Parallel Algorithms and Applications in Data Science

0.5 credit · Graduate

Multiprocessor architectures from an application programmer’s perspective: programming models, processor clusters, multi-core processors, GPU’s, algorithmic paradigms, efficient parallel problem solving, scalability and portability. Projects on high performance computing in Data Science, incl. data analytics, bioinformatics, simulations. Programming experience on parallel processing equipment.