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Revisiting hash join on graphics processors: a decade later

机译:重新审视哈希加入图形处理器:十年后

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Over the last decade, significant research effort has been put into improving the performance of hash join operation on GPUs. Over the same period, there have been significant changes to the GPU architecture. Hence in this paper, we first revisit the major GPU hash join implementations in the last decade and detail how they take advantage of different GPU architecture features. We then perform a comprehensive performance evaluation of these implementations using different generations of GPUs released over the last decade, which helps to shed light on the impact of different architecture features and to identify the factors guiding the choice of these features. We then study how data characteristics like skew and match rate impact the performance of GPU hash join implementations and propose techniques to improve the performance of existing implementations under such conditions. Finally, we perform an in-depth comparison of the performance and cost-efficiency of GPU hash join implementations against state-of-the-art CPU implementation.
机译:在过去的十年中,重大的研究努力得到了改善GPUS的哈希连接操作的表现。在同一时期,GPU架构对GPU架构进行了重大变化。因此,在本文中,我们首先在过去十年中重新审视了主要的GPU哈希联合实施,详细介绍了它们如何利用不同的GPU架构功能。然后,我们使用过去十年中发布的不同几代GPU来对这些实现进行全面的绩效评估,这有助于揭示不同架构特征的影响,并确定指导这些功能选择的因素。然后,我们研究数据特征如何像偏差和匹配率影响GPU散列连接实现的性能,并提出技术在这种情况下提高现有实现的性能。最后,我们对GPU哈希连接实现的性能和成本效率进行了深入的比较,防止最先进的CPU实现。

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