Difference between revisions of "Nvidia CUDA Toolkit"
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Revision as of 14:01, 13 September 2021
Description
cuda website
CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA.
Environment Modules
Use the 'module avail' command after loading a cuda environment module to see the available module trees or see which compiler and openmpi modules require the cuda module to be loaded.
System Variables
- HPC_CUDA_DIR
- HPC_CUDA_BIN
- HPC_CUDA_INC
- HPC_CUDA_LIB
Program Development
Environment
For CUDA development please load the "cuda" module. Doing so will ensure that your environment is set up correctly for the use of the CUDA compiler, header files, and libraries. Currently cuda/9.2.88 and cuda/10.0.130 are the only versions supported on hipergator.
$ module spider cuda ------------------------------------------------------------- cuda: ------------------------------------------------------------- Description: NVIDIA CUDA Toolkit Versions: cuda/9.2.88 cuda/10.0.130 -------------------------------------------------------------------------------------------------------------------- For detailed information about a specific "cuda" module (including how to load the modules) use the module full name. For example: $ module spider cuda/10.0.130 -------------------------------------------------------------------------------------------------------------------- $ module load cuda/10.0.130 $ which nvcc /apps/compilers/cuda/10.0.130/bin/nvcc $ printenv | grep CUDA HPC_CUDA_LIB=/apps/compilers/cuda/10.0.130/lib64 HPC_CUDA_DIR=/apps/compilers/cuda/10.0.130 HPC_CUDA_BIN=/apps/compilers/cuda/10.0.130/bin HPC_CUDA_INC=/apps/compilers/cuda/10.0.130/include UFRC_FAMILY_CUDA_VERSION=10.0.130
Selecting CUDA Arch Flags
When compiling with NVCC, you need to specify the Nvidia architecture that the CUDA files will be compiled for. Please refer to GPU Feature List for CUDA naming scheme sm_xy where x denotes the GPU generation and y denotes the version. The table below lists the SM flags for the three types of GPUs on HiPerGator.
SM | Nvidia Cards |
---|---|
SM_37 | Tesla K80 |
SM_61 | GeForce GTX 1080Ti |
SM_75 | GeForce RTX 2080Ti |
SM_80 | DGX A100 |
Sample GPU Batch Job Scripts
SLURM Job Scripts
See the Example_SLURM-GPU-Job-Scripts page for an example.