Dynamic associativity management using utility based way-sharing

Shirshendu Das, H. Kapoor
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引用次数: 3

Abstract

The non-uniform distribution of memory accesses of todays applications affect the performance of cache memories. Due to such non-uniform accesses some sets of large sized caches are used heavily while some other sets are used lightly. This paper presents a technique WS-DAM, to dynamically increase the associativity of the heavily used sets without increasing the cache size. The heavily used sets can use the idle ways of the lightly used sets to distribute the load. A limited number of ways from every lightly used set are reserved for the heavily used sets. To search a block in a heavily used set, both: the set and the entire reserve area is searched. To reduce the cost of searching the entire reserve storage an additional tag-array is used. During execution the sets are re-categorized at intervals. The proposed technique needs much lesser storage, area and power overhead as compared to the other similar techniques. It improves both miss rate and CPI by 14.46% and 6.63% respectively as compared to an existing technique called V-Way. WS-DAM is also compared with another existing proposal called CMP-VR and it improves the performance by 9% and 4.20% in terms of miss-rate and CPI respectively.
使用基于实用程序的路径共享的动态关联管理
当前应用程序内存访问的不均匀分布影响了缓存内存的性能。由于这种不均匀的访问,一些大型缓存集被大量使用,而另一些集则被少量使用。本文提出了一种WS-DAM技术,在不增加缓存大小的情况下,动态地增加频繁使用的数据集的关联性。重负荷机组可以采用轻负荷机组的闲置方式来分配负荷。从每个很少使用的集合中保留有限数量的方法用于频繁使用的集合。要搜索大量使用的集合中的一个块,需要同时搜索集合和整个保留区域。为了减少搜索整个储备存储器的成本,使用了一个额外的标签数组。在执行过程中,每隔一段时间对集合进行重新分类。与其他类似技术相比,所提出的技术需要更小的存储空间、面积和功率开销。与现有的V-Way技术相比,它将漏靶率和CPI分别提高了14.46%和6.63%。WS-DAM还与另一种称为CMP-VR的现有方案进行了比较,它在失误率和CPI方面分别提高了9%和4.20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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