/// Parallel Panorama ///

June 19, 2008

CUDA vs. FPGAs for high-performance computing

Filed under: GPU — Tags: — llpanorama @ 5:50 am

A column by Kevin Morris, editor of the FPGA Journal, discusses the new Nvidia GPU offerings.  Here’s my response about why GPUs will kill-off the use of field-programmable gate arrays (FPGAs) as accelerators in high-performance computing systems.

3 Comments »

  1. Kolonel:

    In the version of CUDA I am using (1.1), there is no way I can find to start multiple grids that run in parallel. Each grid has to complete before another one can start. So you would probably need to run five grids sequentially to multiply your ten matrices.

    I think this is a limitation of the CUDA programming model and not the GPU itself. Perhaps later versions of CUDA will lift this restriction.

    Comment by llpanorama — September 6, 2008 @ 7:23 am

  2. Hi,
    Thanks for sharing these useful information, I learn too much from your posts about CUDA.
    I have a question and I will appreciate if you could let me know your opinion: Is that possible to run 2 or more Grids concurrently in parallel? e.g. I have 10 matrices which I want to multiply them together, is that possible that I define 5 separate Grids and simultaneously multiply these matrices 2 by 2?
    Thanks for your attention.

    Comment by Kolonel — September 2, 2008 @ 8:30 pm

  3. It sure would be a interesting war, I have to vote for FPGA :-)

    Comment by FPGA Blogs — June 20, 2008 @ 1:43 am


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