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# [ISCA'20] Buddy Compression | ||
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**Title:** Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs | ||
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**Keywords:** | ||
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**Major Contribution:** | ||
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## 本文简介 | ||
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GPU加速了高吞吐量的应用程序,这需要比传统的仅CPU系统更高数量级的内存带宽。然而,这种高带宽存储器的容量往往相对较小。伙伴压缩是一种架构,它利用了主机更大的伙伴内存或分解内存,有效地增加了GPU的内存容量。伙伴压缩将每个压缩的128B内存条目分为高带宽GPU内存和较慢但较大的伙伴内存之间,这样可压缩内存条目完全从GPU内存访问,而不可压缩条目从非GPU内存中获取部分数据。使用“伙伴压缩”,可压缩性的变化不会导致昂贵的页面移动或重新分配。对于代表性的HPC应用,伙伴压缩平均实现1.9×的有效GPU内存扩展,对于深度学习训练,平均实现1.5×,执行在没有内存限制的不现实的系统的2%以内。这使得Buddy压缩对需要额外GPU内存容量的性能意识开发人员具有吸引力 | ||
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