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Description

Recent developments in programmable, highly parallel Graphics Processing Units (GPUs) have enabled high performance implementations of machine learning algorithms. We describe a solver for Support Vector Machine training, using Platt's Sequential Minimal Optimization algorithm, which achieves speedups of 5-32x over LibSVM running on a high-end traditional processor. We also present a system for SVM classification which achieves speedups of 120-150x over LibSVM.

Details

Title
Fast Support Vector Machine Training and Classification on Graphics Processors
Creator
Keutzer, Kurt, Author
Catanzaro, Bryan Christopher, Author
Sundaram, Narayanan, Author
EECS Department, University of California, Publisher
Published
2008-02-08
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
EECS-2008-11
Type
Text
Format
technical reports
Extent
10 p
Archive
The Engineering Library
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