269015 VU Computer Architecture and High Performance Computing (2017S)

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 We 01.02.2017 04:00 to Mo 20.02.2017 23:00
Deregistration possible until Tu 21.03.2017 23:00

Details

max. 15 participants

Language: English

Lecturers

Classes (iCal) - next class is marked with N

    
    Monday
    06.03.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    (Kickoff Class)
  
    Monday
    20.03.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    27.03.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    03.04.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    24.04.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    08.05.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    15.05.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    22.05.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    29.05.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    12.06.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    19.06.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG
    
    Monday
    26.06.
    09:45 - 11:15
    Seminarraum 11, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

Understand fundamental concepts of computer architectures and numerical high performance computing. Understand the relationship between problem data, algorithm, implementation of the algorithm, hardware, performance and accuracy. Understand basic concepts for optimized implementations of high performance matrix algorithms, based on a detailed discussion of dense linear solvers for large linear systems.

Method: Integration of lecture and discussions of homework problems in class, programming required (numerical code in a high-level programming language).

Assessment and permitted materials

Two homework projects with several components (implementation, experimentation and analysis), whose results have to be summarized (project report), presented and discussed in class. Oral exam at the end of the semester.

Minimum requirements and assessment criteria

Contributions to the total grade: First homework project 50%, second homework project 25%, oral exam 25%.

Examination topics

Material presented in class and contents of homework projects.

Reading list

Slides; M. T. Heath: Scientific Computing an Introductory Survey

Association in the course directory

CO-INF3

Last modified: Sa 08.07.2023 00:21