Computational systems, data bases, networks 4010-WSOa
Subjects:
1. Programming languages - lecture 4 hours
2. File transfer - lecture 2 hours, laboratory 2 hours
3. File systems - lecture 2 hours
4. NAS - lecture 2 hours
5. CPU Architecture: x86_64 - lecture 4 hours
6. Virtualisation - lecture 2 hours, laboratory 2 hours
7. GPU - lecture 4 hours, laboratory 4 hours
8. Slurm Scheduling System - lecture 2 hours, laboratory 2 hours
9. Building and installing software - lecture 2 hours, laboratory 4 hours
10. Vector computers - lecture 2 hours
11. LINPACK - laboratory 2 hours
12. HPCG - laboratory 2 hours
13. Numerical libraries - laboratory 2 hours
14. Scalar optimization - lecture 2 hours, laboratory 2 hours
15. Quantum computers - lecture 2 hours
16. Scaling HPC Application - laboratory 8 hours
The order of topics and the level of detail may be subject to minor adjustments.
Course coordinators
Type of course
Mode
Prerequisites (description)
Learning outcomes
The student knows and understands:
W1 - Demonstrates in-depth understanding of the structure of HPC computer systems, their key components, and their operating mechanisms [K_W07]
W2 - Demonstrates in-depth understanding of the current development trends in modern HPC computer systems (clusters and supercomputers), including their architectures and the networking technologies they utilize [K_W08]
The student is able to:
U1 - Assess the usefulness and feasibility of using new hardware solutions, including HPC architectures, and software solutions (domain-specific implementations) for solving computational problems [K_U07]
U2 - Operate HPC computer systems using secure access protocols, and monitor resource utilization for computational tasks [K_U13]
The student is ready to:
K1 - Establish and maintain collaboration with others and strive to achieve team goals by planning and organizing work – utilizes tools for collaborating on IT projects [K_K01]
Assessment criteria
Learning outcomes W1-W2 and U1-U2 are assessed by a written exam and ongoing monitoring of student activity during lectures and laboratory exercises;
Learning outcome K1 is assessed by ongoing monitoring of student activity during lectures and laboratory exercises.
NOTE
1. A sick leave certificate does not exempt students from knowledge of the material. It only entitles them to an individualized form of assessment.
2. Students who have received approval for an individualized course of study are required to contact the course coordinator to discuss how to achieve all learning outcomes assigned to the course. If the above-mentioned outcomes cannot be achieved, the coordinator may refuse to grant credit for the course.
3. Attendance is mandatory. In cases of justified absence, the student is required to contact the course coordinator immediately.
Practical placement
Not applicable.