TensorFlow

ls /cvmfs/singularity.metacentrum.cz/NGC/    # Singularity image
module avail tensorflow/                     # as a module

TensorFlow is an open source software library for numerical computation using data flow graphs.

A data flow graph, also known as a data flow diagram (DFD), is a graphical representation of the flow of data within a system or process. It is a visual tool used for modeling and understanding how data moves through various components or stages in a system.

Flexible architecture of TensorFlow allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Usage

Singularity image

Newer versions of TensorFlow are available solely as Singularity images optimized for usage with NVidia GPUs (NVidia GPU Cloud, NGC).

The NGC packages are placed in the directory /cvmfs/singularity.metacentrum.cz; you have to list the directory first to see its contents:

ls /cvmfs/singularity.metacentrum.cz

To use a selected version of TensorFlow image, run the image within interactive job as:

qsub -I -l select=1:mem=16gb:scratch_local=10gb:ngpus=1:gpu_cap=cuda60:cuda_version=11.0 -l walltime=4:00:00
singularity shell --nv /cvmfs/singularity.metacentrum.cz/NGC/TensorFlow\:21.03-tf2-py3.SIF

/* More about Nvidia GPU cloud usage can be found at NVidia deep learning frameworks wiki page. */

Module

Unless you have a specific reason, we encourage users to use TensorFlow in a container instead of module.

Once you add the module that best suits your needs, the use is as simple as running python and importing the tensorflow module:

python
>>> import tensorflow as tf
>>> (etc.)

If you are using tensorflow-2.0.0-gpu-python3 and receive a message "Illegal instruction", ask for GPU cards supporting avx512 instructions: `PBS -l select=...:cpu_flag=avx512dq`