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

This complements 3de4a730 and fixes
<https://hpc-community.unige.ch/t/gpu010-cuda-singularity-cuda-runtime-error/306/3>.

p/pytorch/cuda_-_matrix_zeros.py

+#!/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)

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

+#!/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