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TensorFlow#

TensorFlow is a free and open-source software library for machine learning and artificial intelligence.

TensorFlow at NHPCC#

There are three ways to run TensorFlow on Panthera cluster:

  • Interactive mode
  • Using subtf command
  • Using OnDemand web portal

Interactive mode#

First, create an interactive job to connect to one of the compute nodes:

u111112@login1:~/wrkdir> srun -n 4 --mem=1G -p short -t 10 --pty /bin/bash
srun: job 57293 queued and waiting for resources
srun: job 57293 has been allocated resources
u111112@cn-12-1:~/wrkdir>

Then, you have to load the TensorFlow module:

u111112@cn-12-1:~/wrkdir> ml TensorFlow

Tip

In order to see all TensorFlow versions installed on Panthera you can type TensorFlow and press the Tab key twice. For more information on how to use modules, please visit this page.

Finally, you can use your software:

u111112@cn-12-1:~/wrkdir> template ...

Using subtf command#

This is the fast and easiest method most users prefer to load and run TensorFlow on the cluster. Simply on login node press subtf command without any options to see it's help:

u111112@login1:~/wrkdir> subtf
Create and submit job for TensorFlow

Usage: subtf <INPUT> [OPTION]

        -n  <nt:nc>       Number of Tasks:Number of cpus per task.
        -m  <mem>         Memory required for job (GB). Default: 4
        -p  <part>        Partition name to submit the job. (use 'sinfo')
        -v  <ver>         Software version.             Default: 2.14
                          Available: 1.14-Py3.7.4, 2.14-Py3.10.9, 2.15-Py3.11.7
        -g  <gpu>         Number of GPU Device.         Default: 0
        -o  <opt>         Options for input file.
        -j  <jobname>     a name for the job allocation Default: name of input file.
        -l  <disk>        Disk space required for scratch (GB). Run on local hard disk.
        -t  <time>        run time of the job. Valid format: M, H:M:S, D-H, D-H:M
        -so <sopt>        Additional slurm options if needed.
        -u                Unbuffered print messages.
        -no               Only write job file.
        -h | --help       Print this message and exit.

 Example:   subtf run.py -n 2 -m 4 -t 2-0 -o '-c config/gran_DD.yaml'

Using OnDemand web portal#

Sometimes you need to take a quick look at your project to make a change or have a graphical view of that and you are running out of time or even do not have an access on your personal pc at the moment. We have prepared an option for you to launch your software in graphical mode and watch your changes quickly.

Warning

We strongly recommend you, not to use this method all the way using Panthera. Having a graphical access to the cluster should be done just in case of emergency or special use cases.

Follow these instructions

  • Go to Interactive Apps > ML/AI

Interactive Apps > ML/AI


  • Fill out the form according to your needs:

form

  • Wait until your session is being ready and now press on Connect to Jupyter :


PyTorch card info and adjustment

  • After a few seconds, A fresh notebook project will be opened. Now write and run your code:


alt

Tip

for more information about using OnDemand portal please visit this page.