High-Performance Astrophysical Simulations and Analysis with Python
  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. 
Matthew J. Turk (1) and Britton D. Smith (2) ((1) Columbia University,   (2) Michigan State University)
astro-ph.IM astro-ph.CO