| Opportunistic evolution: efficient evolutionary computation on large-scale computational grids |
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Genetic And Evolutionary Computation Conference
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Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation
table of contents
Atlanta, GA, USA
SESSION: Late-breaking papers
table of contents
Pages 2227-2232
Year of Publication: 2008
ISBN:978-1-60558-131-6
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Authors
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Keith Sullivan
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George Mason University, Fairfax, VA, USA
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Sean Luke
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George Mason University, Fairfax, VA, USA
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Curt Larock
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Parabon Computing Inc., Reston, VA, USA
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Sean Cier
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Parabon Computing Inc., Reston, VA, USA
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Steven Armentrout
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Parabon Computing Inc., Reston, VA, USA
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ABSTRACT
We examine opportunistic evolution, a variation of master-slave distributed evaluation designed for deployment of evolutionary computation to very large grid computing architectures with limited communications, severe evaluation overhead, and wide variance in evaluation node speed. In opportunistic evolution, slaves receive some N individuals at a time, evaluate them, and then run those individuals through their own mini evolutionary loop until some fixed wall clock time has been exceeded. Our implementation of opportunistic evolution may be used in conjunction with either a generational or, for maximum throughput, an asynchronous steady-state evolutionary model in the master. Opportunistic evolution is strongly exploitative. We perform initial experiments comparing the technique with a traditional master/slave model, and suggest possible classes of problems for which it might be apropos.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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