Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-14-58-K-6

High Performance Computing for Python (1V+1U, 3.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 3.0 CP 62 h
1 V Lecture 14 h
1 U Exercise class (in small groups) 14 h
(1V+1U) 3.0 CP 28 h 62 h

Basedata

SWS 1V+1U
CP, Effort 3.0 CP = 90 h
Position of the semester 1 Sem. in WiSe
Level [6] Master (General)
Language [EN] English
Lecturers
Area of study [INF-VIS] Visualisation and Scientific Computing
Livecycle-State [NORM] Active

Notice

Lecture plus programming exercises.

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)
  • Details of the examination (type, duration, criteria) will be announced at the beginning of the course.

Contents

Python's powerful elegance has driven its adoption at clusters for High Performance Computing (HPC) for job orchestration, visualisation, exploratory data analysis, and even numerical simulations. But maximising performance from Python applications can be challenging especially on supercomputing architectures. This course will outline a variety of performance optimisation strategies, tools for measuring and addressing performance problems, and establish best practices for Python for HPC.

Competencies / intended learning achievements

Programming for Computations, S. Linge, H. P. Langtangen, Springer 2020

Requirements for attendance (informal)

Basic knowledge in Python is mandatory.

Requirements for attendance (formal)

None

References to Course [INF-14-58-K-6]

Module Name Context
[INF-14-58-M-6] High Performance Computing for Python P: Obligatory 1V+1U, 3.0 LP
Course-Pool Name
[INF-VIS_V-KPOOL-6] Lectures of the teaching area Visualization and Scientific Computing