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Title
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Virtual Savant for the heterogeneous computing scheduling problem
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Author
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Abstract
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| A key issue when using distributed computing environments is finding a planning strategy to execute tasks in order to use the computational resources efficiently. This article presents the application of Virtual Savant to solve the heterogeneous computing scheduling problem, a widely-studied problem with several real-world applications. Virtual Savant is a novel method that uses machine learning techniques to automatically generate programs that can be executed in parallel to solve a given problem. Experimental analysis is performed on a set of problem instances generated following methodologies from the related literature. Results show that Virtual Savant is able to outperform MinMin, a well-known heuristic for the studied problem, by up to 15% while showing good scalability properties when increasing the number of computing resources and the dimension of the problem instances. |
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Language
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English
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Source (book)
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2018 International Conference on High Performance Computing & Simulation (HPCS), 16-20 July, 2018, Orleans, France
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Publication
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New york
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2018
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ISBN
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978-1-5386-7878-7
978-1-5386-7879-4
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DOI
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10.1109/HPCS.2018.00133
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Volume/pages
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(2018)
, p. 821-827
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ISI
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000450677700114
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Full text (Publisher's DOI)
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