Parallel Computing Experiences with CUDA

@article{Garland2008ParallelCE,
  title={Parallel Computing Experiences with CUDA},
  author={Michael Garland and Scott Le Grand and John Nickolls and John Eric Anderson and Jim Hardwick and Scott Morton and Everett H. Phillips and Yao Zhang and Vasily Volkov},
  journal={IEEE Micro},
  year={2008},
  volume={28}
}
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. 

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References

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SHOWING 1-10 OF 20 REFERENCES

Traves- set, ‘‘General Purpose Molecular Dynamics Simulations Fully Implemented on Graphics Processing Units,’

J. A. Anderson, C. D. Lorenz
  • J. Computational Phys- ics,
  • 2008
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

A Multi-Grid Solver for the 2D Compressible Euler Equations on a GPU Cluster,’

E. H. Phillips
  • tech. report ECE-CE-2008-2, Computer Eng. Research Lab., Univ. of California,
  • 2008