A thread-adaptive sparse approximate inverse preconditioning algorithm on multi-GPUs

被引:14
作者
Gao, Jiaquan [1 ]
Chen, Qi [1 ]
He, Guixia [2 ]
机构
[1] Nanjing Normal Univ, Sch Comp & Elect Informat, Jiangsu Key Lab NSLSCS, Nanjing 210023, Peoples R China
[2] Zhejiang Univ Technol, Zhijiang Coll, Hangzhou 310024, Peoples R China
关键词
Sparse approximate inverse; Preconditioning; CUDA; GPU; GMRES;
D O I
10.1016/j.parco.2020.102724
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this study, we present an efficient thread-adaptive sparse approximate inverse preconditioning algorithm on multiple GPUs, called GSPAI-Adaptive. For our proposed GSPAI-Adaptive, there are the following novelties: (1) a thread-adaptive allocation strategy is presented for each column of the preconditioner, and (2) a parallel framework of constructing the sparse approximate inverse preconditioner is proposed on multiple GPUs, and (3) each component of the preconditioner is computed in parallel inside a thread group of GPU. Experimental results show that GSPAI-Adaptive is effective, and is advantageous over the popular preconditioning algorithms in two public libraries, and a latest parallel sparse approximate inverse preconditioning algorithm.
引用
收藏
页数:13
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