Accelerating iterative linear solvers using multiple graphical processing units |
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| Authors: | Zhangxin Chen Bo Yang |
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| Affiliation: | 1. Department of Chemical and Petroleum Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada;2. Center for Computational Geoscience, College of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China |
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| Abstract: | In this paper, we develop, study and implement iterative linear solvers and preconditioners using multiple graphical processing units (GPUs). Techniques for accelerating sparse matrix–vector (SpMV) multiplication, linear solvers and preconditioners are presented. Four Krylov subspace solvers, a Neumann polynomial preconditioner and a domain decomposition preconditioner are implemented. Our numerical tests with NVIDIA C2050 GPUs show that the SpMV kernel can be sped over 40 times faster using four GPUs. Our linear solvers and preconditioners have similar speedup. |
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| Keywords: | multi-GPUs SpMV linear solver domain decomposition preconditioner preconditioner parallel computing |
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