Data compression: methods and theory
Data compression: methods and theory
Data cache management using frequency-based replacement
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Optimal prefetching via data compression (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
A Model of Workloads and its Use in Miss-Rate Prediction for Fully Associative Caches
IEEE Transactions on Computers
The LRU-K page replacement algorithm for database disk buffering
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Characteristics of program localities
Communications of the ACM
Some Results on Distribution-Free Analysis of Paging Algorithms
IEEE Transactions on Computers
On optimization of storage hierarchies
IBM Journal of Research and Development
Compression-Based Program Characterization for Improving Cache Memory Performance
IEEE Transactions on Computers
Real time aspects of cluster based caches
RTCSA '95 Proceedings of the 2nd International Workshop on Real-Time Computing Systems and Applications
A time invariant working set model for independent reference
ACM-SE 33 Proceedings of the 33rd annual on Southeast regional conference
External memory page remapping for embedded multimedia systems
Proceedings of the 2007 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
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Locality of reference in program behavior has been studied and modelled extensively because of its application to CPU, cache and virtual memory design, code optimization, multiprogramming etc. In this paper we propose a scheme based on Markov chains for modelling the time interval between successive references to the same address in a program execution. Using this technique and trace driven simulations, it is shown that memory references are predictable and repetitive. This is used to improve miss ratios of memory replacement algorithms. Using trace driven simulations over a wide range of traces we get improvements up to 35% over the least recently used (LRU) replacement algorithm.