Support Vector Machines on GPU with Sparse Matrix Format
Published 1 December 2010
Tsung-Kai Lin, Shao‐Yi Chien
Citations33
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TL;DR
Sparse matrix format is introduced into parallel SVM to achieve better performance and Experimental results show that the speedup of 55x–133.8x over LIBSVM can be achieved in training process on NVIDIA GeForce GTX470.
Abstract
Emerging general-purpose Graphics Processing Unit (GPU) provides a multi-core platform for wide applications, including machine learning algorithms. In this paper, we proposed several techniques to accelerate Support Vector Machines (SVM) on GPUs. Sparse matrix format is introduced into parallel SVM to achieve better performance. Experimental results show that the speedup of 55x-133.8x over LIBSVM can be achieved in training process on NVIDIA GeForce GTX470.
Keywords
Computer Science
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