A GPU Based Approach for Solving the Workflow Scheduling Problem

Mohammed Benhammouda and Mimoun Malki
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Mohammed Benhammouda: EEDIS Laboratory, Djillali Liabes University at Sidi Bel Abbes, Sidi Bel Abbès, Algeria
Mimoun Malki: LabRI-SBA Laboratory, Ecole Supérieure en Informatique de Sidi Bel Abbes, Sidi Bel Abbès, Algeria

International Journal of Information Retrieval Research (IJIRR), 2019, vol. 9, issue 4, 1-12

Abstract: Cloud computing is considered a new way to use on-demand computing resources. When executing a workflow process in such an environment, task scheduling, a well-known NP-hard problem is a very important step. Many heuristic algorithms have been proposed to solve this problem. In this article, the authors present a GPU-based approach for solving the workflow scheduling problem. The main idea of the approach is to implement a massively parallel version of the simulated annealing algorithm, in an asynchronous way where no information is exchanged among parallel runs. The proposed approach, called PSA algorithm, is against another well-established scheduling HEFT heuristic. Experiments with randomly generated graphs show a much better performance from the proposed approach.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:9:y:2019:i:4:p:1-12

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