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LIRS: an efficient low inter-reference recency set replacement policy to improve buffer cache performance
Abstract
Although LRU replacement policy has been commonly used in the buffer cache management, it is well known for its inability to cope with access patterns with weak locality. Previous work, such as LRU-K and 2Q, attempts to enhance LRU capacity by making use of additional history information of previous block references other than only the recency information used in LRU. These algorithms greatly increase complexity and/or can not consistently provide performance improvement. Many recently proposed policies, such as UBM and SEQ, improve replacement performance by exploiting access regularities in references. They only address LRU problems on certain specific and well-defined cases such as access patterns like sequences and loops. Motivated by the limits of previous studies, we propose an efficient buffer cache replacement policy, called Low Inter-reference Recency Set (LIRS). LIRS effectively addresses the limits of LRU by using recency to evaluate Inter-Reference Recency (IRR) for making a replacement decision. This is in contrast to what LRU does: directly using recency to predict next reference timing. At the same time, LIRS almost retains the same simple assumption of LRU to predict future access behavior of blocks. Our objectives are to effectively address the limits of LRU for a general purpose, to retain the low overhead merit of LRU, and to outperform those replacement policies relying on the access regularity detections. Conducting simulations with a variety of traces and a wide range of cache sizes, we show that LIRS significantly outperforms LRU, and outperforms other existing replacement algorithms in most cases. Furthermore, we show that the additional cost for implementing LIRS is trivial in comparison with LRU.
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Cited by
Cooperative Caching for Chip Multiprocessors
Chang, J., & Sohi, G. S. (2006) · ACM SIGARCH Computer Architecture News · doi:10.1145/1150019.1136509 · Cited by 355
Workload analysis of a large-scale key-value store
Atikoglu, B., Xu, Y., Frachtenberg, E., Jiang, S., & Paleczny, M. (2012) · ACM SIGMETRICS Performance Evaluation Review · doi:10.1145/2318857.2254766 · Cited by 268
Self-citationOutperforming LRU with an adaptive replacement cache algorithm
Megiddo, N., & Modha, D. S. (2004) · Computer · doi:10.1109/mc.2004.1297303 · Cited by 243
Metadata
- Authors
- Jiang, S., & Zhang, X.
- Venue
- Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
- Publisher
- ACM
- Published
- 2002-06
- Pages
- 31-42
- OpenAlex
- W2072853307
- Cited by
- 489
- References
- 0
- FWCI
- 10.98
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: LIRS: an efficient low inter-reference recency set replacement policy to improve buffer cache performance. https://app.cochat.ai/papers/10.1145/511334.511340
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- Jiang, S., & Zhang, X. (2002). LIRS: an efficient low inter-reference recency set replacement policy to improve buffer cache performance. Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems. https://doi.org/10.1145/511334.511340
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