052113 VU Software Tools and Libraries for Scientific Computing (2020W)
Continuous assessment of course work
Labels
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
Monday 18:30 - 20:00 digital
Wednesday 18:30 - 20:00 digital (except for exams)
Monday
05.10.
18:30 - 20:00
Digital
Wednesday
07.10.
18:30 - 20:00
Digital
Monday
12.10.
18:30 - 20:00
Digital
Wednesday
14.10.
18:30 - 20:00
Digital
Monday
19.10.
18:30 - 20:00
Digital
Wednesday
21.10.
18:30 - 20:00
Digital
Wednesday
28.10.
18:30 - 20:00
Digital
Wednesday
04.11.
18:30 - 20:00
Digital
Monday
09.11.
18:30 - 20:00
Digital
Wednesday
11.11.
18:30 - 20:00
Digital
Monday
16.11.
18:30 - 20:00
Digital
Wednesday
18.11.
18:30 - 20:00
Digital
Monday
23.11.
18:30 - 20:00
Digital
Wednesday
25.11.
18:30 - 20:00
Digital
Monday
30.11.
18:30 - 20:00
Digital
Wednesday
02.12.
18:30 - 20:00
Digital
Wednesday
02.12.
18:30 - 21:00
Hörsaal 2, Währinger Straße 29 2.OG
Monday
07.12.
18:30 - 20:00
Digital
Wednesday
09.12.
18:30 - 20:00
Digital
Monday
14.12.
18:30 - 20:00
Digital
Wednesday
16.12.
18:30 - 20:00
Digital
Monday
11.01.
18:30 - 20:00
Digital
Wednesday
13.01.
18:30 - 20:00
Digital
Monday
18.01.
18:30 - 20:00
Digital
Wednesday
20.01.
18:30 - 20:00
Digital
Monday
25.01.
18:30 - 20:00
Digital
Wednesday
27.01.
18:30 - 20:00
Digital
Wednesday
27.01.
18:30 - 21:00
Hörsaal 2, Währinger Straße 29 2.OG
Information
Aims, contents and method of the course
We discuss software tools and libraries for scientific computing including their foundational numerical algorithms. The students get familiar with using numerical libraries for sequential and parallel scientific applications like BLAS, LAPACK, MLPACK, GSL, PETSc, and MPFR. Moreover, tools for testing, debugging, and benchmarking scientific software are used. Topics include, but are not limited to, dense linear algebra, sparse linear algebra, and differential equations.The students are expected to have good general programming skills, basic familiarity with programming in C, and experience in using GNU/Linux and Bash. The course builds upon the contents of the modules "Introduction to Numerical Computing" (NUM) and "Combinatorial and Numerical Algorithms" (CNA).
Assessment and permitted materials
Weekly submissions and presentations of solutions to homework exercises, a 90-minutes midterm exam, and a 90-minutes final exam.
Minimum requirements and assessment criteria
At least 50% of the homework points and 50% of the exam points have to be achieved for passing the course. Presence is mandatory during the entire course.
Examination topics
All topics of the lectures and homework exercises.
Reading list
The lectures are accompanied by slides, which point to additional relevant literature.
Association in the course directory
Module: STL
Last modified: Th 23.03.2023 00:15