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基于GPU的几何多重网络的避免通信优化

Communication-Avoiding Optimization of Geometric Multigrid on GPUs

作者:Amik Singh; James Demmel, Ed. 作者单位:EECS Department, University of California, Berkeley 加工时间:2013-12-18 信息来源:EECS 索取原文[11 页]
关键词:GPU;避免通信优化;多重网格;算法
摘 要:Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear systems in a number of different application areas. In this report, we explore communication-avoiding implementations of Geometric Multigrid on Nvidia GPUs. We achieved an overall gain of 1.2x for the whole multigrid algorithm over baseline implementation. We also provide an insight into what future GPUs need to have in terms of on chip and shared memory for these kinds of algorithms to perform even better.
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