Using Python in an HPC environment

Pre-requirements:

Pre-requirements
Prepare the environment

Common:

Schedule
Log in and other preparations
Use the tarball with exercises
Use a text editor
HPC clusters
NAISS projects overview
New system Arrhenius

Lessons day 1 (Intro to Python):

Link to Day 1 (Intro to Python)

Lessons day 2 (packages and analysis):

Introduction
Using packages
Installing packages
Using isolated environments
Basic batch and Slurm
Interactive work on the compute nodes
Gfx launcher/Desktop On Demand including IDEs
Using IDEs
Summary day 2
Evaluation
Python documentations at the different HPC centres

Lessons day 3 (advanced analysis):

pandas
matplotlib
seaborn
Big data with Python
Running Python in batch mode
Summary day 3
Evaluation

Lessons day 4 (parallel and ML):

Parallel computing with Python
Using GPUs with Python
Machine Learning and Deep Learning
Dimensionality Reduction
Evaluation
Summary day 4

Extra:

Acknowledgments
Other courses
Interactive sessions and Desktop On-Demand
Python bundles
More about ML
Evaluations
Conda
Extra material about isolated environments
More about interactive work
Developing in isolated environments
Jupyter at Kebnekaise
Other courses
More about packages
On Kebnekaise cluster
Lesson plans
Meeting notes
Reflections
On UPPMAX clusters

Using Python in an HPC environment

Evaluation 2025-11
Edit on GitHub

Evaluation 2025-11

analysis.R

Analysis

Analysis
The same data as a table: confidences_course.csv

Confidences per question

© Copyright 2025, UPPMAX/HPC2N/LUNARC/InfraVis.

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