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Twinned buffering: A simple and highly effective scheme for parallelization of Successive Over-Relaxation on GPUs and other accelerators

机译:Twinned Butfering:一种简单而高效的方案,用于在GPU和其他加速器上连续放松的并行化

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In this paper we present a new scheme for parallelization of the Successive Over-Relaxation method for solving the Poisson equation over a 3-D volume. Our new scheme is both simple and effective, outperforming the conventional Red-Black scheme by a factor of 16 on an NVIDIA GeForce GTX 590 GPU, a factor of 11 on an NVIDIA GeForce TITAN Black GPU and a factor of 5 on an Intel Xeon Phi. The speed-up compared to the fully optimised reference implementation running on an Intel Xeon CPU is 16 times on the GTX 590, 22 times on the TITAN and 5 times on the Xeon Phi. We explain the rationale and the implementation in OpenCL and present the performance evaluation results.
机译:在本文中,我们提出了一种新的方案,用于通过三维体积求解泊松方程的连续过度放松方法的并行化。我们的新方案既简单又有效,优于常规的红黑色方案,在NVIDIA GeForce GTX 590 GPU上以16倍,在NVIDIA GeForce Titan Black GPU上的一个倍数为11个倍数和英特尔Xeon Phi 。与英特尔Xeon CPU上的完全优化的参考实现相比,GTX 590上运行的完全优化的参考实现相比,泰坦的22次和Xeon Phi上的5次。我们解释了OpenCL中的理由和实施,并提出了绩效评估结果。

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