Back to selection
17164-01 - Lecture: High Performance Computing (6 CP)
| Semester | spring semester 2026 |
| Course frequency | Every spring sem. |
| Lecturers | Florina M. Ciorba (florina.ciorba@unibas.ch, Assessor) |
| Content | High performance computing (HPC) enables modern scientific discovery, large-scale data analysis, and computational science. From simulating climate systems and training advanced machine-learning models to enabling real-time processing of data produced by scientific instruments, efficient parallel programs are essential to achieving breakthrough results. Achieving this performance requires a deep understanding of parallel programming models, system architectures, and the principles that influence scalable computation. In this lecture, you will expand on the parallel programming foundations introduced in Foundations of Distributed Systems course (8 CP) and learn additional core concepts and techniques required to design, implement, and optimize high-performance applications. We will discuss: * Parallel systems architectures * Parallel applications workloads * Advanced parallel programming models and languages (OpenMP, MPI, OpenACC, CUDA, and combinations thereof) * Fault tolerance and resilience * Performance engineering and performance reproducibility * The role of HPC in the age of AI * Novel/upcoming models of computation |
| Learning objectives | * Understand how computational problems can be efficiently parallelized, distributed, and executed across diverse compute entities, from multi- and heterogeneous cores within a single machine to thousands of nodes in large-scale HPC systems. * Know the advanced principles of parallel and distributed programming needed to reason about performance, scalability, and resource utilization. * Understand the importance of algorithms, performance-optimization techniques, performance engineering, correctness, and reproducibility, as well as the role of HPC in the era of AI-driven workloads. * Implement, analyze, and evaluate high-performance solutions using modern HPC tools, programming models, and profiling techniques. |
| Bibliography | Course material, such as book titles and links to online information, are provided in the lectures. |
| Comments | Target group: * Master students * Doctoral students * Postdoctoral researchers from computer science, computational science, digital humanities, and all disciplines that (need to) process information on more than one computer and demand high performance. Note for students of the Master Computer Science: you can take this lecture as part of the modules “Concepts of Distributed Systems”, “Applications of Distributed Systems”, “Applications of Machine Intelligence” Note for students of the Master Data Science: you can take this lecture as part of the module "Systems Foundations". Note for students of the Master Computational Biology and Bioinformatics: you can take this lecture as part of the module “Vertiefungsfächer Theorie und Vertiefungsfächer Biologie”. |
| Weblink | Website of the HPC Lecture |
| Admission requirements | * Foundations of Distributed Systems (8 CP Master lecture offered in the fall semesters). Students who have not taken it, the lecturer can provide the list of relevant topics for independent study. * Basic knowledge of C/C++ programming. Students with reduced computer science background are still encouraged to enroll and discuss their prior knowledge with the lecturer and the course assistants. |
| Course application | Your online/services account. |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Thursday | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| wöchentlich | Thursday | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
Dates
| Date | Time | Room |
|---|---|---|
| Thursday 19.02.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 19.02.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 26.02.2026 | 10.15-12.00 | Fasnachtsferien |
| Thursday 26.02.2026 | 12.15-14.00 | Fasnachtsferien |
| Thursday 05.03.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 05.03.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 12.03.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 12.03.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 19.03.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 19.03.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 26.03.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 26.03.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 02.04.2026 | 10.15-12.00 | Ostern |
| Thursday 02.04.2026 | 12.15-14.00 | Ostern |
| Thursday 09.04.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 09.04.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 16.04.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 16.04.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 23.04.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 23.04.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 30.04.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 30.04.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 07.05.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 07.05.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 14.05.2026 | 10.15-12.00 | Auffahrt |
| Thursday 14.05.2026 | 12.15-14.00 | Auffahrt |
| Thursday 21.05.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 21.05.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 28.05.2026 | 10.15-12.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Thursday 28.05.2026 | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
| Modules |
Doctorate Computer Science: Recommendations (PhD subject: Computer Science) Module: Applications of Distributed Systems (Master's Studies: Computer Science) Module: Applications of Machine Intelligence (Master's Studies: Computer Science) Module: Concepts of Distributed Systems (Master's degree subject: Computer Science) Module: Concepts of Distributed Systems (Master's Studies: Computer Science) Module: Systems Foundations (Master's Studies: Data Science) Vertiefungsfächer Theorie und Vertiefungsfächer Biologie (Master's Studies: Computational Biology and Bioinformatics) |
| Assessment format | continuous assessment |
| Assessment details | Continuous assessment. Please note: final grade of the course is the weighted average of the 40% project grade (writeup and presentation) 60% written exam grade. A 50% score on each homework set is required to participate in the final written exam. Expected date for written exam: Thursday, 11/06/26; 10-12 a.m. (with presence) Room TBD for project presentations: Thursday 25/06/26 and Friday 26/06/26, 08:00-17:00. Room TBD |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Fachbereich Informatik |