A Practical Method For Quickly Evaluating Program Optimizations

Grigori Fursin 1 Albert Cohen 1 Michael O'Boyle 2 Olivier Temam 1
1 ALCHEMY - Architectures, Languages and Compilers to Harness the End of Moore Years
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : This article aims at making iterative optimization practical and usable by speeding up the evaluation of a large range of optimizations. Instead of using a full run to evaluate a single program optimization, we take advantage of periods of stable performance, called phases. For that purpose, we propose a low-overhead phase detection scheme geared toward fast optimization space pruning, using code instrumentation and versioning implemented in a production compiler. Our approach is driven by simplicity and practicality. We show that a simple phase detection scheme can be sufficient for optimization space pruning. We also show it is possible to search for complex optimizations at run-time without resorting to sophisticated dynamic compilation frameworks. Beyond iterative optimization, our approach also enables one to quickly design selftuned applications. Considering 5 representative SpecFP2000 benchmarks, our approach speeds up iterative search for the best program optimizations by a factor of 32 to 962. Phase prediction is 99.4% accurate on average, with an overhead of only 2.6%. The resulting self-tuned implementations bring an average speed-up of 1.4.
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Conference papers
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Submitted on : Thursday, January 26, 2006 - 3:15:08 PM
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Grigori Fursin, Albert Cohen, Michael O'Boyle, Olivier Temam. A Practical Method For Quickly Evaluating Program Optimizations. Proceedings of the 1st International Conference on High Performance Embedded Architectures \& Compilers (HiPEAC 2005), Nov 2005, Barcelona, Spain. ⟨inria-00001054⟩

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