Computational Science: Parallel Programming in Scientific Computing

Education facts

Code: BERN09

<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>

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).

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Computational Science: Parallel Programming in Scientific Computing

  Lund University

  Start date: 2 November 2026

  End date: 17 January 2027

  Pace of study: 50 %