p/pytorch/cuda_9.2.148.1_-_matrix_zeros_-_singularity.sbatch: new

#!/usr/bin/env python

#

# Create a 10x10 matrix filled with zero via the CUDA device

#   <https://hpc-community.unige.ch/t/gpu010-cuda-singularity-cuda-runtime-error/306>

import torch

cuda = torch.device('cuda')

a = torch.zeros(10, device=cuda)

print(a)

#!/bin/sh

#

# <https://hpc-community.unige.ch/t/gpu010-cuda-singularity-cuda-runtime-error/306>

#SBATCH --partition=shared-gpu-EL7

#SBATCH --time=00:15:00

#SBATCH --gres=gpu:1

echo "I: full hostname: $(hostname -f)"

module load GCC/5.4.0-2.26

module load Singularity/2.4.5

VERSION_CUDA='9.2.148.1'

module load CUDA/${VERSION_CUDA}

# if you need to know the allocated CUDA device, you can obtain it here:

echo "I: CUDA_VISIBLE_DEVICES: ${CUDA_VISIBLE_DEVICES}"

echo "====="

srun singularity \

    exec \

    --bind $(readlink ${HOME}/scratch) \

    --nv \

    ${PWD}/pytorch.simg \

        python \

        ${PWD}/cuda_-_matrix_zeros.py