ComputingComputer EngineeringComputer ScienceComputer ArchitectureData StructuresOperating SystemsBuffer ManagementCachingCaching StrategiesMemory HierarchyMemory Hierarchy DesignMemory Hierarchy OptimizationBuffer Cache ManagementCache Access PatternsCache ManagementCache Replacement PoliciesComplexityMemory LocalityReplacementReplacement Decision Making
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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The working set model for program behavior
Peter J. Denning · Communications of the ACM · 1983 · 853 citations · Full text
The working set model for program behavior
Peter J. Denning · Communications of the ACM · 1968 · 652 citations · Full text
Informed prefetching and caching
Russel H. Patterson, Garth A. Gibson, E. Ginting et al. · 1995 · 647 citations