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

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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:

2000