GPUSVM: a comprehensive CUDA based support vector machine package GPUSVM (graphic processing unit support vector machine) is a computing unified device architecture (CUDA) based support vector machine (SVM) package. It is designed to offer an end-user a fully functional and user friendly SVM tool which utilizes the power of GPUs. The core package includes an efficient cross validation tool, a fast training tool and a predicting tool. In this article, we first introduce the background theory of how we build our parallel SVM solver using CUDA programming model. Then we compare our GPUSVM package with the popular state of the art Libsvm package on several well known datasets. The preliminary results have shown one to two orders of magnitude speed improvement in both training and predicting phases compared to Libsvm using our Tesla server.
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References in zbMATH (referenced in 2 articles , 1 standard article )
Showing results 1 to 2 of 2.
- Jiang, Mingfeng; Wang, Yaming; Xia, Ling; Liu, Feng; Jiang, Shanshan; Huang, Wenqing: The combination of self-organizing feature maps and support vector regression for solving the inverse ECG problem (2013)
- Li, Qi; Salman, Raied; Test, Erik: GPUSVM: a comprehensive CUDA based support vector machine package (2011)
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