利用新的图形处理器架构重新评估利用可编程图形处理器加速标准粒子群优化算法的可行性和有效性.针对新的图形处理器架构进行系统分析,在此架构下实现了标准粒子群优化算法的并行版本.实验结果表明,通过合理运用新的图形处理器架构,与其他标准粒子群优化算法的并行版本相比,取得了良好的加速比.
We used a new architecture of graphic processing unit(Fermi GPU) to re-evaluate the feasibility and effectiveness of using programmable GPU to accelerate the standard particle swarm optimization(SPSO) algorithm and made a systematical analysis on the rules of harnessing the power of Fermi GPU,and implemented the parallel version of SPSO on such an architecture.In the experiment,we achieved a good speedup via the best use of the new architecture of graphic processing unit,compared to using the other parallel version of the algorithm.