RT Journal Article
JF Computer Architecture and High Performance Computing, Symposium on
YR 2010
VO 00
SP 223
TI Using Support Vector Machines to Learn How to Compile a Method
A1 Ricardo Nabinger Sanchez,
A1 Duane Szafron,
A1 Marius Pirvu,
A1 Mark Stoodley,
A1 José Nelson Amaral,
K1 Testarossa
K1 Java
K1 Just-in-Time compiler
K1 Method-specific compilation
K1 Machine learning
K1 Support Vector Machines
AB The question addressed in this paper is what subset of code transformations should be attempted for a given method in a Just-in-Time compilation environment. The solution proposed is to use a Support Vector Machine (SVM) to learn a model based on method features and on the measured compilation and execution times of the methods. An extensive exploration phase collects a set of example compilations to be used by the SVM to train the model. This paper reports on a work in progress. So far, linear-SVM models, applied to benchmarks from the SPECjvm98 suite, have not outperformed the compilation plans engineered by the development team over many years. However the models almost match that performance for the javac benchmark.
PB IEEE Computer Society, [URL:http://www.computer.org]
SN 1550-6533
LA English
DO 10.1109/SBAC-PAD.2010.35
LK http://doi.ieeecomputersociety.org/10.1109/SBAC-PAD.2010.35