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Using GPUs and CUDA drivers

If your job involves training a neural network on a large dataset, it is highly recommended that you request CUDA drivers to accelerate the training process. To access CUDA drivers, first load them in your SLURM script using:

module load cuda

Or, you may wish to use a specific CUDA version or add specific CUDA libraries, which you can load by using the following lines instead:

module load cuda11.6/blas/ # (1)!
module load cuda11.6/fft/ # (2)!
module load cuda11.6/toolkit/ # (3)!
  1. cuda11.6/blas/ loads the CUDA Basic Linear Algebra Subroutines library for matrix and vector operations
  2. cuda11.6/fft/ loads the CUDA Fast Fourier Transform library for signal and image processing
  3. cuda11.6/toolkit/ loads the entire CUDA toolkit necessary for using NVIDIA GPUs

To complete the neural network’s training process, you may require minimum specific hardware to ensure the job is handled properly. To do so, add the following line to your SLURM script

#SBATCH -C A100|V100

with the other #SBATCH lines to specify that this job must be run on an NVIDIA A100 or V100 GPU.