Locality-aware parallel block-sparse matrix-matrix multiplication using the Chunks and Tasks programming model
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- 作者：Emanuel H. Rubensson emanuel.rubensson@it.uu.se" class="auth_mail" title="E-mail the corresponding author ; Elias Rudberg ; elias.rudberg@it.uu.se" class="auth_mail" title="E-mail the corresponding author
- 关键词：Parallel computing ; Sparse matrix-matrix multiplication ; Scalable algorithms ; Large-scale computing ; Graphics processing units
- 刊名：Parallel Computing
- 出版年：2016
- 出版时间：September 2016
- 年：2016
- 卷：57
- 期：Complete
- 页码：87-106
- 全文大小：1326 K
文摘
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We present a method for parallel block-sparse matrix-matrix multiplication.
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A distributed quadtree matrix representation allows exploitation of data locality.
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The quadtree structure is implemented using the Chunks and Tasks programming model.
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Data locality is exploited without prior information about matrix sparsity pattern.
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Constant communication per node on average is achieved in weak scaling tests.