TLB Index-Based Tagging for Reducing Data Cache and TLB Energy Consumption

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Conventional cache tag matching identifies the requested data based on a memory address. However, this address-based tag matching is inefficient because it requires unnecessarily many tag bits. Previous studies show that translation look-aside buffer (TLB) index-based tagging (TLBIT) can be adopted in instruction caches because there are not many different tags at a given moment due to spatial locality, and those tags can be captured by TLBs. For the TLBIT scheme, extra TLB indices are added to each TLB entry and conventional cache tags are replaced with TLB indices to identify the requested data in the cache. TLBIT reduces the number of required tag bits in tag arrays; therefore, the cache energy consumption and area are decreased. In this paper, we show that naively adopting TLBIT for data caches is inefficient, in terms of performance and energy consumption, because of cache line searches and invalidations on TLB misses. To achieve the true potential of TLBIT, we propose four novel techniques: search zone, c-LRU, TLB buffer and demand address fetching. The search zone reduces unnecessary cache line searching and c-LRU reduces the cache line invalidations. The TLB buffer prevents immediate cache line invalidations on TLB misses. Furthermore, we present demand address fetching to reduce energy consumption in the TLB. From our experiments, we observed that the proposed techniques reduce the overall dynamic energy consumption of the data cache by 14.3 percent on average. The overall tag array area and leackage power of the data cache are also reduced by 54 and 45 percent, respectively. The TLB energy consumption is reduced by 22.7 percent. The performance impact is small, less than 0.4 percent on average. We also demonstrate that TLBIT can be applied to large caches, and set-associative TLBs.
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IEEE TRANSACTIONS ON COMPUTERS, v.66, no.7, pp.1200 - 1211

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CS-Journal Papers(저널논문)
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