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Experimental Study of Six Different Implementations of Parallel Matrix Multiplication on Heterogeneous Computational Clusters of Multicore Processors

机译:对不同矩阵乘法的六种不同实现对多核处理器异构计算集群的六种不同实现的实验研究

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Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore Processors (HCoMs). These strategies are called Heterogeneous Process Distribution Strategy (HPS) and Heterogeneous Data Distribution Strategy (HDS). They are not novel and have been researched thoroughly. However, the advent of multicores necessitates enhancements to them. In this paper, we present these enhancements. Our study is based on experiments using six applications to perform Parallel Matrix-matrix Multiplication (PMM) on an HCoM employing the two distribution strategies.
机译:计算的两种分配策略可用于实施用于多核处理器(HCOMS)的异构计算集群的致密线性代数问题的平行溶解。 这些策略称为异质过程分配策略(HPS)和异质数据分布策略(HDS)。 它们不是新颖的,已经彻底研究。 但是,多元大石的出现需要对他们的增强。 在本文中,我们提出了这些增强功能。 我们的研究基于使用六个应用程序在采用两个分布策略的HCOM上执行并行矩阵矩阵乘法(PMM)的实验。

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