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W2561442007 abstract "We dispel with street wisdom regarding the practical implementation of Strassen's algorithm for matrix-matrix multiplication (DGEMM). Conventional wisdom: it is only practical for very large matrices. Our implementation is practical for small matrices. Conventional wisdom: the matrices being multiplied should be relatively square. Our implementation is practical for rank-k updates, where k is relatively small (a shape of importance for libraries like LAPACK). Conventional wisdom: it inherently requires substantial workspace. Our implementation requires no workspace beyond buffers already incorporated into conventional high-performance DGEMM implementations. Conventional wisdom: a Strassen DGEMM interface must pass in workspace. Our implementation requires no such workspace and can be plug-compatible with the standard DGEMM interface. Conventional wisdom: it is hard to demonstrate speedup on multi-core architectures. Our implementation demonstrates speedup over conventional DGEMM even on an Intel® Xeon Phi™ coprocessor1 utilizing 240 threads. We show how a distributed memory matrix-matrix multiplication also benefits from these advances." @default.
W2561442007 created "2017-01-06" @default.
W2561442007 creator A5010052270 @default.
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W2561442007 creator A5061722569 @default.
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W2561442007 date "2016-11-13" @default.
W2561442007 modified "2023-09-24" @default.
W2561442007 title "Strassen's algorithm reloaded" @default.
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W2561442007 doi "https://doi.org/10.5555/3014904.3014983" @default.
W2561442007 hasPublicationYear "2016" @default.
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