Skip to main content

About Pyina

The pyina package provides several basic tools to make MPI-based parallel computing more accessable to the end user. The goal of pyina is to allow the user to extend their own code to MPI-based parallel computing with minimal refactoring.

The central element of pyina is the parallel map algorithm. pyina currently provides two strategies for executing the parallel-map, where a strategy is the algorithm for distributing the work list of jobs across the availble nodes. These strategies can be used “in-the-raw” (i.e. directly) to provide the map algorithm to a user’s own mpi-aware code. Further, in pyina.mpi pyina provides pipe and map implementations (known as “easy map”) that hide the MPI internals from the user. With the “easy map”, the user can launch their code in parallel batch mode – using standard Python and without ever having to write a line of MPI code.

There are several ways that a user would typically launch their code in parallel – directly with mpirun or mpiexec, or through the use of a scheduler such as torque or slurm. pyina encapsulates several of these “launchers”, and provides a common interface to the different methods of launching a MPI job.

pyina is part of pathos, a Python framework for heterogeneous computing. pyina is in active development, so any user feedback, bug reports, comments, or suggestions are highly appreciated. A list of issues is located at https://github.com/uqfoundation/pyina/issues, with a legacy list maintained at https://uqfoundation.github.io/project/pathos/query.

Major Features

pyina provides a highly configurable parallel map interface to running MPI jobs, with:

  • a map interface that extends the Python map standard

  • the ability to submit batch jobs to a selection of schedulers

  • the ability to customize node and process launch configurations

  • the ability to launch parallel MPI jobs with standard Python

  • ease in selecting different strategies for processing a work list

Current Release

The latest released version of pyina is available at:

https://pypi.org/project/pyina

pyina is distributed under a 3-clause BSD license.

Development Version

You can get the latest development version with all the shiny new features at:

https://github.com/uqfoundation

If you have a new contribution, please submit a pull request.

Installation

pyina can be installed with pip:

$ pip install pyina

A version of MPI must also be installed. Launchers in pyina that submit to a scheduler will throw errors if the underlying scheduler is not available, however a scheduler is not required for pyina to execute.

Requirements

pyina requires:

  • python (or pypy), >=3.9

  • setuptools, >=42

  • cython, >=0.29.30

  • numpy, >=1.0

  • mpi4py, >=1.3

  • dill, >=0.4.1

  • pox, >=0.3.7

  • pathos, >=0.3.5

More Information

Probably the best way to get started is to look at the documentation at http://pyina.rtfd.io. Also see https://github.com/uqfoundation/pyina/tree/master/examples and pyina.tests for a set of scripts that demonstrate the configuration and launching of mpi-based parallel jobs using the “easy map” interface. You can run the tests with python -m pyina.tests. A script is included for querying, setting up, and tearing down an MPI environment, see python -m pyina for more information. The source code is generally well documented, so further questions may be resolved by inspecting the code itself. Please feel free to submit a ticket on github, or ask a question on stackoverflow (@Mike McKerns). If you would like to share how you use pyina in your work, please send an email (to mmckerns at uqfoundation dot org).

Important classes and functions are found here:

  • pyina.mpi [the map API definition]

  • pyina.schedulers [all available schedulers]

  • pyina.launchers [all available launchers]

Mapping strategies are found here:

  • pyina.mpi_scatter [the scatter-gather strategy]

  • pyina.mpi_pool [the worker pool strategy]

pyina also provides a convience script that helps navigate the MPI environment. This script can be run from anywhere with:

$ mpi_world

If may also be convienent to set a shell alias for the launch of ‘raw’ mpi-python jobs. Set something like the following (for bash):

$ alias mpython1='mpiexec -np 1 `which python`'
$ alias mpython2='mpiexec -np 2 `which python`'
$ ...

Citation

If you use pyina to do research that leads to publication, we ask that you acknowledge use of pyina by citing the following in your publication:

M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
"Building a framework for predictive science", Proceedings of
the 10th Python in Science Conference, 2011;
http://arxiv.org/pdf/1202.1056

Michael McKerns and Michael Aivazis,
"pathos: a framework for heterogeneous computing", 2010- ;
https://uqfoundation.github.io/project/pathos

Please see https://uqfoundation.github.io/project/pathos or http://arxiv.org/pdf/1202.1056 for further information.

Release files for pyina 0.3.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyina 0.3.2
File Size Uploaded
pyina-0.3.2.tar.gz 133.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyina 0.3.2
File Interpreter ABI Platform
pyina-0.3.2-py3-none-any.whl Python 3 none any Details

Total release size: 179.6 kB

Release files / pyina-0.3.2.tar.gz

Download URL pyina-0.3.2.tar.gz
Size 133.4 kB
Tags Source
SHA-256 checksum
How to use checksums
5e83d5f8487f7062cb1d14322798183ec9ecfd713d16c75f5fec3868702f7a4f
BLAKE2b-256 checksum
How to use checksums
0bbc7268f727c0b56a340e670f0c9c0f26aca0a68f1dfb31f7e975b3b98a7ee2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.14.2

Release files / pyina-0.3.2-py3-none-any.whl

Download URL pyina-0.3.2-py3-none-any.whl
Size 46.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
6763b1b41d2c1dc1389cb0f577dd98e2b3a3e39e1ac6160a9445ee2834236af7
BLAKE2b-256 checksum
How to use checksums
43762459eab3dc3b5cf4cad72c62ff9b3c7bef00a0c9d571a736a8959032aae9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.14.2

Release history Release notifications | RSS feed

This release

0.3.2 This release

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.9

2 release files

0.2.8

2 release files

0.2.7

2 release files

0.2.6

3 release files

0.2.5

2 release files

0.2.4

2 release files

0.2.3

1 release file

0.2.2

1 release file

0.2.1

1 release file

0.2.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page