052112 VU Numerical High Performance Algorithms (2020W)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik

Continuous assessment of course work

Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Registration is open from Mo 14.09.2020 09:00 to Mo 21.09.2020 09:00
Deregistration possible until We 14.10.2020 23:59

Details

max. 25 participants

Language: English

Lecturers

Classes (iCal) - next class is marked with N

PLEASE NOTE: Due to the current COVID situation the course is online until further notice!

    
    Thursday
    01.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    06.10.
    13:15 - 14:45
    Digital
    
    Thursday
    08.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    13.10.
    13:15 - 14:45
    Digital
    
    Thursday
    15.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    20.10.
    13:15 - 14:45
    Digital
    
    Thursday
    22.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    27.10.
    13:15 - 14:45
    Digital
    
    Thursday
    29.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    03.11.
    13:15 - 14:45
    Digital
    
    Thursday
    05.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    10.11.
    13:15 - 14:45
    Digital
    
    Thursday
    12.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    17.11.
    13:15 - 14:45
    Digital
    
    Thursday
    19.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    24.11.
    13:15 - 14:45
    Digital
    
    Thursday
    26.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    01.12.
    13:15 - 14:45
    Digital
    
    Thursday
    03.12.
    13:15 - 14:45
    Digital
    
    Thursday
    10.12.
    13:15 - 14:45
    Digital
    
    Tuesday
    15.12.
    13:15 - 14:45
    Digital
    
    Thursday
    17.12.
    13:15 - 14:45
    Digital
    
    Thursday
    07.01.
    13:15 - 14:45
    Digital
    
    Tuesday
    12.01.
    13:15 - 14:45
    Digital
    
    Thursday
    14.01.
    13:15 - 14:45
    Digital
    
    Tuesday
    19.01.
    13:15 - 14:45
    Digital
    
    Thursday
    21.01.
    13:15 - 14:45
    Digital
    
    Tuesday
    26.01.
    13:15 - 14:45
    Digital
    
    Thursday
    28.01.
    13:15 - 14:45
    Digital

Information

Aims, contents and method of the course

PLEASE NOTE: Due to the current COVID situation the course is online until further notice!

Know and understand selected advanced numerical high performance algorithms (including divide-and-conquer eigensolver, GMRES, least squares solver, QR algorithm, communication-avoiding linear solver, etc.) for large and very large problems. Understand the interdependencies between problem data, algorithm, implementation of the algorithm, hardware, performance and accuracy. Understand basic techniques for analysis, implementation and optimization of numerical high performance algorithms. Implement and evaluate your own implementations.

Assessment and permitted materials

Two homework exercises (with theoretical and practical components - implementation, experimentation, analysis), presentation of assigned papers from the literature, and an individual semester project (involving literature research, implementation, experimentation, analysis), whose results have to be presented in class and documented in written form (project report, presentation slides) during the semester.

Minimum requirements and assessment criteria

The maximum possible score is 100 points (20 for the homework exercises, 30 for the paper presentations, 25 for the presentation of the semester project, 25 for the report of the semester project). At least 50 points are required for passing the course. For passing the course, in each component (homeworks, paper presentations, semester project) at least half of the available points have to be achieved.

Examination topics

There is no separate exam, grading takes into account discussions and questions for each component (homeworks, paper presentations, semester project).

Reading list

Slides presented in class, literature references given on the slides.

J. Demmel: Applied Numerical Linear Algebra
L. N. Trefethen and D, Bau, III: Numerical Linear Algebra
Golub & van Loan: Matrix Computations

Association in the course directory

Module: HPA APS

Last modified: Fr 12.05.2023 00:13