- Abstract:
-
This paper describes a portable,machine learning-based approach to Java optimisation. This approach uses an instance-based learning scheme to select good transformations drawn from Pugh 's Unified Transformation Framework [11]. This approach was implemented and applied to a number of numerical Java benchmarks on two platforms. Using this scheme, we are able to gain over 70% of the performance improvement found when using an exhaustive iterative search of the best compiler optimisations. Thus we have a scheme that gives a high level of portable performance without any excessive compilations.
- Links To Paper
- 1st Link
- Bibtex format
- @InProceedings{EDI-INF-RR-0490,
- author = {
Shun Long
and Michael O'Boyle
},
- title = {Adaptive Java Optimisation using Instance-based Learning},
- book title = {Procs of 18th Annual ACM International Conference on Supercomputing (ICS'04)},
- year = 2004,
- month = {Jun},
- pages = {237-246},
- url = {http://www.dcs.ed.ac.uk/home/shun/ICS04.pdf},
- }
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