Emulating Optimal Replacement with a Shepherd Cache

Rajan, Kaushik Sunder; Govindarajan, Raghav

doi:10.1109/micro.2007.4408275

Cited by 10 publications

(11 citation statements)

References 12 publications

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“…Although they successfully combine LRU and LFU replacement policies together via additional data structures, they significantly increase hardware overhead and complexity. A recent study on Shepherd Cache [12] even changes the organization of the existing cache, leading to further verification and testing efforts for it.…”

Section: Existing Solutionsmentioning

confidence: 99%

Adaptive Insertion and Promotion Policies Based on Least Recently Used Replacement

Jin

Yu³

et al. 2013

IEICE Trans. Inf. & Syst.

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SUMMARYTo improve Last-Level Cache (LLC) management, numerous approaches have been proposed requiring additional hardware budget and increased overhead. A number of these approaches even change the organization of the existing cache design. In this letter, we propose Adaptive Insertion and Promotion (AIP) policies based on Least Recently Used (LRU) replacement. AIP dynamically inserts a missed line in the middle of the cache list and promotes a reused line several steps left, realizing the combination of LRU and LFU policies deliberately under a single unified scheme. As a result, it benefits workloads with high locality as well as with many frequently reused lines. Most importantly, AIP requires no additional hardware other than a typical LRU list, thus it can be easily integrated into the existing hardware with minimal changes. Other issues around LLC such as scans, thrashing and dead lines are all explored in our study. Experimental results on the gem5 simulator with SPEC CUP2006 benchmarks indicate that AIP outperforms LRU replacement policy by an average of 5.8% on the misses per thousand instructions metric.

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Section: Existing Solutionsmentioning

confidence: 99%

Adaptive Insertion and Promotion Policies Based on Least Recently Used Replacement

Jin

Yu³

et al. 2013

IEICE Trans. Inf. & Syst.

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“…PACMan [36] extends RRIP to be prefetch-aware. Shepherd cache [29] uses two separate caches to record the relative access order of blocks, and then emulates the replacement and bypass decisions of OPT+B.…”

Section: Related Workmentioning

confidence: 99%

Optimal bypass monitor for high performance last-level caches

Tong

Xie

et al. 2012

Proceedings of the 21st International Conference on Parallel Architectures and Compilation Techniques

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In the last-level cache, large amounts of blocks have reuse distances greater than the available cache capacity. Cache performance and efficiency can be improved if some subset of these distant reuse blocks can reside in the cache longer. The bypass technique is an effective and attractive solution that prevents the insertion of harmful blocks.Our analysis shows that bypass can contribute significant performance improvement, and the optimal bypass can achieve similar performance compared to OPT+B, which is the theoretical optimal replacement policy. Thus, we propose a bypass technique called Optimal Bypass Monitor (OBM), which makes bypass decisions by learning and predicting the behavior of the optimal bypass. OBM keeps a short global track of the incoming-victim block pairs. By detecting the first reuse block in each pair, the behavior of the optimal bypass on the track can be asserted to guide the bypass choice.Any existing replacement policy can be extended with OBM while requiring negligible design modification. Our experimental results show that using less than 1.5KB extra memory, OBM with the NRU replacement policy outperforms LRU by 9.7% and 8.9% for single-thread and multiprogrammed workloads respectively. Compared with other state-of-the-art proposals such as DRRIP and SDBP, it achieves superior performance with less storage overhead.

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“…Finally, a recent approach, called shepherd cache [25], attempts to emulate the Belady's optimal algorithm for a conventional cache. In this work, the large, highly associative cache is replaced by a cache with lower associativity (the main cache) and use a secondary (shepherd) cache to approximate an optimal replacement policy in the main cache.…”

Section: Related Workmentioning

confidence: 99%

Instruction-based reuse-distance prediction for effective cache management

Petoumenos

Κεραμίδας

2009

2009 International Symposium on Systems, Architectures, Modeling, and Simulation

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Abstract-The effect of caching is fully determined by the program locality or the data reuse and several cache management techniques try to base their decisions on the prediction of temporal locality in programs. However, prior work reports only rough techniques which either try to predict when a cache block loses its temporal locality or try to categorize cache items as highly or poorly temporal. In this work, we quantify the temporal characteristics of the cache block at run time by predicting the cache block reuse distances (measured in intervening cache accesses), based on the access patterns of the instructions (PCs) that touch the cache blocks. We show that an instruction-based reused distance predictor is very accurate and allows approximation of optimal replacement decisions, since we can "see" the future. We experimentally evaluate our prediction scheme in various sizes L2 caches using a subset of the most memory intensive SPEC2000 benchmarks. Our proposal obtains a significant improvement in terms of IPC over traditional LRU up to 130.6% (17.2% on average) and it also outperforms the previous state of the art proposal (namely Dynamic Insertion Policy or DIP) by up to 80.7% (15.8% on average).

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Emulating Optimal Replacement with a Shepherd Cache

Cited by 10 publications

References 12 publications

Adaptive Insertion and Promotion Policies Based on Least Recently Used Replacement

Adaptive Insertion and Promotion Policies Based on Least Recently Used Replacement

Optimal bypass monitor for high performance last-level caches

Instruction-based reuse-distance prediction for effective cache management

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