Commit fcf71290 authored by Jan Meinke's avatar Jan Meinke
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Add missing README.

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High-Performance Computing with Python @ JSC
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:Author: Jan H. Meinke
:Author: Olav Zimmermann
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.
This course combines lectures and hands-on session. We will show how Python can be used on parallel
architectures and how performance critical parts of the kernel can be optimized using various tools.
For using Python productively for parallel computing, these topics will be covered:
* Interactive parallel programming with IPython
* Profiling and optimization
* High-performance NumPy and SciPy, numba
* Distributed-memory parallel programming with Python and MPI
* Bindings to other programming languages and HPC libraries
* Interfaces to GPUs
This course is aimed at scientists who wish to explore the productivity gains made possible by Python
for HPC.
This course is a PRACE Advanced Training Centres (PATC) course.
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