多核矢量处理器的倾斜多银行缓存

Hikaru Takayashiki, Masayuki Sato, K. Komatsu, Hiroaki Kobayashi
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摘要

随着核心数量和内存带宽的平衡增长,现代矢量处理器实现了高持续性能,特别是在科学和工程领域的内存密集型应用中。然而,由于集成在单个芯片上的输入/输出引脚数量的限制,很难显著增加片外存储器带宽。在这种情况下,现代矢量处理器采用共享缓存来实现高的持续内存带宽。共享缓存通过保留多个矢量核所需的可重用数据,有效地减少了对片外内存带宽的压力。然而,随着共享缓存的矢量内核数量的增加,同时从多个内核请求的更多不同块使用同一集合。因此,由这些块引起的冲突丢失会降低性能。为了避免在核数增加的情况下增加冲突缺失,本文提出了一种多核矢量处理器的倾斜缓存。倾斜缓存防止同时请求的块被存储到同一个集合中。本文讨论了如何在现代矢量处理器中实现倾斜缓存的两个最重要的特性:哈希函数和替换策略。该缓存采用奇乘位移哈希法进行有效倾斜,采用静态重引用间隔预测策略进行合理替换。评估结果表明,该缓存通过消除冲突缺失,显著提高了多核矢量处理器的性能。
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A Skewed Multi-banked Cache for Many-core Vector Processors
As the number of cores and the memory bandwidth have increased in a balanced fashion, modern vector processors achieve high sustained performances, especially in memory-intensive applications in the fields of science and engineering. However, it is difficult to significantly increase the off-chip memory bandwidth owing to the limitation of the number of input/output pins integrated on a single chip. Under the circumstances, modern vector processors have adopted a shared cache to realize a high sustained memory bandwidth. The shared cache can effectively reduce the pressure to the off-chip memory bandwidth by keeping reusable data that multiple vector cores require. However, as the number of vector cores sharing a cache increases, more different blocks requested from multiple cores simultaneously use the same set. As a result, conflict misses caused by these blocks degrade the performance. In order to avoid increasing the conflict misses in the case of the increasing number of cores, this paper proposes a skewed cache for many-core vector processors. The skewed cache prevents the simultaneously requested blocks from being stored into the same set. This paper discusses how the most important two features of the skewed cache should be implemented in modern vector processors: hashing function and replacement policy. The proposed cache adopts the oddmultiplier displacement hashing for effective skewing and the static re-reference interval prediction policy for reasonable replacing. The evaluation results show that the proposed cache significantly improves the performance of a many-core vector processor by eliminating conflict misses.
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