Main field(s) of study and in-depth level:
Computational Science A1N,
Computer Science A1N,
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
G1N: has only upper-secondary level entry requirements
G1F: has less than 60 credits in first-cycle course/s as entry requirements
G1E: contains specially designed degree project for Higher Education Diploma
G2F: has at least 60 credits in first-cycle course/s as entry requirements
G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
GXX: in-depth level of the course cannot be classified
A1N: has only first-cycle course/s as entry requirements
A1F: has second-cycle course/s as entry requirements
A1E: contains degree project for Master of Arts/Master of Science (60 credits)
A2E: contains degree project for Master of Arts/Master of Science (120 credits)
AXX: in-depth level of the course cannot be classified
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
The Faculty Board of Science and Technology
120 credits in science/engineering including Scientific Computing II, 5 credits, a second course in computer programming and 30 credits in mathematics. Scientific Computing II may be replaced by Scientific Computing, bridging course or Numerical Methods and Simulation or Scientific Computing and Calculus.
implement computational algorithms to efficient C-code for modern computer architectures;
use tools for performance optimisation and debugging;
propose and implement efficient performance optimisations;
identify factors that restrict parallelism in an algorithm or a program;
present written performance analysis in a clear and explicit way.
Programming in C/C++ under Linux/Unix. Parallel programming with OpenMP and Pthreads. Task-based programming. Tools and methods for problem solving, software development, debugging and performance analysis. Different types of computer architectures and memory organisations. Efficient implementations of numerical methods on modern computer architectures. Applications from different areas in science and engineering.
Lectures, computer labs, assignments and projects.
Assignments and projects reported both as written reports and orally.