Informatics Report Series



Related Pages

Report (by Number) Index
Report (by Date) Index
Author Index
Institute Index

Title:Fast Compiler Optimisation Evaluation Using Code-Feature Based Performance Prediction
Authors: Christophe Dubach ; John Cavazos ; Bjoern Franke ; Michael O'Boyle ; Grigori Fursin ; Olivier Temam
Date:May 2007
Publication Title:Proceedings of the ACM International Conference on Computing Frontiers
Publication Type:Conference Paper Publication Status:Published
Performance tuning is an important and time consuming task which may have to be repeated for each new application and platform. Although iterative optimisation can automate this process, it still requires many executions of different versions of the program. As execution time is frequently the limiting factor in the number of versions or transformed programs that can be considered, what is needed is a mechanism that can automatically predict the performance of a modified program without actually having to run it. This paper presents a new machine learning based technique to automatically predict the speedup of a modified program using a performance model based on the code features of the tuned programs. Unlike previous approaches it does not require any prior learning over a benchmark suite. Furthermore, it can be used to predict the performance of any tuning and is not restricted to a prior seen transformation space. We show that it can deliver predictions with a high correlation coefficient and can be used to dramatically reduce the cost of search.
Links To Paper
1st Link
Bibtex format
author = { Christophe Dubach and John Cavazos and Bjoern Franke and Michael O'Boyle and Grigori Fursin and Olivier Temam },
title = {Fast Compiler Optimisation Evaluation Using Code-Feature Based Performance Prediction},
book title = {Proceedings of the ACM International Conference on Computing Frontiers},
year = 2007,
month = {May},
url = {},

Home : Publications : Report 

Please mail <> with any changes or corrections.
Unless explicitly stated otherwise, all material is copyright The University of Edinburgh