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A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms

A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms

Huming Zhu, Pei Li, Peng Zhang, Zheng Luo
Copyright: © 2019 |Volume: 11 |Issue: 1 |Pages: 12
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781522564904|DOI: 10.4018/IJGHPC.2019010102
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MLA

Zhu, Huming, et al. "A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms." IJGHPC vol.11, no.1 2019: pp.17-28. http://doi.org/10.4018/IJGHPC.2019010102

APA

Zhu, H., Li, P., Zhang, P., & Luo, Z. (2019). A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms. International Journal of Grid and High Performance Computing (IJGHPC), 11(1), 17-28. http://doi.org/10.4018/IJGHPC.2019010102

Chicago

Zhu, Huming, et al. "A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms," International Journal of Grid and High Performance Computing (IJGHPC) 11, no.1: 17-28. http://doi.org/10.4018/IJGHPC.2019010102

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Abstract

A ranking support vector machine (RSVM) is a typical pairwise method of learning to rank, which is effective in ranking problems. However, the training speed of RSVMs are not satisfactory, especially when solving large-scale data ranking problems. Recent years, many-core processing units (graphics processing unit (GPU), Many Integrated Core (MIC)) and multi-core processing units have exhibited huge superiority in the parallel computing domain. With the support of hardware, parallel programming develops rapidly. Open Computing Language (OpenCL) and Open Multi-Processing (OpenMP) are two of popular parallel programming interfaces. The authors present two high-performance parallel implementations of RSVM, an OpenCL version implemented on multi-core and many-core platforms, and an OpenMP version implemented on multi-core platform. The experimental results show that the OpenCL version parallel RSVM achieved considerable speedup on Intel MIC 7110P, NVIDIA Tesla K20M and Intel Xeon E5-2692v2, and it also shows good portability.

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