TensorFlow - Office of Research

QuickStart TensorFlow

Tensorflow is a symbolic math library based on dataflow and differentiable programming.

Use Global Protect VPN: Whether on or Off-Campus

In the top menu bar access (globe icon).

Be sure vpn-groups selected when you connect.
Start an SSH Session

SSH your_netid@hpc.kennesaw.edu
To Test or Develop, Reserve a Node (for non-gpu)

$ qsub -I -q batch -l nodes=1:ppn=24,walltime=1:00:00
To Test or Develop, Reserve a Node (gpu)

$ qsub -I -q gpuq -l nodes=1:ppn=24:gpus=2,walltime=1:00:00
Due to the Variety of Ways TensorFlow is Used, It is Now Advised to Build Your Own Python Virtual Environment to Access a Recent Copy of TensorFlow

You will want to utilize the Anaconda module to .

From your Conda environment, you can have access to TensorFlow with GPU support that should work without a GPU.

Once created, to use the environment in an interactive session or from within a PBS job submission script, you will need to load Anaconda and activate your new TensorFlow-aware conda environment.

Step by step instructions have been prepared by the KSU Sysadmins on the KSU HPCdocs wiki: .
Write a Job Submission Script (run_tf2.pbs)

Check the at hpcdocs.
Submit Your Job to the Scheduler

Use the qsub sumission example at the bottom of the .
TensorFlow Tutorials and Guides

Visit .