Estimating neural networks-based algorithm for adaptive cache replacement

In this paper, we propose an adaptive cache replacement scheme based on the estimating type of neural networks (NN's). The statistical prediction property of such NN's is used in our work to develop a neural network based replacement policy which can effectively identify and eliminate inactive cache lines. This would provide larger free space for a cache to retain actively referenced lines. The proposed strategy may, therefore, yield better cache performance as compared to the conventional schemes. Simulation results for a wide spectrum of cache configurations indicate that the estimating neural network based replacement scheme provides significant performance advantage over existing policies.

[1]  Alan Jay Smith,et al.  A Comparative Study of Set Associative Memory Mapping Algorithms and Their Use for Cache and Main Memory , 1978, IEEE Transactions on Software Engineering.

[2]  Janak H. Patel,et al.  Accurate Low-Cost Methods for Performance Evaluation of Cache Memory Systems , 1988, IEEE Trans. Computers.

[3]  Harold S. Stone,et al.  Improving Disk Cache Hit-Ratios Through Cache Partitioning , 1992, IEEE Trans. Computers.

[4]  Bart Kosko,et al.  Differential competitive learning for centroid estimation and phoneme recognition , 1991, IEEE Trans. Neural Networks.

[5]  James R. Goodman,et al.  Instruction Cache Replacement Policies and Organizations , 1985, IEEE Transactions on Computers.

[6]  Thomas M. Conte,et al.  The Effect of Code Expanding Optimizations on Instruction Cache Design , 1993, IEEE Trans. Computers.

[7]  S. G. Tucker,et al.  The IBM 3090 System: An Overview , 1986, IBM Syst. J..

[8]  Mohammad S. Obaidat,et al.  Ultrasonic Transducer Characterization by Neural Networks , 1998, Inf. Sci..

[9]  Thomas Roberts Puzak,et al.  Analysis of cache replacement-algorithms , 1985 .

[10]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[11]  Alan Jay Smith,et al.  Evaluating Associativity in CPU Caches , 1989, IEEE Trans. Computers.

[12]  Mark Horowitz,et al.  An analytical cache model , 1989, TOCS.

[13]  Mohammad S. Obaidat,et al.  Performance evaluation of CISC computer systems under single- and two-level cache environments , 1994, CSC '94.

[14]  Hans G. C. Tråvén,et al.  A neural network approach to statistical pattern classification by 'semiparametric' estimation of probability density functions , 1991, IEEE Trans. Neural Networks.

[15]  Sang-Hui Park,et al.  Self-creating and organizing neural networks , 1994, IEEE Trans. Neural Networks.

[16]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[17]  Wen-mei W. Hwu,et al.  Achieving High Instruction Cache Performance With An Optimizing Compiler , 1989, The 16th Annual International Symposium on Computer Architecture.

[18]  Mohammad S. Obaidat,et al.  A performance evaluation methodology for computer systems , 1995, Proceedings International Phoenix Conference on Computers and Communications.

[19]  Mahmoud A. Manzoul,et al.  AN IMPROVED FUZZY REPLACEMENT ALGORITHM FOR CACHE MEMORIES , 1993 .

[20]  Eric E. Johnson,et al.  PDATS Lossless Address Trace Compression For Reducing File Size And Access Time , 1994, Proceeding of 13th IEEE Annual International Phoenix Conference on Computers and Communications.