Parallel Computing Experiences with CUDA
Michael Garland(Nvidia (United States)), Scott Le Grand(Nvidia (United Kingdom)), John Nickolls(Nvidia (United Kingdom)), Joshua A. Anderson(Iowa State University), Jim Hardwick(TechniScan (United States)), Scott Morton(Hess (United States)), Everett Phillips(University of California, Davis), Yao Zhang(University of California, Davis), В. М. Волков(Gangwon Provincial University)
Cited by 537
Abstract
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.
Related Papers
No related papers found
Powered by citation graph analysis