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Parallel Implementation of Vortex Element Method on CPUs and GPUs

机译:在CPU和GPU上并行实现Vortex元素方法

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The implementations of 2D vortex element method adapted to different types of parallel computers are considered. The developed MPI-implementation provides close to linear acceleration for small number of computational cores and approximately 40-times acceleration for 80-cores cluster when solving model problem. OpenMP-based modification allows to obtain 5% additional acceleration due to shared memory usage. Approximate fast multipole method usage reduces time of computations significantly: 11 times for the testmodel problem in sequential mode and 3.5 times in parallel mode for 16-cores cluster. The most efficient implementation of vortex element method is developed for GPUs using NVidia CUDA technology. Time of the model problem solving using single GeForce GTX 970 or Tesla C2070 accelerator is comparable with time of its solving on cluster when involving 30–40 cores of Intel Xeon E5450 CPUs.
机译:考虑了适用于不同类型的并行计算机的2D涡旋元素方法的实现。解决模型问题时,开发的MPI实现为少量计算核提供接近线性加速,为80核集群提供接近40倍的加速。基于OpenMP的修改允许由于共享内存的使用而获得5%的额外加速。近似快速多极点方法的使用显着减少了计算时间:对于16核群集,连续模式下的testmodel问题为11倍,并行模式下为3.5倍。使用NVidia CUDA技术为GPU开发了最有效的涡流元素方法。当涉及30至40个Intel Xeon E5450 CPU内核时,使用单个GeForce GTX 970或Tesla C2070加速器解决模型问题的时间与其在群集上解决问题的时间相当。

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