Quick and Practical Run-Time Evaluation of Multiple Program Optimizations

Grigori Fursin, Albert Cohen, Michael O'Boyle, Olivier Temam

Research output: Chapter in Book/Report/Conference proceedingChapter

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.
Original languageEnglish
Title of host publicationTransactions on High-Performance Embedded Architectures and Compilers I
EditorsPer Stenström
PublisherSpringer Berlin Heidelberg
Pages34-53
Number of pages20
ISBN (Electronic)978-3-540-71528-3
ISBN (Print)978-3-540-71527-6
DOIs
Publication statusPublished - 2007

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume4050
ISSN (Print)0302-9743

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