چکیده مقاله
Parallel computing techniques provide high performance execution of the large size real world complex problems such as heuristic optimization algorithms e g , PSO PSO, as a population based stochastic search technique for solving optimization problems, has been proven to be effective in a wide range of applications Hence, parallel implementation of this algorithm with numerous parallelization models and strategies for solving complex applications has obtained significant attention by researchers In comparison with the PSO, ALC PSO algorithm avoids the problem of premature convergence and improves convergence speed Similar to most of the evolutionary algorithms, ALC PSO is population based iterative and computationally intensive, because the optimizing process of this algorithm requires a large number of fitness evaluations which can run sequentially on CPU or parallel on GPU or on both of them In this article, we propose parallel implementation of ALC PSO algorithm using OmpSs and CUDA, two powerful parallel programming models, for parallel executing the algorithm on both CPUs and GPUs OmpSs is a task parallel programming model and helps developers accelerate their applications execution, on CPU and GPUs, with a low programming effort The results show the proposed implementation provides higher performance than the serial and the CUDA based parallel implementations of ALC PSO
کلیدواژهها
نویسندگان
Mohammad Alaei
Computer Engineering Department, Faculty of Engineering, Vali e Asr University of Rafsanjan, Rafsanjan, Iran
Fahimeh Yazdanpanah
Computer Engineering Department, Faculty of Engineering, Vali e Asr University of Rafsanjan, Rafsanjan, Iran
شیوه ارجاع
Alaei, Mohammad and Yazdanpanah, Fahimeh,1398,A High-Performance Parallel Implementation of ALC-PSO Algorithm using OmpSs and CUDA,3rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی محاسبات نرم29 آبان 1398 · رودسر