High-level synthesis optimisation with genetic algorithms

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.