Locality estimation of parallel algorithm for distributed memory computers

N. A. Likhoded, A. Tolstsikau
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Abstract

Locality is an algorithm characteristic describing a usage level of fast access memory. For example, in case of distributed memory computers we focus on memory of each computational node. To achieve the high performance of algorithm implementation one should choose the best possible locality option. Studying the parallel algorithm locality is to estimate the number and volume of data communications. In this work, we formulate and prove the statements for computers with distributed memory that allow us to estimate the asymptotic volume of data communication operations. These estimation results are useful while comparing alternative versions of parallel algorithms during data communication cost analysis.
分布式存储计算机并行算法的局部性估计
局部性是一种描述快速存取存储器使用水平的算法特征。例如,对于分布式内存计算机,我们关注每个计算节点的内存。为了实现算法的高性能,应该选择最好的局部性选项。研究并行算法的局部性是为了估计数据通信的数量和容量。在这项工作中,我们制定并证明了具有分布式内存的计算机的陈述,使我们能够估计数据通信操作的渐近体积。这些估计结果在数据通信成本分析中比较并行算法的替代版本时非常有用。
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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