Rapidly Selecting Good Compiler Optimizations using Performance Counters

Applying the right compiler optimizations to a particular program can have a significant impact on program performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space...

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Bibliographic Details
Main Authors: Cavazos, John, Fursin, Grigori, Agakov, Felix, Bonilla, Edwin, O'Boyle, Michael F. P., Temam, Olivier
Format: Conference Proceeding
Language:English
Subjects:
Computer architecture
Counting circuits
Hardware
Informatics
Optimizing compilers
Performance analysis
Performance gain
Probability distribution
Production facilities
Program processors
Software and its engineering > Software notations and tools > Compilers
Citations: Items that cite this one
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Summary:Applying the right compiler optimizations to a particular program can have a significant impact on program performance. Due to the non-linear interaction of compiler optimizations, however, determining the best setting is nontrivial. There have been several proposed techniques that search the space of compiler options to find good solutions; however such approaches can be expensive. This paper proposes a different approach using performance counters as a means of determining good compiler optimization settings. This is achieved by learning a model off-line which can then be used to determine good settings for any new program. We show that such an approach outperforms the state-ofthe- art and is two orders of magnitude faster on average. Furthermore, we show that our performance counter-based approach outperforms techniques based on static code features. Using our technique we achieve a 17% improvement over the highest optimization setting of the commercial PathScale EKOPath 2.3.1 optimizing compiler on the SPEC benchmark suite on a recent AMD Athlon 64 3700+ platform.
DOI:10.1109/CGO.2007.32