On Fri, Nov 30, 2012 at 2:06 AM, kurisaki <
kurisaki.ncube.human.nagoya-u.ac.jp> wrote:
> Dear Amber developers and users,
>
> Thank you for kind support.
>
> I would resolve the following error by
> Adding $CUDA_HOME/* to $LD_LIBRARY_PATH.
>
> However, in the TEST step,
> There still error message,
> " cudaGetDeviceCount failed no CUDA-capable device is detected"
>
> I am most grateful if you give me an advice to treat it.
>
This is not actually an Amber problem. The CUDA API cannot find any GPU
accelerator, which means the driver may not be properly installed (or it
may not be the right version). If you haven't installed the CUDA SDK yet,
I would suggest doing that. The "nvidia-smi" program is helpful in
determining what GPUs are available (and their current load, if that model
supports those functions).
Good luck,
Jason
--
Jason M. Swails
Quantum Theory Project,
University of Florida
Ph.D. Candidate
352-392-4032
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Received on Fri Nov 30 2012 - 05:30:03 PST
