hands-on tutorial
Hands-on for 'Python - Multiprocessing' tutorial
The questions this addresses are:
- How can I parallelize code to make it run faster
- What code is, or is not, a prime target for parallelisation
The objectives are:
- Understanding how to paralellise code to make it run faster.
- Identifying how to decompose code into a parallel unit.
Licence: Creative Commons Attribution 4.0 International
Keywords: data-science, jupyter-notebook
Target audience: Students
Resource type: hands-on tutorial
Scientific topics: Software engineering
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