.. _sphx_glr_auto_examples_07_parallel:

7. Running a whole cohort
=========================

**Background.** A real study has tens to hundreds of subjects. Running
them is a scheduling question, not a scientific one: the backend and
run policy change speed and failure handling, never the habitat labels.

**Purpose.** Run the same study on the serial and process backends and
check the labels match; see what happens when one subject fails
(``on_subject_failure``), resume from checkpoints, set a per-subject
timeout, cap workers to the GPUs, and learn when parallel is actually
worth it (on a tiny cohort serial can be faster because Windows spawn
start-up dominates).

:doc:`/auto_examples/07_parallel/plot_01_backends`


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  <div id='sg-tag-list' class='sphx-glr-tag-list'></div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Background. Once a study is declared, HABIT still has to run it on every subject. This page is about that scheduling layer. Switching the backend or RunPolicy changes speed and how failures are handled; it does not change the science, so the habitat labels must come out identical.">

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  .. image:: /auto_examples/07_parallel/images/thumb/sphx_glr_plot_01_backends_thumb.png
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  :doc:`/auto_examples/07_parallel/plot_01_backends`

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      <div class="sphx-glr-thumbnail-title">Running the same study on each backend</div>
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.. toctree::
   :hidden:

   /auto_examples/07_parallel/plot_01_backends