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Permanent link (DOI): https://doi.org/10.7939/R37W4H

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Applying support vector machines to discover just-in-time method-specific compilation strategies Open Access

Descriptions

Other title
Subject/Keyword
just-in-time compilation
optimizing compiler
machine-learning
method-specific
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Nabinger Sanchez, Ricardo
Supervisor and department
Szafron, Duane (Computing Science)
Amaral, José Nelson (Computing Science)
Examining committee member and department
Sutton, Richard S. (Computing Science)
Cockburn, Bruce F. (Electrical and Computer Engineering)
Department
Department of Computing Science
Specialization

Date accepted
2010-09-30T15:05:31Z
Graduation date
2010-11
Degree
Master of Science
Degree level
Master's
Abstract
Adaptive Just-in-Time compilers employ multiple techniques to concentrate compilation efforts in the most promising spots of the application, balancing tight compilation budgets with an appropriate level of code quality. Some compiler researchers propose that Just-in-Time compilers should benefit from method-specific compilation strategies. These strategies can be discovered through machine-learning techniques, where a compilation strategy is tailored to a method based on the method's characteristics. This thesis investigates the use of Support Vector Machines in Testarossa, a commercial Just-in-Time compiler employed in the IBM J9 Java Virtual Machine. This new infrastructure allows Testarossa to explore numerous compilation strategies, generating the data needed for training such models. The infrastructure also integrates Testarossa to learned models that predict which compilation strategy balances code quality and compilation effort, on a per-method basis. The thesis also presents the results of an extensive experimental evaluation of the infrastructure and compares these results with the performance of the original Testarossa.
Language
English
DOI
doi:10.7939/R37W4H
Rights
License granted by Ricardo Nabinger Sanchez (nabinger@ualberta.ca) on 2010-09-28T21:30:08Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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