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Expected I-cache miss rates via the gap model

Published: 01 April 1994 Publication History

Abstract

To evaluate the performance of a memory system, computer architects must determine the miss rate m of a cache C when running program P. Typically, the measured miss rate depends on the specific address mapping M of P set arbitrarily by the compiler and linker. In this paper, we remove the effect of the address-mapping on the miss rate by analyzing a symbolic trace T of basic blocks. By assuming each basic block has an equal probability of ending up anywhere in the address map, we determine the expected miss rate averaged over all possible address mappings.Our resulting gap model gives the expected miss rate for instruction caches of varying cache size, line size, and set associativity. Our model is simple but robust, and turns out to be the familiar LRU stack model with a statistical viewpoint. Our model allows a trace of arbitrary length to be compactly summarized in a few thousand bytes of information. Our model also predicts how an intervening trace, such as an operating system call or a task switch, will affect the miss rate. Comparisons to measured miss rates from SPEC 92 instruction traces show that our model typically has relative differences of less than 20% for a variety of cache parameters.

References

[1]
Anant Agarwal, Mark Horowitz, and John Hennessy. An Analytical Cache Model. A CM Transactions on Computer Systems, 7(2):184-215, May 1989.
[2]
C. K. Chow. Determining the Optimum Capacity of a Cache Memory. IBM Technical Disclosure Bulletin, 17(10):3163-3166, March 1975.
[3]
Robert F. Cmelik. Shade: A fast instruction set simulator for execution profiling. Technical Report TR-93-12, Sun Microsystems Inc., April 1993.
[4]
Robert F. Cmelik. Spixtools, Introduction and User's Manual. Technical Report TR-93-06, Sun Microsystems Inc., Feb 1993.
[5]
Jack W. Davidson and Anne M. Holler. A Study of a C Function Inliner. Software Practice and Experience, 18(8):775-790, August 1988.
[6]
John L. Hennessy and David A. Patterson. Computer Architecture: A Quantitative Approach. Morgan Kaufmann, San Mateo, CA, 1990.
[7]
Mark D. Hill. Aspects of Cache Memory and Instruction Buffer Performance. PhD thesis, University of California at Berkeley, Computer Science Division, 1987. Tech. Rep. UCB/CSD 87/381.
[8]
Wen-Mei W. Hwu and Pohua P. Chang. Inline Function Expansion for Compiling C Programs. In A CM SIGPLAN Conference on Programming Language Design and Implementation, pages 246- 257, Portland, OR, June 21-23 1989. ACM.
[9]
Scott McFarling. Proocedure Merging with Instruction Caches. In A CM SIGPLAN Conference on Programming Language Design and Implementation, pages 71-79~ Toronto, Canada, June 26-28 1991. ACM.
[10]
William Pugh. Skip Listn; A Ptobabilistic Alternative to Balanced Trees. Communications of the ACM, 33(6):668-676, June 1990.
[11]
Russell W. Quong. Expected Values for Cache Miss Rates for a Single Trace. Technical Report TR-EE 93-26, Purdue University, July 1993.
[12]
Turner Rollins and Bill Strecker. Use of the LRU Stack Depth Distribution for Simulation of Paging Behavior. Communications of the A CM, 20(7):795-798, November 1977.
[13]
J. P. Singh, H. S. Stone, and D. Thi~baut. A Model of Workloads and Its Use in Miss-Rate Prediction for Fully Associative Caches. IEEE Trans. actions on Computers, 41(7):811-825, July 1992.
[14]
Alan Jay Smith. Cache Memories. Computing Surveys, 14(3):473-530, September 1982.
[15]
J.R. Spirn. Program Behavior: Models and Measureme:nts. Operating and Programming Systems Series. Elsevier Scientific Publishing Co., Inc., New York, 1977.
[16]
Dominique Thi~baut, Joel L. Wolf, and Harold S. Stone. Synthetic Traces for Trace-Driven Simulation of Cache Memories. IEEE Transactions on Computers, 41(4):388-410, April 1992.
[17]
Jenlong Wang and Russell W. Quong. The Feasibility of Using Compression to Increase Memory System Performance. in International Workshop on Modeling, Analysis and Simulation of Computer' and Telecommunications Systems -- MAS- COTS 1994, pages 107-113, Jan. 31 - Feb. 2 1994.

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cover image ACM Conferences
ISCA '94: Proceedings of the 21st annual international symposium on Computer architecture
April 1994
394 pages
ISBN:0818655100
  • cover image ACM SIGARCH Computer Architecture News
    ACM SIGARCH Computer Architecture News  Volume 22, Issue 2
    Special Issue: Proceedings of the 21st annual international symposium on Computer architecture (ISCA '94)
    April 1994
    386 pages
    ISSN:0163-5964
    DOI:10.1145/192007
    Issue’s Table of Contents

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IEEE Computer Society Press

Washington, DC, United States

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Published: 01 April 1994

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