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DTSTAMP:20260704T204559Z
UID:23a1cc11-2b4b-4523-ba67-09bf9193cd4c
DTSTART:20170612T070000Z
DTEND:20170613T143000Z
DESCRIPTION:Python is being increasingly used in high-performance computing
  projects. It can be used either as a high-level interface to existing HPC
  applications and libraries\, as embedded interpreter\, or directly.\n\nTh
 is course combines lectures and hands-on session. We will show how Python 
 can be used on parallel architectures and how performance critical parts o
 f the kernel can be optimized using various tools.\n\nFor using Python pro
 ductively for parallel computing\, these topics will be covered:\n\nIntera
 ctive parallel programming with IPython\n	Profiling and optimization\n	Hig
 h-performance NumPy and SciPy\, numba\n	Distributed-memory parallel progra
 mming with Python and MPI\n	Bindings to other programming languages and HP
 C libraries\n	Interfaces to GPUs\nThis course is aimed at scientists who w
 ish to explore the productivity gains made possible by Python for HPC.\n\n
 Prerequisites: Experience with Python and NumPy\n\nApplication \nRegistrat
 ions are only considered until 31 May 2017 due to available space\, the ma
 ximal number of participants is limited. Applicants will be notified\, whe
 ther they are accepted for participitation.\n\nInstructors: Dr. Jan Meinke
 \, Dr. Olav Zimmermann\, JSC\n\nContact \nFor any questions concerning the
  course please send an e-mail to j.meinke@fz-juelich.de\n\nhttps://events.
 prace-ri.eu/event/567/
SUMMARY:High-performance computing with Python @ JSC
URL;VALUE=URI:https://events.prace-ri.eu/event/567/
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