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17164-01 - Lecture: High Performance Computing 4 CP

Semester spring semester 2024
Course frequency Every spring sem.
Lecturers Florina M. Ciorba (florina.ciorba@unibas.ch, Assessor)
Content Deepen and expand the knowledge of parallel and distributed computing systems. 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
* HPC, Big Data, and AI
* Novel/upcoming models of computation
* Hold a debate on a hot topic in HPC
Learning objectives Offer students an advanced understanding parallelization of various problems and their parallel programming, as well as how their performance and factors that influence it when executing on parallel architectures.

The course will leave students with an up-to-date overview and the practical use of current programming models for achieving high performance computing (HPC).
Bibliography Course material, such as book titles and links to online information, are provided in the lectures.
Comments Target group:

* Bachelor
* Master
* Doctoral students
* Postdoctoral researchers

from computer science, computational science (biology, physics, chemistry) as well as digital humanities and all disciplines that (need to) process information on more than one computer and demand high performance (not productivity).
Weblink Website of the HPC Lecture

 

Admission requirements Basic knowledge of the following topics is a plus, but not a prerequisite.
* Programming (C/C++ or Java),
* Foundations of Distributed Systems (MA lecture offered in the fall semesters).

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 MOnA 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

Dates

Date Time Room
Thursday 29.02.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 07.03.2024 10.15-12.00 Biozentrum, Seminarraum U1.197
Thursday 14.03.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 21.03.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 28.03.2024 10.15-12.00 Ostern
Thursday 04.04.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 11.04.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 18.04.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 25.04.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 02.05.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 09.05.2024 10.15-12.00 Auffahrt
Thursday 16.05.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 23.05.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Thursday 30.05.2024 10.15-12.00 Spiegelgasse 5, Seminarraum 05.002
Modules Doctorate Computer Science: Recommendations (PhD subject: Computer Science)
Modul: Concepts of Distributed Systems (Master's degree 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 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 The course assessment will be in the form of a *written examination*, which will result in the only (but final) grade of the course.

To be eligible to take the written examination, students must achieve a minimum of 50% of the number of points associated with *each* of the exercises accompanying the lecture.

Expected examination date: 13 June 2024, 10-12 a.m. (written exam, with presence), Spiegelgasse 5, room 05.002.
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

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