High Performance Parallel Implementation of A Novel HSS-structured Sparse Solver Using Randomized Sa

来源 :第八届工业与应用数学国际大会 | 被引量 : 0次 | 上传用户：woaichensi

【摘要】

：

　　We present an efficient code for solving large sparse linear systems using the multifrontal method with hierarchically semi-separable(HSS)matrices.The low r

【作者】

：

GhyselsPieter[1]RouetFrancois-Henry[2]LiXiaoye[2]

【机构】

：

Lawrence Berkeley National Lab

【出处】

：

第八届工业与应用数学国际大会

【发表日期】

：

2015年期

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　　We present an efficient code for solving large sparse linear systems using the multifrontal method with hierarchically semi-separable(HSS)matrices.The low rank compression in HSS limits fill-in and reduces complexity of the solver.The HSS matrices are constructed using randomized sampling and rank-revealing QR.ULV decomposition replaces the traditional dense LU.The factorization acts as solver or preconditioner.Shared and distributed memory parallel results are presented for a range of applications

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High Performance Parallel Implementation of A Novel HSS-structured Sparse Solver Using Randomized Sa

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