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Dynamic Resizing on Active Warps Scheduler to Hide Operation Stalls on GPUs

机译:在Active Warps Scheduler上动态调整大小以隐藏GPU上的操作停顿

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摘要

This paper conducts a detailed study of the factors affecting the operation stalls in terms of the fetch group size on the warp scheduler of GPUs. Throughout this paper, we reveal that the size of a fetch group is highly involved for hiding various types of operation stalls: short latency stalls, long latency stalls, and Load/Store Unit (LSU) stalls. The scheduler with a small fetch group cannot hide short latency stalls due to the limited number of warps in a fetch group. In contrast, the scheduler with a large fetch group cannot hide long latency and LSU stalls due to the limited number of fetch groups and the lack of memory subsystems, respectively. To hide various types of stalls, this paper proposes a Dynamic Resizing on Active Warps (DRAW) scheduler which adjusts the size of a fetch group dynamically based on the execution phases of applications. For the applications that have the best performance at LRR (one fetch group), the DRAW scheduler matches the performance of LRR and outperforms TL (multiple fetch groups) by 22.7 percent. In addition, for the applications that have the best performance at TL, our scheduler achieves 11.0 and 5.5 percent better performance compared to LRR and TL, respectively.
机译:本文根据GPU翘曲调度程序上的访存组大小,对影响操作停顿的因素进行了详细研究。在整个本文中,我们揭示了获取组的大小与隐藏各种类型的操作停顿密切相关:短等待时间停顿,长等待时间停顿和加载/存储单元(LSU)停顿。由于访存组中的扭曲数量有限,因此访存组较小的调度程序无法隐藏短时延停顿。相反,由于获取组数量有限且分别缺少内存子系统,具有较大获取组的调度程序无法隐藏长等待时间和LSU停顿。为了隐藏各种类型的停顿,本文提出了一种基于动态扭曲的动态调整大小(DRAW)调度程序,该调度程序根据应用程序的执行阶段动态调整获取组的大小。对于在LRR(一个读取组)上具有最佳性能的应用程序,DRAW调度程序与LRR的性能相匹配,并且比TL(多个读取组)的性能高出22.7%。此外,对于在TL上具有最佳性能的应用程序,与LRR和TL相比,我们的调度程序的性能分别提高了11.0%和5.5%。

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