Abstract
This paper presents how we have achieved the parallelization of Aevol, a biological evolution simulator, on multi-core architecture using the OpenMP standard. While it looks like a simple for-loop problem with independent iterations, the stochastic nature of Aevol makes the duration of the iterations unpredictable and it conveys a high irregularity. Classical scheduling algorithms of OpenMP runtimes turn out to be inefficient. By analysing the origin of this irregularity, this paper present how to transform the highly irregular Aevol for-loop to a sequence composed by a small duration irregular for-loop followed by work intensive for-loop easy to schedule using classical LPT algorithm. This method leads to a gain up to 27% from the best OpenMP loop schedule.
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Notes
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Iterations only perform computation.
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Acknowledgement
Experiments presented in this paper were carried out using the Grid’5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000.fr).
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Turpin, L., Gautier, T., Rouzaud-Cornabas, J., Perez, C. (2020). P-Aevol: An OpenMP Parallelization of a Biological Evolution Simulator, Through Decomposition in Multiple Loops. In: Milfeld, K., de Supinski, B., Koesterke, L., Klinkenberg, J. (eds) OpenMP: Portable Multi-Level Parallelism on Modern Systems. IWOMP 2020. Lecture Notes in Computer Science(), vol 12295. Springer, Cham. https://doi.org/10.1007/978-3-030-58144-2_4
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