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Conda

Another example of conda environment setup.

Login on the submit node

Login on the cluster submission node, check the page How to Access for more information:

$ ssh -l <username> hpc7.ncg.ingrid.pt
[username@hpc7 ~]$ _
Prepare a conda virtual environment

The default python version for CentOS 7.x is 2.7.5 which is not suitable for many applications. So, we will create a python virtual environment:

[username@hpc7 ~]$ conda create -n myconda python=3.6
[username@hpc7 ~]$ conda activate myconda

On the first command, where we create the conda virtual environment, you can include a list of applications to include on your environmnet, for example:

[username@hpc7 ~]$ conda create -n myconda python=3.6 ipython-notebook numpy=1.6
Manage the conda virtual environment

It is possible to include additional packages to your conda environment, for example:

[username@hpc7 ~]$ conda activate myconda
[username@hpc7 ~]$ conda install numpy

You can update your software bandle on the conda virtual environment with the command:

[username@hpc7 ~]$ conda update [scipy ...]

or remove a specific application:

[username@hpc7 ~]$ conda uninstall tensorflow-gpu

Check the conda help for more information:

[username@hpc7 ~]$ conda help
[username@hpc7 ~]$ conda install --help
Manage the conda packages list with pip

It is possible to complemment the conda virtual environment packages list with pip. For example:

[username@hpc7 ~]$ conda activate myconda
[username@hpc7 ~]$ pip install --upgrade pip
[username@hpc7 ~]$ pip install --upgrade setuptools
[username@hpc7 ~]$ pip install tensorflow-gpu
[username@hpc7 ~]$ pip install keras
Manage packages versions

If the applications available on conda virtual environment do not match your version requirements you may need to use packages from pip repostory; check the availability of conda search and pip search command line interfaces.

As an example we have the tensorflow-gpu package, when used with keras, the conda repository downgrades *tensorflow-gpu to version 1.15, but you most likely will prefer version 2.0. The pip repository has the right combination of tensorflow-gpu and keras packages.

We advise the user to install a package from only one repository in order to guarantee perfect behaviour.

Load conda environment on a batch job

Create a submit script:

[username@hpc7 ~]$ cat submit.sh 

#!/bin/bash

# Set parallell environment "mp", and excute in 4 cores on same node
#$ -pe mp 4

# Queue selection 
#$ -q hpc

# check python version
python --version

# Load conda environment
conda activate myconda

# recheck python version
python --version

# your job payload
#....

Submit:

[username@hpc7 ~]$ qsub submit.sh
Your job 2037792 ("submit.sh") has been submitted

After completion:

[username@hpc7 ~]$ ls -l
-rwxr-----+ 1 username hpc    668 Jan  7 12:19 submit.sh
-rw-r-----+ 1 username hpc     44 Jan  7 12:18 submit.sh.e2037792
-rw-r-----+ 1 username hpc      0 Jan  7 12:18 submit.sh.o2037792

[username@hpc7 ~]$ cat submit.sh.e2037792
Python 2.7.5
Python 3.6.9 :: Anaconda, Inc.
Some References