arXiv (Cornell University) · 2015 · 25 citations · 14 references
Open access
ComputingComputer ScienceMathematicsAlgorithmsParallel ComputingTheory Of ComputationAlgorithm AnalysisAlgorithmic ComplexityComputational ComplexityMatrix ComputationNumerical Linear AlgebraComputational Matrix TheoryIdentityMatrix Multiplication
Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time O(n2.3755). Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le~Gall has led to an improved algorithm running in time O(n2.3729). These algorithms are obtained by analyzing higher and higher tensor powers of a certain identity of Coppersmith and Winograd. We show that this exact approach cannot result in an algorithm with running time O(n2.3725), and identify a wide class of variants of this approach which cannot result in an algorithm with running time $O(n^{2.3078}); in particular, this approach cannot prove the conjecture that for every e > 0, two n x n matrices can be multiplied in time O(n2+e).We describe a new framework extending the original laser method, which is the method underlying the previously mentioned algorithms. Our framework accommodates the algorithms by Coppersmith and Winograd, Stothers, Vassilevska-Williams and Le~Gall. We obtain our main result by analyzing this framework. The framework also explains why taking tensor powers of the Coppersmith--Winograd identity results in faster algorithms.
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Gaussian elimination is not optimal
Volker Strassen · Numerische Mathematik · 1969 · 2.5K citations
Matrix multiplication via arithmetic progressions
Don Coppersmith, S. Winograd · Journal of Symbolic Computation · 1990 · 2.3K citations
Most Tensor Problems Are NP-Hard
Christopher J. Hillar, Lek‐Heng Lim · Journal of the ACM · 2013 · 1.1K citations
Multiplying matrices faster than coppersmith-winograd
Virginia Vassilevska Williams · 2012 · 887 citations
Powers of tensors and fast matrix multiplication
François Le Gall · 2014 · 873 citations