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 fa...
Grigori Fursin, Albert Cohen, Michael F. P. O'Boyl