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 clusterpartition, please login to
- a GPU A100 login node, like bgnlogin.nhr.zib.de.
- see also QuickstartGPU 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.
| Codeblock |
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| language | text |
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| title | Plain OpenMP for GPUCUDA and with cublas |
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bgnlogin1 $ module load nvhpc-hpcx/23.1
bgnlogin1 $ module list
Currently Loaded Modulefiles: ... 4) hpcx 5) nvhpc-hpcx/23.1
bgnlogin1 $ nvc -mpcuda -target=gpu openmp_gpugpu=cc8.0 cuda.c -o cuda.bin
bgnlogin1 $ nvc -cuda -gpu=cc8.0 -cudalib=cublas cuda_cublas.c -o openmpcuda_gpucublas.bin |
CUDA can be used in combination with MPI.
| Codeblock |
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| language | text |
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| title | CUDA with MPI + OpenMP for GPU |
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bgnlogin1 $ module load nvhpc-hpcx/23.1
bgnlogin1 $ module list
Currently Loaded Modulefiles: ... 4) hpcx 5) nvhpc-hpcx/23.1
bgnlogin1 $ mpicc -mp -target=gpu mpi_openmp_gpumpicc -cuda -gpu=cc8.0 -cudalib=cublas mpi_cuda_cublas.c -o mpi_openmpcuda_gpucublas.bin |
Code execution
All available slurm partitions for the A100 GPU partition you can see on Slurm partitions GPU A100.
| Codeblock |
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| language | text |
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| title | Job script for plain OpenMPCUDA |
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#!/bin/bash
#SBATCH --partition=gpu-a100:shared
#SBATCH --gres=gpu:41
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=72
./cuda.bin
./openmpcuda_gpucublas.bin
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| Codeblock |
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| language | text |
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| title | Job script for CUDA with MPI + OpenMP |
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#!/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_openmpcuda_gpucublas.bin
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