Hyper‐heuristic method for processor allocation in parallel tasks scheduling

Scheduling the tasks of parallel scientific applications is very important for efficient utilization of resources and reducing the overall execution time (makespan). Parallel applications typically include both data parallelism and task parallelism. It is known that the scheduling problem on multipr...

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Bibliographic Details
Published in:Concurrency and computation 2023-11, Vol.35 (24)
Main Authors: Yıldız, Gülçin, Sevilgen, Fatih Erdoğan
Format: Article
Language:English
Subjects:
Genetic algorithms
Greedy algorithms
Heuristic methods
Microprocessors
Multiprocessing
Parallel processing
Resource utilization
Task scheduling
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Summary:Scheduling the tasks of parallel scientific applications is very important for efficient utilization of resources and reducing the overall execution time (makespan). Parallel applications typically include both data parallelism and task parallelism. It is known that the scheduling problem on multiprocessor systems problem is NP‐Hard even for applications involving pure task parallelism. The problem becomes more difficult when data parallelism is also taken into consideration. These problems usually considered in two steps, processor allocation and task scheduling, and various algorithms have been proposed. In this study, we introduce a genetic algorithm based hyper‐heuristic approach for the processor allocation problem. Experimental results indicate that the algorithm provides better performance compared to various greedy algorithms.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.7757