论文信息 - Calculating stack distances efficiently

Calculating stack distances efficiently

This paper1 describes our experience using the stack processing algorithm [6] for estimating the number of cache misses in scientific programs. By using a new data structure and various optimization techniques we obtain instrumented run-times within 50 to 100 times the original optimized run-times of our benchmarks.

David A. Padua | George Almási | Calin Cascaval

[1] Vincent J. Kruskal,et al. LRU Stack Processing , 1975, IBM J. Res. Dev..

[2] Santosh G. Abraham,et al. Set-associative cache simulation using generalized binomial trees , 1995, TOCS.

[3] Donald E. Knuth,et al. The Art of Computer Programming: Volume 3: Sorting and Searching , 1998 .

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

[5] Alan Jay Smith,et al. Efficient (stack) algorithms for analysis of write-back and sector memories , 1989, TOCS.

[6] Donald E. Knuth,et al. The art of computer programming, volume 3: (2nd ed.) sorting and searching , 1998 .

[7] Irving L. Traiger,et al. Evaluation Techniques for Storage Hierarchies , 1970, IBM Syst. J..

[8] Wen-Hann Wang,et al. Efficient trace-driven simulation methods for cache performance analysis , 1991, TOCS.

[9] Geoffrey C. Fox,et al. The Perfect Club Benchmarks: Effective Performance Evaluation of Supercomputers , 1989, Int. J. High Perform. Comput. Appl..

[10] Ronald L. Rivest,et al. Introduction to Algorithms , 1990 .