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UID:pretalx-euroscipy-2024-E8HD9K@pretalx.com
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DESCRIPTION:Parallel computing is essential for many performance-critical a
 pplications. Python provides many solutions for this problem. New versions
  of Python will support sub-interpreters and a\, currently experimental\, 
 free-threading version without the Global Interpreter Lock (GIL).\n\nThis 
 talk starts with a short overview over this topic\, clarifying terms such 
 parallel\, concurrent\, and distribute computing as well as CPU-bound\, me
 mory-bound\, and IO-bound problems. The presentation explains how Python a
 nd its standard library support parallel programming tasks. In addition\, 
 many Python libraries provide very useful approaches and tools for paralle
 l computing. An overview of important libraries provides guidance which li
 brary can be used for what type of parallel problem.\n\nHow do Python's ne
 w features such as sub-interpreters and free-threading without the Global 
 Interpreter Lock (GIL) impact parallel Programming in Python? This talk ad
 dress this question by providing examples where these features might help 
 to make programs simpler and/or faster.
DTSTAMP:20260423T031858Z
LOCATION:Room 6
SUMMARY:The Parallel Universe in Python - A Time Travel to Python 3.13 and 
 beyond - Mike Müller
URL:https://pretalx.com/euroscipy-2024/talk/E8HD9K/
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