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DTSTAMP:20260405T165251Z
UID:c939a049-f8d5-425a-bf85-6332f261ec83
DTSTART:20240924T093000Z
DTEND:20240927T180000Z
DESCRIPTION:This is a School organized by the ErUM-Data-Hub with support fr
 om DIG-UM.\n\nIn this school you will learn how Python code can be acceler
 ated. A focus will be placed on numeric NumPy-like array computations. In 
 addition\, running these array computations on hardware accelerators\, i.e
 .\, GPUs\, will play a key role in this school.\n\nThe school is intended 
 for young researchers - especially for PhD students - who regularly work w
 ith the scientific Python ecosystem. Requirements are good knowledge of th
 e scientific Python ecosystem\, basics of the C++ programming language are
  beneficial.\n\nThe school (see timetable) is split into five parts of whi
 ch three are keynote lectures with hands-on tutorials. The other two compr
 ise an opening talk and a coding group challenge for the participants.\n\n
 A fee of 300€ will be charged for participation in the workshop.\n\n## T
 opics: \n\n* Setting the scene: benefits and disadvantages of the Python p
 rogramming language and a brief outline how Python programs can be acceler
 ated in general.\n* Efficient Python Programming: general approaches to ac
 celerate Python code\, using C++ in Python and accelerating array computat
 ions. \n* Accelerator Optimised Programming: how array computations can be
  run on GPUs with typical Deep Learning libraries\, such as JAX or TensorF
 low. \n* GPU Programming: understanding the hardware layout\, i.e.\, threa
 d and memory layout and hierarchy and basics of the CUDA toolkit. A focus 
 is set on how to program custom GPU kernels for\, e.g.\, Deep Learning app
 lications (in JAX or TensorFlow).\n* Group Challenge
SUMMARY:Fast and Efficient Python Computing School
URL;VALUE=URI:https://indico.desy.de/event/40133/
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