Partitioning Rectangular and Structurally Unsymmetric Sparse Matrices for Parallel Processing
نویسندگان
چکیده
A common operation in scientific computing is the multiplication of a sparse, rectangular, or structurally unsymmetric matrix and a vector. In many applications the matrix-transposevector product is also required. This paper addresses the efficient parallelization of these operations. We show that the problem can be expressed in terms of partitioning bipartite graphs. We then introduce several algorithms for this partitioning problem and compare their performance on a set of test matrices.
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عنوان ژورنال:
- SIAM J. Scientific Computing
دوره 21 شماره
صفحات -
تاریخ انتشار 2000