CUDA (Compute Unified Device Architecture) is an interface to program Nvidia GPUs. It offers support to the languages such as C, C++, and Fortran.

To build and execute code on the GPU A100 partition, please login to

a GPU A100 login node, like bgnlogin.nhr.zib.de.
see also GPU A100 partition

Note, that codes written in the cross-industry standard language SYCL can be executed on Nvidia (and AMD) hardware.

Code build

For code generation we recommend the software package NVIDIA hpcx which is a combination of compiler and powerful libraries, like e.g. CUDA, cublas, and MPI.

CUDA and with cublas

bgnlogin1 $ module load nvhpc-hpcx/23.1
bgnlogin1 $ module list
Currently Loaded Modulefiles: ... 4) hpcx   5) nvhpc-hpcx/23.1
bgnlogin1 $ nvc -cuda -gpu=cc8.0 cuda.c -o cuda.bin
bgnlogin1 $ nvc -cuda -gpu=cc8.0 -cudalib=cublas cuda_cublas.c -o cuda_cublas.bin

CUDA can be used in combination with MPI.

CUDA with MPI

bgnlogin1 $ module load nvhpc-hpcx/23.1
bgnlogin1 $ mpicc -cuda -gpu=cc8.0 -cudalib=cublas mpi_cuda_cublas.c -o mpi_cuda_cublas.bin

Code execution

All available slurm partitions for the A100 GPU partition you can see on Slurm partition GPU A100.

Job script for CUDA

#!/bin/bash
#SBATCH --partition=gpu-a100:shared
#SBATCH --gres=gpu:1
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=72

./cuda.bin
./cuda_cublas.bin

Job script for CUDA with MPI

#!/bin/bash
#SBATCH --partition=gpu-a100
#SBATCH --gres=gpu:4
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=72

module load nvhpc-hpcx/23.1
mpirun --np 8 --map-by ppr:2:socket:pe=1 ./mpi_cuda_cublas.bin