Using program and user information to improve file prediction performance

Appeared in Proceedings of the International Symposium on Performance Analysis of Systems and Software (ISPASS '01).

Abstract

Correct prediction of file accesses can improve system performance by mitigating the relative speed difference between CPU and disks. This paper discusses Program-based Last Successor (PLS) and presents Program- and User-based Last Successor (PULS), file prediction algorithms that utilize information about the program and user that access the files. Our simulation results show that PLS makes 21% fewer incorrect predictions and PULS makes 24% fewer incorrect predictions than last-successor with roughly the same number of correct predictions that last successor makes. The cache space wasted on incorrect predictions can be reduced accordingly. We also show that a cache using the Least Recently Used (LRU) caching algorithm can perform better when the PULS is applied. In some cases, a cache using LRU and either PLS or PULS performs better than a cache up to 40 times larger using LRU alone.

Publication date:
November 2001

Authors:
Tsozen Yeh
Darrell D. E. Long
Scott A. Brandt

Projects:
Prediction and Grouping

Available media

Full paper text: PDF

Bibtex entry

@inproceedings{yeh-ispass01,
  author       = {Tsozen Yeh and Darrell D. E. Long and Scott A. Brandt},
  title        = {Using program and user information to improve file prediction performance},
  booktitle    = {Proceedings of the International Symposium on Performance Analysis of Systems and Software (ISPASS '01)},
  pages        = {Proceedings},
  month        = nov,
  year         = {2001},
}