added tensorflow cuda example

97-frameworks-tensorflow-cuda/01-tensorflow-python-single-node.sh

+#!/bin/bash
+
+##############################################################################
+# User Request:
+#   - allocate single gpu node
+#	- run python script
+#
+# Provided Allocation:
+#   - 1 exclusive gpu node
+#   - 16 physical cores / 32 logical cores
+#   - 256 GB memory
+#
+# VSC policy:
+#   - '--nodes' flag set -> exclusive node allocation
+#   - '--ntasks-per-node' & '--ntasks' implicitly set to 16
+#   
+# Accounting:
+#   - 1x 16 core hours / hour
+##############################################################################
+
+#SBATCH --partition=zen2_0256_a40x2
+#SBATCH --qos=zen2_0256_a40x2
+#SBATCH --gres=gpu:2
+
+# optionally activate a conda or python environment
+module load miniconda3
+eval "$(conda shell.bash hook)"
+conda activate tensorflow-cuda
+
+# load matching cuda module
+module load cuda/11.8.0-gcc-12.2.0-knnuyxt
+
+# run python code
+python tensorflow-test.py

97-frameworks-tensorflow-cuda/environment.yaml

+name: tensorflow-cuda
+channels:
+  - conda-forge
+  - bioconda
+  - nvidia  
+  - defaults
+dependencies:
+  - python=3.11
+  - tensorflow=2.13.*=cuda118*
+  - keras
+  - nccl
+  - cudatoolkit=11.8*
+  - cudnn
+  - pip

97-frameworks-tensorflow-cuda/tensorflow-test.py

+import tensorflow as tf
+
+print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))
+print("Is built with CUDA: ", tf.test.is_built_with_cuda())
+print("Build Info: ", tf.sysconfig.get_build_info())