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arXiv:math/0603207math.NA

Fast matrix multiplication is stable

James Demmel, Ioana Dumitriu, Olga Holtz, Robert Kleinberg

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Abstract

We perform forward error analysis for a large class of recursive matrix multiplication algorithms in the spirit of [D. Bini and G. Lotti, Stability of fast algorithms for matrix multiplication, Numer. Math. 36 (1980), 63--72]. As a consequence of our analysis, we show that the exponent of matrix multiplication (the optimal running time) can be achieved by numerically stable algorithms. We also show that new group-theoretic algorithms proposed in [H. Cohn, and C. Umans, A group-theoretic approach to fast matrix multiplication, FOCS 2003, 438--449] and [H. Cohn, R. Kleinberg, B. Szegedy and C. Umans, Group-theoretic algorithms for matrix multiplication, FOCS 2005, 379--388] are all included in the class of algorithms to which our analysis applies, and are therefore numerically stable. We perform detailed error analysis for three specific fast group-theoretic algorithms.

arXiv comments
19 pages; final version, expanded and updated to reflect referees' remarks; to appear in Numerische Mathematik
Journal reference
Numer. Math. 106 (2007), no. 2, 199-224
DOI
doi:10.1007/s00211-007-0061-6
Subjects
math.NANumerical Analysis cs.CCComputational Complexity cs.DSData Structures and Algorithms math.GRGroup Theory

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    • You seem to be confusing the mathematical definition of matrix multiplication with an explicit algorithm to compute it. The wiki page you linked is almost entirely about the abstract mathematical definition and talks about algorithms only for a single paragraph, which is about…

      eigenketView on HNParent context

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