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CUDA

Description

cuda website

The NVIDIA CUDA Toolkit provides a development environment for creating high performance GPU-accelerated applications. The toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler and a runtime library to deploy your application.

Environment Modules

Run module spider cuda to find out what environment modules are available for this application.

Environment Variables

  • HPC_CUDA_DIR - installation directory
  • HPC_CUDA_BIN - executable directory
  • HPC_CUDA_INC - includes directory
  • HPC_CUDA_LIB - library directory

Additional Usage Information

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. The cuda versions below are currently supported on hipergator.

Expand to view example of loading/using cuda. 
$ module spider cuda
-------------------------------------------------------------
cuda:
-------------------------------------------------------------
    Description:
    NVIDIA CUDA Toolkit

    Versions:
        cuda/10.0.130
        cuda/11.0.207
        cuda/11.1.0
        cuda/11.4.3
        cuda/11.6
        cuda/12.2.0
        cuda/12.2.2
        cuda/12.4.1

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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_61 GeForce GTX 1080Ti
SM_75 GeForce RTX 2080Ti
SM_80 DGX A100

Sample GPU Batch Job Scripts

See the Sample Job Scripts page for an example.

Categories

programming, library, graphics