Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization

We develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning methods within Bayesian optimization and evaluate their effectiveness. We select six of the most complex PolyBench benchmarks and apply th...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Concurrency and computation 2022-09, Vol.34 (20), p.n/a
Hauptverfasser:	Wu, Xingfu, Kruse, Michael, Balaprakash, Prasanna, Finkel, Hal, Hovland, Paul, Taylor, Valerie, Hall, Mary
Format:	Artikel
Sprache:	eng
Schlagworte:	autotuning Bayesian analysis Benchmarks Clang Deep learning loop transformation Machine learning Optimization Parameters Performance enhancement Polly PolyBench benchmarks
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!