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Highly Parallel Sparse Matrix-Matrix Multiplication

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arxiv 1006.2183 v1 pith:TMVFVVTV submitted 2010-06-11 cs.DC cs.MScs.NAcs.PFmath.NA

Highly Parallel Sparse Matrix-Matrix Multiplication

classification cs.DC cs.MScs.NAcs.PFmath.NA
keywords algorithmssparsematrix-matrixmultiplicationparallelprocessorsachieveblock
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Generalized sparse matrix-matrix multiplication is a key primitive for many high performance graph algorithms as well as some linear solvers such as multigrid. We present the first parallel algorithms that achieve increasing speedups for an unbounded number of processors. Our algorithms are based on two-dimensional block distribution of sparse matrices where serial sections use a novel hypersparse kernel for scalability. We give a state-of-the-art MPI implementation of one of our algorithms. Our experiments show scaling up to thousands of processors on a variety of test scenarios.

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Cited by 1 Pith paper

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    Introduces a 2D cyclic decomposition triangle counting algorithm for distributed-memory systems achieving 3.24-7.22x relative speedup on 169 MPI ranks and 10.2x over prior distributed algorithms.