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KSU Kennesaw Campus, Kennesaw Hall building - A-Z Index
QuickStart TensorFlow
Tensorflow is a symbolic math library based on dataflow and differentiable programming.
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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.
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Start an SSH Session
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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 create a Conda environment.
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: TensorFlow Example.
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Write a Job Submission Script (run_tf2.pbs)
Check the PBS file example at hpcdocs. -
Submit Your Job to the Scheduler
Use the qsub sumission example at the bottom of the PBS file example.
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TensorFlow Tutorials and Guides
Visit TensorFlow Tutorials.
