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 self-tuned 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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Fursin, G., Cohen, A., O’Boyle, M., Temam, O. (2005). A Practical Method for Quickly Evaluating Program Optimizations. In: Conte, T., Navarro, N., Hwu, Wm.W., Valero, M., Ungerer, T. (eds) High Performance Embedded Architectures and Compilers. HiPEAC 2005. Lecture Notes in Computer Science, vol 3793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11587514_4
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DOI: https://doi.org/10.1007/11587514_4
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