Fast matrix multiplication via recursive $\langle$ 4x4x4:48 $\rangle$ algorithms into practice

📅 2026-09-10
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该论文提出了一种使用48次乘法和216次其他运算的快速4x4矩阵乘法算法,并通过递归应用及基变换优化,降低了计算复杂度。
📝 Abstract
We present a fast algorithm for multiplying two 4x4 matrices using 48 multiplications and 216 other operations (addition, subtraction or scaling by a constant) over any ring containing an inverse of 2. Applied recursively, this algorithm reaches a cost bound with leading term $7.75 n^{\log_4(48)}$. This is, up to our knowledge, the best-known leading constant in the cost for matrix multiplication algorithms with exponent $log_4(48)$. We further present an alternative basis version of this algorithm, reducing the leading term to $6.5 n^{\log_4(48)}$ by minimizing the extra cost after the change of basis.
Problem

Research questions and friction points this paper is trying to address.

fast matrix multiplication
recursive algorithm
operation count
Innovation

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fast matrix multiplication
recursive algorithm
alternative basis
leading constant improvement
Jean-Guillaume Dumas
Jean-Guillaume Dumas
Pr. Applied Mathematics, Université Grenoble Alpes, Laboratoire Jean Kuntzmann
Computer AlgebraSymbolic computationCryptologySecurityParallelism
Clément Pernet
Clément Pernet
Grenoble INP - UGA, LJK
computer algebracoding theorycryptographylinear algebrafault tolerance
A
Alexandre Sedoglavic
Université de Lille, Centrale Lille, umr cnrs 9189 CRISTAL, Lille, France
P
Petr Tichavský
Academy of Sciences of the Czech Republic, Inst. of Information Theory and Automation, Praha, Czech Republic