首页> 外文期刊>Journal of circuits, systems and computers >Parloom: A New Low-Power Set-Associative Instruction Cache Architecture Utilizing Enhanced Counting Bloom Filter and Partial Tags
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Parloom: A New Low-Power Set-Associative Instruction Cache Architecture Utilizing Enhanced Counting Bloom Filter and Partial Tags

机译:Parloom:利用增强的计数布隆过滤器和部分标签的新型低功耗集关联指令缓存体系结构

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The cache system dissipates a significant amount of energy compared to the other memory components. This will be intensified if a cache is designed with a set-associative structure to improve the system performance because the parallel accesses to the entries of a set for tag comparisons lead to even more energy consumption. In this paper, a novel method is proposed as a combination of a counting Bloom filter and partial tags to mitigate the energy consumption of set-associative caches. This new hybrid method noticeably decreases the cache energy consumption especially in highly-associative instruction caches. In fact, it uses an enhanced counting Bloom filter to predict cache misses with a high accuracy as well as partial tags to decrease the overall cache size. This way, unnecessary tag comparisons can be prevented and therefore, the cache energy consumption is considerably reduced. Based on the simulation results, the proposed method provides the energy reduction from 22% to 31% for 4-way-32-way set-associative L1 caches bigger than 16 kB running the MiBench programs. The improvements are attained with a negligible system performance degradation compared to the traditional cache system.
机译:与其他内存组件相比,缓存系统耗散了大量能量。如果将高速缓存设计为具有集关联结构以提高系统性能,则将加剧这种情况,因为并行访问集条目以进行标记比较会导致更多的能耗。在本文中,提出了一种新的方法,该方法将计数布隆过滤器和部分标签结合起来以减轻集合关联缓存的能耗。这种新的混合方法显着降低了缓存能量消耗,尤其是在高度关联的指令缓存中。实际上,它使用增强的计数布隆过滤器来高精度地预测高速缓存未命中,并使用部分标签来减小整体高速缓存大小。这样,可以防止不必要的标签比较,因此大大降低了缓存能量消耗。根据仿真结果,对于运行MiBench程序的大于16 kB的4路32路集关联L1高速缓存,该方法可将能耗从22%降低到31%。与传统的缓存系统相比,系统性能的降低可忽略不计,从而实现了这些改进。

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