Practical introduction to HPC systems 4010-PROa
A detailed description of the subject is provided at the level of a given teaching cycle in the Description section.
|
Term 2025Z:
Course topics: Total: 15 hours |
Term 2025L:
Course topics: Total: 15 hours |
Term 2026Z:
Course topics: Total: 15 hours |
Course coordinators
Type of course
Mode
Term 2025L: Blended learning | Term 2025Z: Blended learning | Term 2026Z: Classroom |
Prerequisites (description)
Learning outcomes
Field-specific learning outcomes with reference to Level 2 PRK characteristics:
the student is able to:
K_U05 - plan and conduct computer simulations, analyze their results, and formulate conclusions relevant to a selected field of science,
K_U13 - manage large computer systems, e.g., by ensuring access control and a level of security appropriate to requirements, as well as by monitoring resource utilization.
and the subject-specific learning outcomes:
the student is able to:
U1 - Prepare the user environment and input data necessary to perform scientific calculations in an HPC system [K_U05],
U2 - Access the HPC system via a secure network protocol, allocate computing resources, and launch and control tasks running in the system [K_U13].
Assessment criteria
1. Completion of the course ends with one common grade for all classes (lecture + laboratory) carried out as part of the course.
2. A sick leave does not exempt students from knowledge of the material. It only entitles them to an individualized form of assessment.
3. Students who have received approval for an individualized course of study are required to contact the course coordinator to determine how to achieve all the learning outcomes assigned to the course. If the above-mentioned outcomes cannot be achieved, the coordinator may refuse to grant credit for the course.
4. Attendance is mandatory. In cases of justified absences, the student is required to contact the course coordinator immediately.
5. Regarding the use of artificial intelligence (AI) tools in the preparation of coursework, the rules set out in the "Regulations on the Use of Artificial Intelligence Tools in the Educational Process for the Computational Engineering Degree Programme" apply.
6. Detailed grading criteria are provided at the level of the given academic cycle in the "Notes" section.
Practical placement
Not applicable.
Bibliography
The subject literature has been posted at the level of a given teaching cycle in the Bibliography section.
|
Term 2025Z:
Lecture and exercise materials provided by the instructors, and documentation for the software used: |
Term 2025L:
Lecture and exercise materials provided by the instructors, and documentation for the software used: |
Term 2026Z:
Lecture and exercise materials provided by the instructors, and documentation for the software used: |
Notes
|
Term 2025Z:
Grade-based assessment based on the completion of practical assignments specified by the instructor (Learning Outcomes U1-U2). |
Term 2025L:
Grade-based assessment based on the completion of practical assignments specified by the instructor (Learning Outcomes U1-U2). |
Term 2026Z:
Grade-based assessment based on the completion of practical assignments specified by the instructor (Learning Outcomes U1-U2). |