Difference between revisions of "CUDA On The CS Linux Clients"
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==CUDA On The CS Linux Clients== | ==CUDA On The CS Linux Clients== | ||
| − | :[ | + | :[https://developer.nvidia.com/cuda-zone '''CUDA'''] is a parallel computing platform and application programming interface (API) model created by Nvidia. |
| − | :It will only run on our [ | + | :It will only run on our [[GPUs In The CS Linux Clients|CS Linux clients that include GPUs]]. |
| − | :Although the CS IT Support Group makes the CUDA software available on our GPU-enabled systems, we | + | :Although the CS IT Support Group makes the CUDA software available on our GPU-enabled systems, we do not use CUDA ourselves. We therefore do not have the experience necessary to provide instructions on how to use the CUDA toolchain and libraries. |
| − | :The CUDA tools should work as their standard documentation say they do. If for some reason they do not, please email [mailto:support@cs.jhu.edu support@cs.jhu.edu] and let us know as much information as possible, and we'll see if we can help correct the | + | :The CUDA tools should work as their standard documentation say they do. If for some reason they do not, please email [mailto:support@cs.jhu.edu support@cs.jhu.edu] and let us know as much information as possible, and we'll see if we can help correct the issue with our installation. |
:To learn how to use CUDA, we recommend consulting its online documentation or discussing its use with your instructor. | :To learn how to use CUDA, we recommend consulting its online documentation or discussing its use with your instructor. | ||
Revision as of 13:21, 2 January 2018
CUDA On The CS Linux Clients
- CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia.
- It will only run on our CS Linux clients that include GPUs.
- Although the CS IT Support Group makes the CUDA software available on our GPU-enabled systems, we do not use CUDA ourselves. We therefore do not have the experience necessary to provide instructions on how to use the CUDA toolchain and libraries.
- The CUDA tools should work as their standard documentation say they do. If for some reason they do not, please email support@cs.jhu.edu and let us know as much information as possible, and we'll see if we can help correct the issue with our installation.
- To learn how to use CUDA, we recommend consulting its online documentation or discussing its use with your instructor.