Accurate modeling of parallel scientific computations
- 1 April 1989
- proceedings article
- Published by Association for Computing Machinery (ACM)
- Vol. 17 (1) , 165-170
- https://doi.org/10.1145/75108.75390
Abstract
Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load-time. Critical mapping and remapping decisions rest on our ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models we construct are shown empirically to be accurate, and are used to find optimal remapping schedules.Keywords
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