- Volume 24 Issue 5
DOI QR Code
Introduction to general purpose GPU computing
GPU를 이용한 범용 계산의 소개
- Yu, Donghyeon (Department of Statistics, Seoul National University) ;
- Lim, Johan (Department of Statistics, Seoul National University)
- Received : 2013.07.09
- Accepted : 2013.09.06
- Published : 2013.09.30
Recent advances in computer technology introduce massive data and their analysis becomes important. The high performance computing is one of the most essential part in analysis of massive data. In this paper, we review the general purpose of the graphics processing unit and its application to parallel computing, which has been of great interest in statistics communities.
- Jacob, P., Robert, C. P. and Smith, M.H. (2011). Using parallel computation to improve independent Metropolis-Hastings based estimation. Journal of Computational and Graphical Statistics, 20, 616-635. https://doi.org/10.1198/jcgs.2011.10167
- Jung, Y. (2011). CUDA parallel programming, Freelec, Bucheon.
- Murray, L. (2012). GPU acceleration of the particle filter: The Metropolis resampler. http://arxiv.org/ abs/1202.6163.
- Sanders, J. and Kandrot, E. (2011). CUDA by example: An Introduction to general-purpose GPU programming, translated by Park, C., Bjpublic, Seoul.
- Suchard, M., Wang, Q., Chan, C., Frelinger, J., Cron, A. and West, M. (2010). Understanding GPU programming for statistical computation: Studies in massively parallel massive mixture. Journal of Computational and Graphical Statistics, 19, 419-438. https://doi.org/10.1198/jcgs.2010.10016
- Yu, D., Won, J-H., Lee, T., Lim, J. and Yoon, S-R. (2013). High-dimensional fused lasso regression using majorization-minimization and parallel processing. http://arxiv.org/abs/1306.1970.
- Zhou, H., Lange, K. and Suchard, M.A. (2010). Graphics processing units and high-dimensional optimization. Statistical Science, 25, 311-324. https://doi.org/10.1214/10-STS336
- BCDR algorithm for network estimation based on pseudo-likelihood with parallelization using GPU vol.27, pp.2, 2016, https://doi.org/10.7465/jkdi.2016.27.2.381