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052112 VU Numerical High Performance Algorithms (2020W)

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

Prüfungsimmanente Lehrveranstaltung

Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Anmeldung von Mo 14.09.2020 09:00 bis Mo 21.09.2020 09:00
Abmeldung bis Mi 14.10.2020 23:59

Details

max. 25 Teilnehmer*innen

Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

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

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

Ziele, Inhalte und Methode der Lehrveranstaltung

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.

Art der Leistungskontrolle und erlaubte Hilfsmittel

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.

Mindestanforderungen und Beurteilungsmaßstab

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.

Prüfungsstoff

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

Literatur

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

Zuordnung im Vorlesungsverzeichnis

Module: HPA APS

Letzte Änderung: Do 08.10.2020 11:28