Difference between revisions of "Applications/Cuda"
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==Application Details== | ==Application Details== | ||
| − | * Description: CUDA is NVIDIA’s parallel computing architecture that enables dramatic increases in computing performance by harnessing the power of the GPU ( | + | * Description: CUDA is NVIDIA’s parallel computing architecture that enables dramatic increases in computing performance by harnessing the power of the GPU (Graphics Processing Unit). |
| − | * Version: | + | * Version: 9.0.176,10.1.168 and 11.5.0 ('''preferred''') |
| − | * Modules: cuda/ | + | * Modules: cuda/9.0.176, and cuda/10.1.168 and cuda/11.5.0 |
| − | * Licence: Free, but owned by NVidia | + | * Licence: Free to download, but owned by NVidia |
| + | |||
| + | '''Note''' : Version 8.0.61 is designated for retirement | ||
==Usage Examples== | ==Usage Examples== | ||
| + | {| | ||
| + | |style="width:5%; border-width: 0" | [[File:icon_tick.png]] | ||
| + | |style="width:95%; border-width: 0" | All NVIDIA CUDA® modules have the Deep Neural Network library (cuDNN) included. It is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK. | ||
| + | |- | ||
| + | |} | ||
| + | |||
| − | + | ===Interactive Session=== | |
| + | Running a CUDA-based program on a GPU node in an interactive session: | ||
<pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;"> | <pre style="background-color: black; color: white; border: 2px solid black; font-family: monospace, sans-serif;"> | ||
| − | [username@ | + | [username@login01 ~]$ interactive -pgpu |
| − | [username@ | + | salloc: Granted job allocation 1014031 |
| + | Job ID 1014031 connecting to gpu03, please wait... | ||
| + | Last login: Fri Mar 16 10:05:54 2018 from gpu03 | ||
| + | |||
| + | [username@gpu03 ~]$ module add cuda/11.5.0 | ||
| + | [username@gpu03 ~]$ ./gpuTEST | ||
| + | |||
| + | </pre> | ||
| + | |||
| + | ===Batch Job=== | ||
| + | |||
| + | Running a CUDA-based program on a GPU node as a batch script below: | ||
| + | |||
| + | <pre style="font-family: monospace, sans-serif;"> | ||
| + | #!/bin/bash | ||
| + | #SBATCH -J gpu-cuda | ||
| + | #SBATCH -N 1 | ||
| + | #SBATCH --ntasks-per-node 1 | ||
| + | #SBATCH -D /home/user/ | ||
| + | #SBATCH -o %N.%j.%a.out | ||
| + | #SBATCH -e %N.%j.%a.err | ||
| + | #SBATCH -p gpu | ||
| + | #SBATCH --exclusive | ||
| + | |||
| + | module load cuda/11.0.5 | ||
| + | |||
| + | /home/user/gpu_program | ||
</pre> | </pre> | ||
| − | == | + | ==Next Steps== |
| + | |||
| + | * [[Programming/Cuda|CUDA Programming Support]] | ||
| + | * [https://developer.nvidia.com/accelerated-computing https://developer.nvidia.com/accelerated-computing] | ||
| − | + | {{Modulepagenav}} | |
Latest revision as of 14:25, 17 November 2022
Application Details
- Description: CUDA is NVIDIA’s parallel computing architecture that enables dramatic increases in computing performance by harnessing the power of the GPU (Graphics Processing Unit).
- Version: 9.0.176,10.1.168 and 11.5.0 (preferred)
- Modules: cuda/9.0.176, and cuda/10.1.168 and cuda/11.5.0
- Licence: Free to download, but owned by NVidia
Note : Version 8.0.61 is designated for retirement
Usage Examples
|
All NVIDIA CUDA® modules have the Deep Neural Network library (cuDNN) included. It is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK. |
Interactive Session
Running a CUDA-based program on a GPU node in an interactive session:
[username@login01 ~]$ interactive -pgpu salloc: Granted job allocation 1014031 Job ID 1014031 connecting to gpu03, please wait... Last login: Fri Mar 16 10:05:54 2018 from gpu03 [username@gpu03 ~]$ module add cuda/11.5.0 [username@gpu03 ~]$ ./gpuTEST
Batch Job
Running a CUDA-based program on a GPU node as a batch script below:
#!/bin/bash #SBATCH -J gpu-cuda #SBATCH -N 1 #SBATCH --ntasks-per-node 1 #SBATCH -D /home/user/ #SBATCH -o %N.%j.%a.out #SBATCH -e %N.%j.%a.err #SBATCH -p gpu #SBATCH --exclusive module load cuda/11.0.5 /home/user/gpu_program