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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

1114

Series

Lecture notes in comptuer science

Pagination

276 - 287

Publisher

Springer

Location

Cairns, Queensland

Place of publication

Berlin, Germany

Start date

1996-08-26

End date

1996-08-30

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783540615323

ISBN-10

3540615326

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

Norman Foo, Randy Goebel

Title of proceedings

PRICAI 1996 : Topics in artificial inteligence : Proceedings of the 4th Pacific Rim Internationaal 1996 Conference

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