Course content

Optimizing algorithms for both single and multi-processors systems. Choosing numerical algoriths, use of optimized libraries, compiler optimizations and program profiling. How to take advantage of PC-clusters and graphics cards for computationally large tasks which cannot be run on a single processor system will also be covered. The course includes parallel programming asignments.

Learning outcome

Understanding parallel programing is becoming increasingly more important as PCs and desktops incorporate multicore and multichip multiprocessor technology.

Knowledge:
The goal of this course is hence: To give the students a good understanding of optimzing serial programs and algorithms within computational science.

Skills:
Develop the students programming skills for and future multi- and many-core processor systems.

Learning methods and activities

Lecture and programming assignments. The course will be given in English. All problem sets and exams will be given in English. The programing assignments will count for one 4th of the final grade. If there is a re-sit examination, the examination form may change from written to oral.

Compulsory assignments

• Exercises

Recommended previous knowledge

Operation systems and algorithms & data structures are recommended, but if your have a strong math background, that should way up for possible extra work.

Course materials

Syllabus will be available at the start of the semester.

Credit reductions