Kaisa_2012_3_photo by Veikko Somerpuro

All information on exceptional situation arrangements in spring 2020 of teaching the course can be found at course Moodle page at https://moodle.helsinki.fi/course/view.php?id=17217

Enrol

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Wed 15.1.2020
16:15 - 18:00
Wed 22.1.2020
16:15 - 18:00
Wed 29.1.2020
16:15 - 18:00
Wed 5.2.2020
16:15 - 18:00
Wed 12.2.2020
16:15 - 18:00
Wed 19.2.2020
16:15 - 18:00
Wed 26.2.2020
16:15 - 18:00
Wed 11.3.2020
16:15 - 18:00
Wed 18.3.2020
16:15 - 18:00
Wed 25.3.2020
16:15 - 18:00
Wed 1.4.2020
16:15 - 18:00
Wed 8.4.2020
16:15 - 18:00
Wed 22.4.2020
16:15 - 18:00
Wed 29.4.2020
16:15 - 18:00

Other teaching

17.01. - 28.02.2020 Fri 12.15-14.00
13.03. - 03.04.2020 Fri 12.15-14.00
17.04. - 24.04.2020 Fri 12.15-14.00
Teaching language: English

Description

Master's Programme in Materials Research is responsible for the course.

Modules where the course belongs to:

  • MATR300 Advanced Studies in Materials Research
    Optional for:
    1. Study Track in Computational Materials Physics
  • TCM300 Advanced Studies in Theoretical and Computational Methods

The course is available to students from other degree programmes.

  • Good programming skills in C/C++, or Fortran90/95/2003/2008, languages on the level of course 53399 Scientific Computing II.
  • Familiarity with the Linux programming environment is strongly suggested.

Course 53369 Scientific computing III where numerical methods are is recommended.

  • You will learn to use Linux programming tools
    • compilation, make utility, debugging, profiling
  • You will learn the means to optimize your code
  • You will understand the concept of parallel computing
  • You will learn to write parallel programs using
    • message passing
    • thread-based parallellization

The course can be taken in the early or later stages of studies.

Given every second year (even years) in the spring term.

  • Programming tools in the Linux environment

  • Code optimization
  • Concepts in parallel computing
  • Parallel computing in clusters: message passing
  • Thread-based parallel computing

Lecture notes.

Weekly lectures and exercises (individual work). Final programming project (individual). Total hours 135.

Final grade is based on exercises (50%) and final programming project (50%).

Exercises and final project. Exercises are mostly small programming tasks. In the final project a computational problem larger than exercises is solved.