mpi4py 3.0.0

Python bindings for MPI

This package provides Python bindings for the Message Passing Interface (MPI) standard. It is implemented on top of the MPI-1/2/3 specification and exposes an API which grounds on the standard MPI-2 C++ bindings.

Features

This package supports:

• Convenient communication of any picklable Python object
  • point-to-point (send & receive)
  • collective (broadcast, scatter & gather, reductions)
• Fast communication of Python object exposing the Python buffer interface (NumPy arrays, builtin bytes/string/array objects)
  • point-to-point (blocking/nonbloking/persistent send & receive)
  • collective (broadcast, block/vector scatter & gather, reductions)
• Process groups and communication domains
  • Creation of new intra/inter communicators
  • Cartesian & graph topologies
• Parallel input/output:
  • read & write
  • blocking/nonbloking & collective/noncollective
  • individual/shared file pointers & explicit offset
• Dynamic process management
  • spawn & spawn multiple
  • accept/connect
  • name publishing & lookup
• One-sided operations
  • remote memory access (put, get, accumulate)
  • passive target syncronization (start/complete & post/wait)
  • active target syncronization (lock & unlock)

Install

Once you have a working MPI implementation and the mpicc compiler wrapper is on your search path, you can install this package

• using pip:

  $ pip install mpi4py
  

• using easy_install (deprecated):

  $ easy_install mpi4py
  

You can also install the in-development version of mpi4py

• using pip:

  $ pip install git+https://bitbucket.org/mpi4py/mpi4py
  

  or:

  $ pip install https://bitbucket.org/mpi4py/mpi4py/get/master.tar.gz
  

• using easy_install (deprecated):

  $ easy_install git+https://bitbucket.org/mpi4py/mpi4py
  

  or:

  $ easy_install https://bitbucket.org/mpi4py/mpi4py/get/master.tar.gz
  

You can also install it directly on Fedora (as well as RHEL and their derivatives using the EPEL software repository)

• using dnf and the mpich package on x86_64:

  $ dnf install mpi4py-mpich
  

• using dnf and the openmpi package on x86_64:

  $ dnf install mpi4py-openmpi
  

Please remember to load the correct module for your choosen MPI environment

• for mpich package on x86_64 do:

  $ module load mpi/mpich-x86_64
  $ python -c "import mpi4py"
  

• for openmpi package on x86_64 do:

  $ module load mpi/openmpi-x86_64
  $ python -c "import mpi4py"
  

Citations

If MPI for Python been significant to a project that leads to an academic publication, please acknowledge that fact by citing the project.

• L. Dalcin, P. Kler, R. Paz, and A. Cosimo, Parallel Distributed Computing using Python, Advances in Water Resources, 34(9):1124-1139, 2011. http://dx.doi.org/10.1016/j.advwatres.2011.04.013
• L. Dalcin, R. Paz, M. Storti, and J. D’Elia, MPI for Python: performance improvements and MPI-2 extensions, Journal of Parallel and Distributed Computing, 68(5):655-662, 2008. http://dx.doi.org/10.1016/j.jpdc.2007.09.005
• L. Dalcin, R. Paz, and M. Storti, MPI for Python, Journal of Parallel and Distributed Computing, 65(9):1108-1115, 2005. http://dx.doi.org/10.1016/j.jpdc.2005.03.010