By Topic

Load balancing strategies for dense linear algebra kernels on heterogeneous two-dimensional grids

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)
Beaumont, O. ; Ecole Normale Superieure de Lyon, France ; Boudet, V. ; Rastello, F. ; Robert, Y.

We study the implementation of dense linear algebra computations, such as matrix multiplication and linear system solvers, on two-dimensional (2D) grids of heterogeneous processors. For these operations, 2D-grids are the key to scalability and efficiency. The uniform block-cyclic data distribution scheme commonly used for homogeneous collections of processors limits the performance-of-these operations on heterogeneous grids to the speed of the slowest processor. We present and study more sophisticated data allocation strategies that balance the load on heterogeneous 2D-grids with respect to the performance of the processors. The usefulness of these strategies is demonstrated by simulation measurements for a heterogeneous network of workstations

Published in:

Parallel and Distributed Processing Symposium, 2000. IPDPS 2000. Proceedings. 14th International

Date of Conference: