Abstract
Diverse technologies have been used to accelerate the execution of Evolutionary Algorithms. Nowadays, the GPGPU cards have demonstrated a high efficiency in the improvement of the execution times in a wide range of scientific problems, including some excellent examples with diverse categories of Evolutionary Algorithms. Nevertheless, the studies in depth of the efficiency of each one of these technologies, and how they affect to the final performance are still scarce. These studies are relevant in order to reduce the execution time budget, and therefore affront higher dimensional problems. In this work, the improvement of the speed-up face to the percentage of threads used per block in the GPGPU card is analysed. The results conclude that a correct election of the occupancy —number of the threads per block— contributes to win an additional speed-up.
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Cárdenas-Montes, M., Vega-Rodríguez, M.A., Rodríguez-Vázquez, J.J., Gómez-Iglesias, A. (2011). Effect of the Block Occupancy in GPGPU over the Performance of Particle Swarm Algorithm. In: Dobnikar, A., Lotrič, U., Šter, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2011. Lecture Notes in Computer Science, vol 6593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20282-7_32
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DOI: https://doi.org/10.1007/978-3-642-20282-7_32
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