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The Fat-Link Computation on Large GPU Clusters for Lattice QCD

机译:适用于莱迪思QCD的大型GPU群集上的胖链接计算

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Graphics Processing Units (GPU) are becoming increasingly popular in high performance computing due to their high performance, high power efficiency and low cost. In this paper, we present results of an effort to implement the fatlink computation -- an important component of many lattice quantum chromo dynamics (LQCD) calculations -- on GPU clusters using the QUDA framework. Two implementations, one similar to the original CPU algorithm in the MILC code and one based on the idea of reduced communication by redundant computations, are presented and their relative advantages are discussed. In strong-scaling tests on up to 384GPUs on Longhorn and 256 GPUs on Keene land GPU clusters, where the CPU core to GPU ratio is 4:1 in both clusters, we achieved up to 11.4x and 8.7x node speedup when running on the two GPU clusters, respectively.
机译:图形处理单元(GPU)由于其高性能,高能效和低成本而在高性能计算中变得越来越流行。在本文中,我们介绍了使用QUDA框架在GPU群集上实施Fatlink计算(许多晶格量子色动力学(LQCD)计算的重要组成部分)的努力结果。提出了两种实现方式,一种类似于MILC代码中的原始CPU算法,一种基于通过冗余计算减少通信的思想,并讨论了它们的相对优势。在Longhorn上最多384个GPU和Keene陆地GPU群集上的256个GPU的强扩展测试中,两个群集中的CPU核心与GPU的比率均为4:1,在运行于两个GPU群集。

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