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DistArray

Think globally, act locally.

DistArray provides general multidimensional NumPy-like distributed arrays to Python. It intends to bring the strengths of NumPy to data-parallel high-performance computing. DistArray has a similar API to NumPy_.

DistArray is ready for real-world testing and deployment; however, the project is still evolving rapidly, and we appreciate continued input from the scientific-Python community.

DistArray is for users who

• know and love Python and NumPy,
• want to scale NumPy to larger distributed datasets,
• want to interactively play with distributed data but also
• want to run batch-oriented distributed programs;
• want an easier way to drive and coordinate existing MPI-based codes,
• have a lot of data that may already be distributed,
• want a global view ("think globally") with local control ("act locally"),
• need to tap into existing parallel libraries like Trilinos, PETSc, or Elemental,
• want the interactivity of IPython and the performance of MPI.

DistArray is designed to work with other packages that implement the Distributed Array Protocol_.

.. _Distributed Array Protocol: http://distributed-array-protocol.readthedocs.org .. _NumPy: http://www.numpy.org

Please see our documentation at readthedocs_ (or in the docs directory) for more, or ask us questions on our mailing list_. Pull requests gladly accepted.

.. _readthedocs: http://distarray.readthedocs.org .. _mailing list: https://groups.google.com/forum/#!forum/distarray