Nvidia CUDA Toolkit

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.

Required Modules

For single task, non MPI programs

module load cuda/10.0.130 intel/2018.1.163

or

module load cuda/10.0.130  gcc/7.3.0

For MPI programs

module load cuda/10.0.130 intel/2018.1.163 openmpi/4.0.0

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

Sample GPU Batch Job Scripts

SLURM Job Scripts

See the Example_SLURM-GPU-Job-Scripts page for an example.