes, with total work Θ(nlg 7), and reducer size and reducer workload o(n). In this paper, we show that Part III can be implemented in three passes. So, overall, Strassen's algorithm can be implemented in six passes, with total work Θ(nlg 7), and reducer size and reducer workload o(n).
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矩阵乘法Strassen算法的六步MapReduce实现
考虑两个n × n矩阵的乘法。计算乘积的直接顺序算法需要Θ(n3)时间。Strassen[21]提出的算法耗时Θ(nlg7);Lg表示以2为底的对数;Lg 7的价格约为2.81。现在,考虑在mapReduce框架中实现这两种算法(straight和Strassen)。有几篇论文研究了mapReduce的直接算法实现;这个算法可以使用一个常量(通常是一个或两个)的mapReduce传递来实现。本文主要研究Strassen算法的mapReduce实现。如果我们展开递归,Strassen的算法由三部分组成,第一部分-第三部分。这三个部分的mapReduce直接实现分别需要lgn、1和lgn次传递;总次数是2lgn + 1。在之前的论文[7]中,我们展示了第一部分可以分2次实现,总工作量Θ(nlg 7),减速器尺寸和减速器工作量o(n)。在本文中,我们证明了第三部分可以通过三个步骤实现。因此,总的来说,Strassen算法可以在六次中实现,总工作量为Θ(nlg 7), reducer大小和reducer工作负载为o(n)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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