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LOCATION:D220
DTSTART;TZID=America/Chicago:20181112T110000
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UID:submissions.supercomputing.org_SC18_sess172_ws_phpsc103@linklings.com
SUMMARY:Managing Python in HPC Environments
DESCRIPTION:Workshop\nParallel Application Frameworks, Reproducibility, Sc
 ientific Computing, Workshop Reg Pass\n\nManaging Python in HPC Environmen
 ts\n\nGall, Indiviglio\n\nPython has seen a rapid adoption in the weather 
 and climate modeling science communities.  This swift rise has taken HPC s
 ystem administrators by surprise, leading to inadequate support.  These tr
 ends, like those in other sciences, led to the development and widespread 
 adoption of user managed binary distributions.  An example being Anaconda 
 in 2012, which comes with security risks.  We present a system for mirrori
 ng Anaconda Python that embeds PyRats, a dependency analyzer and logger de
 scended from Blais’ Snakefood into the Anaconda installers.  We show that 
 Anaconda performance, reliability, security, and availability can be impro
 ved dramatically and enable timely integration into automated test environ
 ments.  The dependency logging yields insights into which packages users r
 ely on most.  It can help prioritize optimization efforts such as building
  packages for the CPU families used in a given HPC environment.  We also d
 iscuss related work, including a complimentary automated Python provisioni
 ng effort by Oak Ridge National Laboratory that they call PythonEnv-noaa.
URL:https://sc18.supercomputing.org/presentation/?id=ws_phpsc103&sess=sess
 172
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