Journal of Computational and Applied Mathematics2022,Vol.40617.DOI:10.1016/j.cam.2021.113941

Equivalent polyadic decompositions of matrix multiplication tensors

Berger, Guillaume O. Absil, Pierre-Antoine Jungers, Raphael M. Van Barel, Marc De Lathauwer, Lieven
Journal of Computational and Applied Mathematics2022,Vol.40617.DOI:10.1016/j.cam.2021.113941

Equivalent polyadic decompositions of matrix multiplication tensors

Berger, Guillaume O. 1Absil, Pierre-Antoine 1Jungers, Raphael M. 1Van Barel, Marc 2De Lathauwer, Lieven3
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作者信息

  • 1. UCLouvain
  • 2. Katholieke Univ Leuven
  • 3. KU Leuven Kulak
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Abstract

Invariance transformations of polyadic decompositions of matrix multiplication tensors define an equivalence relation on the set of such decompositions. In this paper, we present an algorithm to efficiently decide whether two polyadic decompositions of a given matrix multiplication tensor are equivalent. With this algorithm, we analyze the equivalence classes of decompositions of several matrix multiplication tensors. This analysis is relevant for the study of fast matrix multiplication as it relates to the question of how many essentially different fast matrix multiplication algorithms there exist. This question has been first studied by de Groote, who showed that for the multiplication of 2 x2 matrices with 7 active multiplications, all algorithms are essentially equivalent to Strassen's algorithm. In contrast, the results of our analysis show that for the multiplication of larger matrices (e.g., 2 x3 by 3 x2 or 3 x3 by 3 x3 matrices), two decompositions are very likely to be essentially different. We further provide a necessary criterion for a polyadic decomposition to be equivalent to a polyadic decomposition with integer entries. Decompositions with specific integer entries, e.g., powers of two, provide fast matrix multiplication algorithms with better efficiency and stability properties. This condition can be tested algorithmically and we present the conclusions obtained for the decompositions of small/medium matrix multiplication tensors. (C)& nbsp;2021 Elsevier B.V. All rights reserved.

Key words

Fast matrix multiplication/Polyadic tensor decompositions/Eigenvalue decomposition/BILINEAR ALGORITHMS/COMPLEXITY

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出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
参考文献量31
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