Parallel algorithm for evolvable-based boolean synthesis on GPUs
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The use of evolutionary algorithms in the boolean synthesis is an attractive alternative to generate interesting and efficient hardware structures, with a high computational load. This paper presents the implementation of a parallel genetic programming (PGP) for boolean synthesis on a GPU-CPU based platform. Our implementation uses the island model, that allows the parallel and independent evolution of the PGP through the multiple processing units of the GPU and the multiple cores of a new generation desktop processors. We tested multiple mapping alternatives of the PGP on the platform in order to optimize the PGP response time. As a result we show that our approach achieves a speedup up to 41 compared to CPU implementation.
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