Abstract
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.
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© 1996 Springer-Verlag Berlin Heidelberg
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Daalder, J., Eklund, P.W., Ohmori, K. (1996). High-level synthesis optimisation with genetic algorithms. In: Foo, N., Goebel, R. (eds) PRICAI'96: Topics in Artificial Intelligence. PRICAI 1996. Lecture Notes in Computer Science, vol 1114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61532-6_24
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DOI: https://doi.org/10.1007/3-540-61532-6_24
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