Proceedings of the 21st International Symposium on High-Performance Computer Architecture (HPCA), Bay Area, CA, February 2015.
Gennady Pekhimenko, Tyler Huberty, Rui Cai, Onur Mutlu, Phillip P. Gibbons*, Michael A. Kozuch*,
Todd C. Mowry
Carnegie Mellon University
*Intel Labs Pittsburgh
We introduce a set of new Compression-Aware Management Policies (CAMP) for on-chip caches that employ data compression. Our management policies are based on two key ideas. First, we show that it is possible to build a more effi cient management policy for compressed caches if the compressed block size is directly used in calculating the value (importance) of a block to the cache. This leads to Minimal-Value Eviction (MVE), a policy that evicts the cache blocks with the least value, based on both the size and the expected future reuse. Second, we show that, in some cases, compressed block size can be used as an e fficient indicator of the future reuse of a cache block. We use this idea to build a new insertion policy called Size-based Insertion Policy (SIP) that dynamically prioritizes cache blocks using their compressed size as an indicator.
We compare CAMP (and its global variant G-CAMP) to prior on-chip cache management policies (both size-oblivious and size-aware) and find that our mechanisms are more e ective in using compressed block size as an extra dimension in cache management decisions. Our results show that the proposed management policies (i) decrease off -chip bandwidth consumption (by 8.7% in single-core), (ii) decrease memory subsystem energy consumption (by 7.2% in single-core) for memory intensive workloads compared to the best prior mechanism, and (iii) improve performance (by 4.9%/9.0%/10.2% on average in single- /two-/four-core workload evaluations and up to 20.1%) CAMP is eff ective for a variety of compression algorithms and diff erent cache designs with local and global replacement strategies.
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