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High-Performance Astrophysical Simulations and Analysis with Python
Matthew Turk and Britton Smith
The usage of the high-level scripting language Python has enabled new mechanisms for data interrogation, discovery and visualization of scientific data. We present
yt
, an open source, community-developed astrophysical analysis and visualization toolkit for data generated by high-performance computing (HPC) simulations of astrophysical phenomena. Through a separation of responsibilities in the underlying Python code, yt allows data generated by incompatible, and sometimes even directly competing, astrophysical simulation platforms to be analyzed in a consistent manner, focusing on physically relevant quantities rather than quantities native to astrophysical simulation codes. We present on its mechanisms for data access, capabilities for MPI-parallel analysis, and its implementation as an
in situ
analysis and visualization tool.
PyHPC2011
Call for Papers
Program
Abstracts
Program Committee
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PyHPC2011-Program
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PyHPC2011-CfP
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SC11
Workshop Python for High Performance and Scientific Computing (SC11)
Submission page (EasyChair)
Birds of a Feather Python for High Performance Computing (SC11)
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