Performing distributed AI on a dataset
Contents
Performing distributed AI on a dataset#
This page explains how to distribute azimuthal integration of a dataset.
You first have to create a configuration file which describes how the azimuthal integration should be performed.
Then, Integrator provides two commands: integrate-slurm
and integrate-mp
.
Both work the same way: with a configuration file.
Run distributed AI on the local machine#
The azimuthal integration can be distributed on a local powerful machine.
Modify the configuration file to set partition = local
:
[computations distribution]
partition = local
n_workers = 4
cores_per_worker = 4
Then run integrate-mp conf_file.conf
Run distributed AI using several powerful (GPU) machines#
Use the integrate-mp
command, using partition = gpu
or partition = p9gpu
.
Warning
in this case, n_workers
has a different meaning. It will actually spawn 8 * n_workers
(8 workers by SLURM job).
Run distributed AI using many CPU machines#
Use the integrate-slurm
command, with partition = nice
or partition = p9gpu
.
With this mode, you will likely have to use many workers to achieve decent speed (especially when using partition = nice
).