Universität Wien
Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.

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").

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

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: Fr 12.05.2023 00:13