By Topic

A general scalable implementation of fast matrix multiplication algorithms on distributed memory computers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Nguyen, D.K. ; Lab. de Recherche en Informatique Avancee, Paris Univ., France ; Lavallee, I. ; Bui, M. ; Quoc Trung Ha

Fast matrix multiplication (FMM) algorithms to multiply two n × n matrices reduce the asymptotic operation count from O(n3) of the traditional algorithm to O(n2.38), thus on distributed memory computers, the association of FMM algorithms and the parallel matrix multiplication algorithms always gives remarkable results. Within this association, the application of FMM algorithms at inter-processor level requires us to solve more difficult problems in designing but it forms the most effective algorithms. In this paper, a general model of these algorithms is presented and we also introduce a scalable method to implement this model on distributed memory computers.

Published in:

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005. Sixth International Conference on

Date of Conference:

23-25 May 2005