Highly Concurrent Algorithms

The course is given biannually, next time spring 2020. The purpose of the course is studying massively parallel systems for special purpose data applications. The focus is on non-numerical applications, i.e. searching, recognition, pattern discovery and algorotihms related to Machine Learning. The chosen subjects might be adapted to the background and interests of the students.

The main objective of the course is to train PhD students in advanced methods in parallel algorithms. A. Knowledge: The candidate's knowledge about state of the art massively parallel algorithms and main research methods in the field will be strengthened by selected scientific papers. B. Skills: The candidate will be able to apply massively parallel algorithms in different application domains as well as analysing them wrt. performance on different underlying computational models (abstract machines). C. Competence: The candidate will get new knowledge and learn to build new knowledge within the field, and thus be trained to contribute in research or development projects within parallel computing.

Colloquial form where students take part and/or self-study. Dependent on number of students having the course.