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  1. Proceedings of the 6th Workshop on Python for High-Performance and Scientific Computing (PyHPC '16)
  2. Performance of MPI codes written in Python with NumPy and mpi4py
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Dynamic provisioning and execution of HPC workflows using Python
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PALLADIO: a parallel framework for robust variable selection in high-dimensional data
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Performance of MPI codes written in Python with NumPy and mpi4py
Boosting Python performance on Intel processors: a case study of optimizing music recognition
ePython: an implementation of Python for the many-core Epiphany coprocessor
Devito: towards a generic finite difference DSL using symbolic Python
Mrs: high performance mapreduce for iterative and asynchronous algorithms in Python

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Performance of MPI codes written in Python with NumPy and mpi4py

Content Provider ACM Digital Library
Author Smith, Ross
Abstract Python is an interpreted language that has become more commonly used within HPC applications. Python benefits from the ability to write extension modules in C, which can further use optimized libraries that have been written in other compiled languages. For HPC users, two of the most common extensions are NumPy and mpi4py. It is possible to write a full computational kernel in a compiled language and then build that kernel into an extension module. However, this process requires not only the kernel be written in the compiled language, but also the interface between the kernel and Python be implemented. If possible, it would be preferable to achieve similar performance by writing the code directly in Python using readily available performant modules. In this work the performance differences between compiled codes and codes written using Python3 and commonly available modules, most notably NumPy and mpi4py, are investigated. Additionally, the performance of an open source Python stack is compared to the recently announced Intel Python3 distribution.
Starting Page 45
Ending Page 51
Page Count 7
ISBN 9781509052202
DOI 10.1109/PyHPC.2016.6
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-11-13
Access Restriction Subscribed
Subject Keyword Mpi Mpi4py Hpc Intel python Python
Content Type Text
Resource Type Article
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