CUDA: Scalable parallel programming for high-performance scientific computing

@article{Luebke2008CUDASP,
  title={CUDA: Scalable parallel programming for high-performance scientific computing},
  author={David P. Luebke},
  journal={2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
  year={2008},
  pages={836-838}
}
Graphics processing units (GPUs) originally designed for computer video cards have emerged as the most powerful chip in a high-performance workstation. Unlike multicore CPU architectures, which currently ship with two or four cores, GPU architectures are "manycore" with hundreds of cores capable of running thousands of threads in parallel. NVIDIA's CUDA is a co-evolved hardware-software architecture that enables high-performance computing developers to harness the tremendous computational power… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 10 REFERENCES

Nonrigid multi-modal registration on the GPU

C. Vetter, C. Guetter, C. Xu, R. Westermann
  • Medical Imaging 2007: Image Processing, SPIE, vol. 6512, Mar 2007.
  • 2007
VIEW 1 EXCERPT

Fast DDR Generation Based on GPU

J. Gu, L. Gu
  • Int’l Journal of Computer Assisted Radiology and Surgery, Jun 2006.
  • 2006
VIEW 1 EXCERPT