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Estimating Parallel Performance, a Skeleton-based Approach by Oleg Lobachev; Rita Loogen is a scholarly article available to read on EtoBox.

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In this paper we estimate parallel execution times, based on identifying separate "parts" of the work done by parallel programs. We assume that programs are described using algorithmic skeletons. Therefore our runtime analysis works without any source code inspection. The time of parallel program execution is expressed in terms of the sequential work and the parallel penalty. We measure these values for different problem sizes and numbers of processors and estimate them for unknown values in both dimensions. This allows us to predict parallel execution time for unknown inputs and non-available processor numbers.Another useful application of our formalism is a measure of parallel program quality. We analyse the values for parallel penalty both for growing input size and for increasing numbers of processing elements. From these data, conclusions on parallel performance and scalability are drawn.

Author

Oleg Lobachev; Rita Loogen

Publisher

ACM

Published

2010

Language

EN