基于GPU的稀疏近似逆预处理算法优化

BenchCouncil Transactions on Benchmarks, Standards and Evaluations Pub Date : 2022-10-01 DOI:10.1016/j.tbench.2023.100087

Xinyue Chu, Yizhou Wang, Qi Chen, Jiaquan Gao

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引用次数: 1

摘要

在本研究中，我们提出了一种GPU上的优化稀疏近似逆(SPAI)预处理算法，称为GSPAI-Opt。GSPAI-Opt,融合两种流行的优势SPAI预处理算法,和下面的小礼品:(1)提出了一种优化策略选择是否使用常数或不恒定线程组的稀疏模式预处理器,和(2)一个并行的框架上,提出了优化SPAI预处理GPU,和(3)对于每个组件的预处理,建立决策树来选择最优计算内核。实验结果验证了GSPAI-Opt算法的有效性。

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Optimizing the sparse approximate inverse preconditioning algorithm on GPU

In this study, we present an optimization sparse approximate inverse (SPAI) preconditioning algorithm on GPU, called GSPAI-Opt. In GSPAI-Opt, it fuses the advantages of two popular SPAI preconditioning algorithms, and has the following novelties: (1) an optimization strategy is proposed to choose whether to use the constant or non-constant thread group for any sparse pattern of the preprocessor, and (2) a parallel framework of optimizing the SPAI preconditioner is proposed on GPU, and (3) for each component of the preconditioner, a decision tree is established to choose the optimal kernel of computing it. Experimental results validate the effectiveness of GSPAI-Opt.

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来源期刊

BenchCouncil Transactions on Benchmarks, Standards and Evaluations

CiteScore

4.80

自引率

0.00%

发文量