Matrix multiplication, a little faster

Elaye Karstadt, Oded Schwartz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations


Strassen's algorithm (1969) was the first sub-cubic matrix multiplication algorithm. Winograd (1971) improved its complexity by a constant factor. Many asymptotic improvements followed. Unfortunately, most of them have done so at the cost of very large, o.en gigantic, hidden constants. Consequently, Strassen-Winograd's O (nlog27) algorithm o.en outperforms other matrix multiplication algorithms for all feasible matrix dimensions. The leading coefficient of Strassen-Winograd's algorithm was believed to be optimal for matrix multiplication algorithms with 2 × 2 base case, due to a lower bound of Probert (1976). Surprisingly, we obtain a faster matrix multiplication algorithm, with the same base case size and asymptotic complexity as Strassen- Winograd's algorithm, but with the coefficient reduced from 6 to 5. To this end, we extend Bodrato's (2010) method for matrix squaring, and transform matrices to an alternative basis. We prove a generalization of Probert's lower bound that holds under change of basis, showing that for matrix multiplication algorithms with a 2×2 base case, the leading coefficient of our algorithm cannot be further reduced, hence optimal. We apply our technique to other Strassenlike algorithms, improving their arithmetic and communication costs by significant constant factors.

Original languageAmerican English
Title of host publicationSPAA 2017 - Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450345934
StatePublished - 24 Jul 2017
Event29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017 - Washington, United States
Duration: 24 Jul 201726 Jul 2017

Publication series

NameAnnual ACM Symposium on Parallelism in Algorithms and Architectures
VolumePart F129316


Conference29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2017 Copyright held by the owner/author(s).


  • Bilinear algorithms
  • Fast matrix multiplication


Dive into the research topics of 'Matrix multiplication, a little faster'. Together they form a unique fingerprint.

Cite this