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An improved generalized conjugate residual squared algorithm suitable for distributed parallel computing

机译:一种适用于分布式并行计算的改进的广义共轭残差平方算法

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In this paper, based on GCRS algorithm in Zhang and Zhao (2010) and the ideas in Gu et al. (2007), we present an improved generalized conjugate residual squared (IGCRS) algorithm that is designed for distributed parallel environments. The new improved algorithm reduces two global synchronization points to one by changing the computation sequence in the GCRS algorithm in such a way that all inner products per iteration are independent so that communication time required for inner products can be overlapped with useful computation. Theoretical analysis and numerical comparison of isoefficiency analysis show that the IGCRS method has better parallelism and scalability than the GCRS method, and the parallel performance can be improved by a factor of about 2. Finally, some numerical experiments clearly show that the IGCRS method can achieve better parallel performance with a higher scalability than the GCRS method and the improvement percentage of communication is up to 52.19% averagely, which meets our theoretical analysis.
机译:本文基于Zhang和Zhao(2010)的GCRS算法以及Gu等人的思想。 (2007年),我们提出了一种改进的广义共轭残差平方(IGCRS)算法,专为分布式并行环境而设计。新的改进算法通过更改GCRS算法中的计算顺序,使每次迭代的所有内积都是独立的,从而使内积所需的通信时间与有用的计算重叠,从而将两个全局同步点减少为一个。理论分析和等效率分析的数值比较表明,IGCRS方法具有比GCRS方法更好的并行性和可扩展性,并且并行性能可以提高大约2倍。最后,一些数值实验清楚地表明,IGCRS方法可以实现比GCRS方法具有更好的并行性能和更高的可扩展性,平均通信改善率高达52.19%,这符合我们的理论分析。

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