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|
Parsl - Parallel Scripting Library
##################################
Parsl extends parallelism in Python beyond a single computer.
You can use Parsl
`just like Python's parallel executors <userguide/workflows/workflow.html#parallel-workflows-with-loops>`_
but across *multiple cores and nodes*.
However, the real power of Parsl is in expressing multi-step workflows of functions.
Parsl lets you chain functions together and will launch each function as inputs and computing resources are available.
.. code-block:: python
import parsl
from parsl import python_app
# Start Parsl on a single computer
parsl.load()
# Make functions parallel by decorating them
@python_app
def f(x):
return x + 1
@python_app
def g(x, y):
return x + y
# These functions now return Futures, and can be chained
future = f(1)
assert future.result() == 2
# Functions run concurrently, can be chained
f_a, f_b = f(2), f(3)
future = g(f_a, f_b)
assert future.result() == 7
Start with the `configuration quickstart <quickstart.html#getting-started>`_ to learn how to tell Parsl how to use your computing resource,
see if `a template configuration for your supercomputer <userguide/configuration/examples.html>`_ is already available,
then explore the `parallel computing patterns <userguide/workflows/workflows.html>`_ to determine how to use parallelism best in your application.
Parsl is an open-source code, and available on GitHub: https://github.com/parsl/parsl/
Why use Parsl?
==============
Parsl is Python
---------------
*Everything about a Parsl program is written in Python.*
Parsl follows Python's native parallelization approach and functions,
how they combine into workflows, and where they run are all described in Python.
Parsl works everywhere
----------------------
*Parsl can run parallel functions on a laptop and the world's fastest supercomputers.*
Scaling from laptop to supercomputer is often as simple as changing the resource configuration.
Parsl is tested `on many of the top supercomputers <userguide/configuration/examples.html>`_.
Parsl is flexible
-----------------
..
Is this redundant with 'everywhere'?
*Parsl supports many kinds of applications.*
Functions can be pure Python or invoke external codes, be single- or multi-threaded or GPUs.
Parsl handles data
------------------
*Parsl has first-class support for workflows involving files.*
Data will be automatically moved between workers, even if they reside on different filesystems.
Parsl is fast
-------------
*Parsl was built for speed.*
Workflows can manage tens of thousands of parallel tasks and process thousands of tasks per second.
Parsl is a community
--------------------
*Parsl is part of a large, experienced community.*
The Parsl Project was launched by researchers with decades of experience in workflows
as part of a National Science Foundation project to create sustainable research software.
The Parsl team is guided by the community through its GitHub,
conversations on `Slack <https://join.slack.com/t/parsl-project/shared_invite/enQtMzg2MDAwNjg2ODY1LTUyYmViOTY1ZTU2ZDUwZTVmOWQ1M2IzZTE5MTM3YWZlM2RhM2IyZjk4ODgwNGRhOGE1MzJlNTYyYjNkYzIzZWE>`_,
Bi-Weekly developer calls,
and engagement with the `Workflows Community Initiative <https://workflows.community/>`_.
..
I was going to work in how we integrate with other tools, but that seemed too-detailed in this draft
Table of Contents
+++++++++++++++++
.. toctree::
:maxdepth: 2
quickstart
userguide/index
userguide/glossary
faq
reference
devguide/index
historical/index
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
|
