pPython for Parallel Python Programming
pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics (PGAS) on top of a simple file-based messaging library (PythonMPI) in pure Python. The core data structure in pPython is...
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| Veröffentlicht in: | arXiv.org 2022-08 |
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| creator | Byun, Chansup Arcand, William Bestor, David Bergeron, Bill Gadepally, Vijay Houle, Michael Hubbell, Matthew Hayden Jananthan Jones, Michael Keville, Kurt Klein, Anna Michaleas, Peter Milechin, Lauren Morales, Guillermo Mullen, Julie Prout, Andrew Reuther, Albert Rosa, Antonio Samsi, Siddharth Yee, Charles Kepner, Jeremy |
| description | pPython seeks to provide a parallel capability that provides good speed-up without sacrificing the ease of programming in Python by implementing partitioned global array semantics (PGAS) on top of a simple file-based messaging library (PythonMPI) in pure Python. The core data structure in pPython is a distributed numerical array whose distribution onto multiple processors is specified with a map construct. Communication operations between distributed arrays are abstracted away from the user and pPython transparently supports redistribution between any block-cyclic-overlapped distributions in up to four dimensions. pPython follows a SPMD (single program multiple data) model of computation. pPython runs on any combination of heterogeneous systems that support Python, including Windows, Linux, and MacOS operating systems. In addition to running transparently on single-node (e.g., a laptop), pPython provides a scheduler interface, so that pPython can be executed in a massively parallel computing environment. The initial implementation uses the Slurm scheduler. Performance of pPython on the HPC Challenge benchmark suite demonstrates both ease of programming and scalability. |
| doi_str_mv | 10.48550/arxiv.2208.14908 |
| format | Article |
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| subjects | Computer Science - Distributed, Parallel, and Cluster Computing Data structures Programming languages Python Semantics |
| title | pPython for Parallel Python Programming |
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