Abstract

Algorithms for matrix multiplication and for Gauss-Jordan and Gaussian elimination on dense matrices on a torus and a boolean cube are presented and analyzed with respect to communication and arithmetic complexity. The number of elements of the matrices is assumed to be larger than the number of nodes in the processing system. The algorithms for matrix multiplication, triangulation, and forward elimination have 100% processor utilization, except for a latency period proportional to the diameter of the system. The constant of proportionality is small. Distributed one-to-all routing algorithms that guarantee completeness and uniqueness, and terminate after k steps for a k-cube are also given.

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 call

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.