Parallel preconditioned conjugate gradient algorithm on GPU

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• 作者：Rudi Helfenstein ; Jonas Koko ; ^{koko@sp.isima.fr}
• 关键词：Preconditioned conjugate gradient ; Parallel computing ; Graphics processor unit
• 刊名：Journal of Computational and Applied Mathematics
• 出版年：2012
• 期刊代码：72_03770427
• 类别：cp
• 出版时间：September, 2012
• 卷：236
• 期：15
• 页码：3584-3590
• 文件大小：224 K

摘要

We propose a parallel implementation of the Preconditioned Conjugate Gradient algorithm on a GPU platform. The preconditioning matrix is an approximate inverse derived from the SSOR preconditioner. Used through sparse matrix-vector multiplication, the proposed preconditioner is well suited for the massively parallel GPU architecture. As compared to CPU implementation of the conjugate gradient algorithm, our GPU preconditioned conjugate gradient implementation is up to 10 times faster (8 times faster at worst).