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 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. The goal of this course is hence: To give the students a good understanding of optimzing serial programs and algorithms within computational science as well as how to develop such programs for current and future multi-processor systems.

Learning methods and activities

Lecture and programming assignments. The course may be given in English if needed. 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

Prerequesites include: Algorithms and datastructure, Operating systems.

Course materials

Syllabus will be available at the start of the semester.

Credit reductions