In this example we see how to run the GPUBench MATLAB program on GPU. Requires the MATLAB Parallel Computing Toolbox and a GPU with CUDA Compute Capability.

Script slurm-matlab-gpu-bench.sh:

slurm-matlab-gpu-bench.sh

#!/bin/bash
#SBATCH --job-name=GPUBench
#SBATCH --output=%x.o%j
#SBATCH --error=%x.e%j
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --gres=gpu:1
#SBATCH --partition=gpu
#SBATCH --qos=gpu
#SBATCH --mem=8G
#SBATCH --time=0-00:30:00
#SBATCH --account=<account>
 
module load matlab/R2017a
 
cd 'GPUBench_v1.10'
 
matlab -nodisplay -nosplash -r "T=gpuBench;quit"

Submitting slurm-matlab-gpu-bench.sh:

sbatch slurm-matlab-gpu-bench.sh

In this example we see how to run two instances of the GPUBench MATLAB program on the same GPU. Requires the MATLAB Parallel Computing Toolbox and a GPU with CUDA Compute Capability.

Script slurm-matlab-multi-gpu-bench.sh:

slurm-matlab-multi-gpu-bench.sh

#!/bin/sh
#SBATCH --job-name=GPUBench
#SBATCH --output=%x.o%j
#SBATCH --error=%x.e%j
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --gres=gpu:1
#SBATCH --partition=gpu
#SBATCH --qos=gpu
#SBATCH --mem=8G
#SBATCH --time=0-00:30:00
#SBATCH --account=<account>
 
module load matlab/R2017a
 
cd 'GPUBench_v1.10'
 
pids=""
 
for i in $(seq 0 1); do
  matlab -nodisplay -nosplash -r "T=gpuBench;quit" \
  1>"$SLURM_SUBMIT_DIR/${SLURM_JOB_NAME}.o${SLURM_JOB_ID}.${i}" \
  2>"$SLURM_SUBMIT_DIR/${SLURM_JOB_NAME}.e${SLURM_JOB_ID}.${i}" &
  pids="${pids:+$pids }$!"
done
 
echo "Waiting PID(s): $pids"
 
wait $pids

Submitting slurm-matlab-multi-gpu-bench.sh:

sbatch slurm-matlab-multi-gpu-bench.sh

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