Multi-class Support Vector Machine Training and Classification Based on MPI-GPU Hybrid Parallel Architecture-Reference-Cited by-同舟云学术

Multi-class Support Vector Machine Training and Classification Based on MPI-GPU Hybrid Parallel Architecture

Published:2018-08-29 Issue: Volume: Page:179-188
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Elgarhy I.,Khaled H.,Gohary Rania El,Faheem H. M.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-99010-1_16

Reference16 articles.

1. NVIDIA Corporation: NVIDIA CUDA C Programming Guide (2010)

2. Sanders, J., Kandrot, E.: CUDA by Example: An Introduction to General-Purpose GPU Programming, 1st edn. Addison-Wesley Professional, Reading (2010)

3. Khaled, H., Faheem, H.M., El-Gohary, R.: Design and implementation of a hybrid MPI-CUDA model for the Smith–Waterman algorithm. Int. J. Data Min. Bioinform. 12(3), 313–327 (2015)

4. Aoyama, Y., Nakano, J., et al.: Rs/6000 sp: Practical MPI Programming. IBM Poughkeepsie, New York (1999)

5. Catanzaro, B., Sundaram, N., Keutzer, K.: Fast support vector machine training and classification on graphics processors. In: Proceedings of the 25th International Conference on Machine Learning, pp. 104–111 (2008)

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