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Flows How-To

This is a list of Frequently Asked Questions about the AbiPy flows and the :ref:`abirun.py` script. Feel free to suggest new entries!

Important

The execution of the flows require the proper configuration of manager.yml and, optionally, scheduler.yml. Please consult the documentation at ....

Suggestions:

  • Start with the examples available in examples/flows before embarking on large scale calculations.
  • Make sure the Abinit executable compiled on the machine can be executed both on the frontend and the compute node (ask your sysadmin)
  • If you are running on clusters in which the architecture of the compute node is completely different from the one available on the frontend, use shell_runner
  • Use the debug command

Do not:

  • Change manually the input files and the submission scripts
  • Submit jobs manually when the scheduler is running
  • Use a too small delay for the scheduler

Contents

Get all the TaskManager options

The :ref:`abidoc.py` script provides three commands to get the documentation for the options supported in manager.yml and scheduler.yml.

Use:

abidoc.py manager

to document all the options supported by |TaskManager| and:

abidoc.py scheduler

for the scheduler options.

If your environment is properly configured, you should be able to get information about the Abinit version used by the AbiPy with:

abidoc.py abibuild

Abinit Build Information:
Abinit version: 8.7.2
MPI: True, MPI-IO: True, OpenMP: False
Netcdf: True

Use --verbose for additional info

Important

Netcdf support must be activated in Abinit as AbiPy might use these files to extract data and/or fix runtime errors.

At this point, you can try to run a small flow for testing purpose with:

abicheck.py --with-flow

Reduce the number of files produced by the Flow

When running many calculations, Use prtwf -1 to tell Abinit to produce the wavefunction file, only if SCF cycle didn't converged so that AbiPy can reuse the file to restart the calculation.

Note that it's possibile to use:

flow.use_smartio()

to activate this mode for all tasks that are not supposed to produce WFK files for their children.

Extend tasks/works with specialized code

Remember that pickle_ does not support classes defined inside scripts. If you need to subclass one of the AbiPy Tasks/Works/Flows, define the subclass in a separated python module and import the module inside your script.

Kill a scheduler running in background

Use the official API:

abirun.py FLOWDIR cancel

to cancel all jobs of the flow that are in queue and kill the scheduler.

Compare multiple output files

The :ref:`abicomp.py` script

Try to understand why a task failed

There are several reasons why a task could fail. Some of these reasons could be related to hardaware failure, disk quota, OS or resource manager errors. others are related to Abinit-specific errors.