ACM Home Page
Please provide us with feedback. Feedback
An analytical cache model
Full text PdfPdf (2.51 MB)
Source ACM Transactions on Computer Systems (TOCS) archive
Volume 7 ,  Issue 2  (May 1989) table of contents
Pages: 184 - 215  
Year of Publication: 1989
ISSN:0734-2071
Authors
A. Agarwal  Massachusetts Institute of Technology, Cambridge
J. Hennessy  Stanford Univ., Stanford, CA
M. Horowitz  Stanford Univ., Stanford, CA
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 22,   Downloads (12 Months): 207,   Citation Count: 59
Additional Information:

abstract   references   cited by   index terms   review   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/63404.63407
What is a DOI?

ABSTRACT

Trace-driven simulation and hardware measurement are the techniques most often used to obtain accurate performance figures for caches. The former requires a large amount of simulation time to evaluate each cache configuration while the latter is restricted to measurements of existing caches. An analytical cache model that uses parameters extracted from address traces of programs can efficiently provide estimates of cache performance and show the effects of varying cache parameters. By representing the factors that affect cache performance, we develop an analytical model that gives miss rates for a given trace as a function of cache size, degree of associativity, block size, subblock size, multiprogramming level, task switch interval, and observation interval. The predicted values closely approximate the results of trace-driven simulations, while requiring only a small fraction of the computation cost.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
AGARWAL, A., HOROWITZ, M., AND HENNESSY, J. An analytical cache model. Computer Systems Lab. Rep. TR 86-304, Stanford Univ. Stanford, Calif., Sept. 1986.
3
4
 
5
ALPERT, D. Performance tradeoffs for microprocessor cache memories. Computer Systems Lab. Rep. TR 83-239, Stanford Univ., Stanford, Calif., Dec. 1983.
6
 
7
CHOW, C.K. Determining the optimum capacity of a cache memory. IBM Tech. Disclosure Bull. I7, 10 (Mar. 1975), 3163-3166.
8
9
10
 
11
EASTON, M. C. Computation of cold-start miss ratios. IEEE Trans. Comput. C-27, 5 (May 1978).
12
13
14
 
15
KUMAR, B. A model of spatial locality and its application to cache design. Unpublished Report, Computer Systems Lab., Stanford Univ., Stanford, Calif., 1979.
 
16
 
17
MATTSON, R. L., GECSEI, J., SLUTZ, D. R., AND TRAIGER, I. L. Evaluation techniques for storage hierarchies. IBM Syst. J. 9, 2 (1970), 78-117.
18
 
19
20
 
21
SMITH, A.J. A comparative study of set associative memory mapping algorithms and their use for cache and main memory. IEEE Trans. Softw. Eng. SE-4, 2 (Mar. 1978), 121-130.
22
23
 
24
25
26

CITED BY  59


REVIEW

"Hosagrahar V. Jagadish : Reviewer"

The authors present an analytical model to predict cache performance. By plugging the values for different parameters into this model, one can predict the miss ratio. Some of these model parameters are design parameters for which different value  more...

Collaborative Colleagues:
A. Agarwal: colleagues
J. Hennessy: colleagues
M. Horowitz: colleagues