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Conference Papers Year : 2005

A Practical Method For Quickly Evaluating Program Optimizations


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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inria-00001054 , version 1 (26-01-2006)


  • HAL Id : inria-00001054 , version 1


Grigori Fursin, Albert Cohen, Michael O'Boyle, Olivier Temam. A Practical Method For Quickly Evaluating Program Optimizations. HiPEAC 2005 -- 1st International Conference on High Performance Embedded Architectures \& Compilers, Nov 2005, Barcelona, Spain, France. ⟨inria-00001054⟩
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