A multi-objective auto-tuning framework for parallel codes

Herbert Jordan, Peter Thoman, Juan J. Durillo, Simone Pellegrini, Philipp Gschwandtner, Thomas Fahringer, Hans Moritsch
2012 2012 International Conference for High Performance Computing, Networking, Storage and Analysis  
In this paper we introduce a multi-objective autotuning framework comprising compiler and runtime components. Focusing on individual code regions, our compiler uses a novel search technique to compute a set of optimal solutions, which are encoded into a multi-versioned executable. This enables the runtime system to choose specifically tuned code versions when dynamically adjusting to changing circumstances. We demonstrate our method by tuning loop tiling in cachesensitive parallel programs,
more » ... allel programs, optimizing for both runtime and efficiency. Our static optimizer finds solutions matching or surpassing those determined by exhaustively sampling the search space on a regular grid, while using less than 4% of the computational effort on average. Additionally, we show that parallelism-aware multi-versioning approaches like our own gain a performance improvement of up to 70% over solutions tuned for only one specific number of threads.
doi:10.1109/sc.2012.7 dblp:conf/sc/JordanTBPGFM12 fatcat:7gq43aun75dcpnpvady63cmmfy