FPM Based Partitioning and Assignment Algorithm for Data Parallel Applications on Heterogeneous Platforms

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2022-7-01

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Alasmar, Mahmoud

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Advances in modern computing devices and applications created the challenge of efficient utilization of resources in satisfying the requirements of running applica- tions. The present work aims to find an efficient workload distribution algorithm for data parallel applications of type single program multiple data (SPMD) running on a heterogeneous computing platform. We first consider a discrete functional perfor- mance model (FPM) that integrates processing speed and capacity of processing ele- ments with the size of the computational task. We then develop a mathematical model and propose an appropriate heuristic mapping algorithm for distributing a given total workload of size N on p processing elements such that the total computation time is minimized and resources are utilized efficiently. Results of our evaluation study show that the proposed method can speed up parallel applications significantly in compari- son to classical approaches. The proposed method is able to generate better solutions than classical methods in a reasonable amount of time by using a limited amount of prior information.

Subject Keywords

Heterogeneous Platforms, High Performance Computing, Workload Distribution, Task assignment, Functional Performance Model, Parallel Computing, Single Program Multiple Data

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https://hdl.handle.net/11511/98200

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. Alasmar, “FPM Based Partitioning and Assignment Algorithm for Data Parallel Applications on Heterogeneous Platforms,” M.S. - Master of Science, Middle East Technical University, 2022.