Parallel Computing Experiences with CUDA
NVIDIA
Micro, IEEE In Micro, IEEE, Vol. 28, No. 4. (19 September 2008), pp. 13-27.
@article{garland2008parallel,
title={Parallel computing experiences with CUDA},
author={Garland, M. and Le Grand, S. and Nickolls, J. and Anderson, J. and Hardwick, J. and Morton, S. and Phillips, E. and Zhang, Y. and Volkov, V.},
journal={Micro, IEEE},
volume={28},
number={4},
pages={13–27},
issn={0272-1732},
year={2008},
publisher={IEEE}
}
The CUDA programming model provides a straightforward means of describing inherently parallel computations, and NVIDIA’s Tesla GPU architecture delivers high computational throughput on massively parallel problems. This article surveys experiences gained in applying CUDA to a diverse set of problems and the parallel speedups over sequential codes running on traditional CPU architectures attained by executing key computations on the GPU.
November 4, 2010 by hgpu
