Abstract
ABSTRACT We present a method for randomizing formulas for bilinear computation of matrix products which does not increase the leading order complexity of the computation. We consider the implications of such randomization when there are two sources of error. The first source is due to the computation formula itself only being approximately correct. Such formulas come up when numerically searching for faster matrix multiplication algorithms. The second source is due to using floating point arithmetic. This kind of error is especially important when computing on low precision hardware like GPUs. Our theoretical results and numerical experiments indicate that our method can improve performance when the two kinds of error are present individually, as well as when they are present at the same time.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Computer Mathematics: Computer Systems Theory
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
