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Lund University
Computational Science: Parallel Programming in Scientific Computing
<p>The course covers key concepts in parallel programming and issues affecting correctness and performance. Upon completion, students will have advanced knowledge to develop, modify, and evaluate parallel algorithms and programs.</p><p>The course is an alternative-compulsory course within the Master’s Programme in C…
- Higher education
- Information unavailable
- 2 November 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>The course covers key concepts in parallel programming and issues affecting correctness and performance. Upon completion, students will have advanced knowledge to develop, modify, and evaluate parallel algorithms and programs.</p><p>The course is an alternative-compulsory course within the Master’s Programme in Computational Science and may be included as an optional advanced-level course in the Master’s Programme in Mathematics with a specialization in Numerical Analysis. It can also be taken as a standalone course.</p> <p>The course introduces programming in C and addresses parallel computing with both distributed and shared memory. It covers essential commands in the MPI and OpenMP interfaces, methods for performance evaluation, debugging, and profiling of parallel applications. Furthermore, it discusses efficient parallelization of common algorithmic constructs as well as hybrid parallelization of stencil codes on regular grids.</p>
Admission scores
Entry requirements
For admission to the course English 6/B and at least 90 credits in natural science are required, including knowledge equivalent to the course NUMA01 Computational Programming with Python (7.5 credits). In addition, knowledge equivalent to one of the following courses is required: NUMA32 Numerical Methods for Differential Equations (7.5 credits), NUMN21 Advanced Course in Numerical Algorithms with Python/SciPy (7.5 credits), FYTN03 Computational Physics (7.5 credits) or FYSN33 Applied Computational Physics and Machine Learning (7.5 credits).
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-11-02
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.lu.bern09.13059.20262
- Last checked
- 2026-09-23T10:38:26.989764+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.bern09.13059.20262
- Offering identity in the source
- e.uoh.lu.bern09.13059.20262
- Education-form source code
- HS
- Education code in the source
- BERN09
- Change time according to the source
- 2026-02-03T10:34:16
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.