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High-level synthesis optimisation with genetic algorithms
conference contribution
posted on 1996-01-01, 00:00 authored by J Daalder, Peter EklundPeter Eklund, K Ohmori© Springer-Verlag Berlin Heidelberg 1996. The results of a genetic algorithm optimisation of the scheduling and allocation phases of high-level synthesis are reported. Scheduling and allocation are NP complete, multi-objective phases of high-level synthesis. A high-level synthesis system must combine the two problems to produce optimal results. The genetic algorithm described provides a robust and efficient method of search capable of combining scheduling and allocation phases, and responding to the multiple and changing objectives of high-level synthesis. The results show the genetic algorithm succeeds in finding optimal or near optimal results to classic benchmarks in small computational time spans.
History
Event
Pacific Rim International Conference on Artificial Intelligence (1996 : Cairns, Queensland)Volume
1114Series
Lecture notes in comptuer sciencePagination
276 - 287Publisher
SpringerLocation
Cairns, QueenslandPlace of publication
Berlin, GermanyPublisher DOI
Start date
1996-08-26End date
1996-08-30ISSN
0302-9743eISSN
1611-3349ISBN-13
9783540615323ISBN-10
3540615326Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
Norman Foo, Randy GoebelTitle of proceedings
PRICAI 1996 : Topics in artificial inteligence : Proceedings of the 4th Pacific Rim Internationaal 1996 ConferenceUsage metrics
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