Caching-efficient multithreaded fast multiplication of sparse matrices (1998) [2 citations — 0 self]
Abstract:
Several fast sequential algorithms have been proposed in the past to multiply sparse matrices. These algorithms do not explicitly address the impact of caching on performance. We show that a rather simple sequential cache–efficient algorithm provides significantly better performance than existing algorithms for sparse matrix multiplication. We then describe a multithreaded implementation of this simple algorithm and show that its performance scales well with the number of threads and CPUs. For 10 % sparse, 500 X 500 matrices, the multithreaded version running on 4–CPU systems provides more than a 41.1–fold speed increase over the well–known BLAS routine and a 14.6 fold and 44.6–fold speed increase over two other recent techniques for fast sparse matrix multiplication, both of which are relatively difficult to parallelize efficiently.
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