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Efficient Assembly of Sparse Matrices Using Hashing

机译:使用散列有效地组装稀疏矩阵

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In certain applications the non-zero elements of large sparse matrices are formed by adding several smaller contributions in random order before the final values of the elements are known. For some sparse matrix representations this procedure is laborious. We present an efficient method for assembling large irregular sparse matrices where the nonzero elements have to be assembled by adding together contributions and updating the individual elements in random order. A sparse matrix is stored in a hash table, which allows an efficient method to search for an element. Measurements show that for a sparse matrix with random elements the hash-based representation performs almost 7 times faster than the compressed row format (CRS) used in the PETSc library. Once the sparse matrix has been assembled we transfer the matrix to e.g. CRS for matrix manipulations.
机译:在某些应用中,大型稀疏矩阵的非零元素是通过在已知元素的最终值之前按随机顺序添加几个较小的贡献而形成的。对于某些稀疏矩阵表示,此过程很麻烦。我们提出了一种用于组装大型不规则稀疏矩阵的有效方法,其中必须通过将贡献相加并以随机顺序更新各个元素来组装非零元素。稀疏矩阵存储在哈希表中,这允许一种有效的方法来搜索元素。测量表明,对于具有随机元素的稀疏矩阵,基于哈希的表示比PETSc库中使用的压缩行格式(CRS)快将近7倍。稀疏矩阵组装完成后,我们会将矩阵转移到例如CRS用于矩阵处理。

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