Abstract
Writing recursive programs for fine-grained task-level execution on parallel architectures, such as the current generation of multi-core machines, often require the application of skilled parallelization knowledge to fully realize the potential of the hardware. This paper automates the process by using Grammatical Evolution (GE) to exploit the multi-cores through the evolution of natively parallel programs. We present Multi-core Grammatical Evolution (MCGE-II), which employs GE and OpenMP specific pragmatic information to automatically evolve task-level parallel recursive programs. MCGE-II is evaluated on six recursive C programs, and we show that it solves each of them using parallel code. We further show that MCGE-II significantly decreases the parallel computational effort as the number of cores increase, when tested on an Intel processor.
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Notes
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For example, the Intel Polaris has 80 cores, while the picoChip PC200 has 200+.
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Chennupati, G., Azad, R.M.A., Ryan, C. (2015). Automatic Evolution of Parallel Recursive Programs. In: Machado, P., et al. Genetic Programming. EuroGP 2015. Lecture Notes in Computer Science(), vol 9025. Springer, Cham. https://doi.org/10.1007/978-3-319-16501-1_14
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