Calculating stack distances efficiently

200292 citationsJournal Article

Authors

George Almási · University of Illinois Urbana-Champaign

Cǎlin Caşcaval · University of Illinois Urbana-Champaign

David Padua · University of Illinois Urbana-Champaign

Abstract

This paper 1 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.

Topics & Keywords

Parallel Computing and Optimization Techniques Cloud Computing and Resource Management Software System Performance and Reliability

Publication Details

Published in: ACM SIGPLAN Notices

Volume 38, Issue 2 supplement, pp. 37-43

DOI: 10.1145/773039.773043

Field-Weighted Citation Impact: 2.48

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Calculating stack distances efficiently

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Abstract

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Publication Details