(Enter summary)
Abstract: Feedback-directed optimization has become an increasingly important
tool in designing and building optimizing compilers. Recently,
reuse-distance analysis has shown much promise in predicting the
memory behavior of programs over a wide range of data sizes.
Reuse-distance analysis predicts program locality by experimentally
determining locality properties as a function of the data size of
a program, allowing accurate locality analysis when the program's
data size changes. (Update)
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2: Predicting whole-program locality through reuse distance analysis
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BibTeX entry: (Update)
C. Fang, S. Carr, S. Onder, and Z. Wang. Reuse-distance-based miss-rate prediction on a per instruction basis. In Workshop on Memory System Performance (MSP), 2004. http://citeseer.ist.psu.edu/fang04reusedistancebased.html More
@misc{ fang04reusedistancebased,
author = "C. Fang and S. Carr and S. Onder and Z. Wang",
title = "Reuse-distance-based miss-rate prediction on a per instruction basis",
text = "C. Fang, S. Carr, S. Onder, and Z. Wang. Reuse-distance-based miss-rate
prediction on a per instruction basis. In Workshop on Memory System Performance
(MSP), 2004.",
year = "2004",
url = "citeseer.ist.psu.edu/fang04reusedistancebased.html" }
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