Fall 2019: Applied Parallel Programming with GPUs

The goal of this class is to teach parallel computing anddeveloping applications for massively parallel processors (e.g.GPUs). Self driving cars, machine learning and augmentedreality are examples of applications involving parallel computing. The class focuses on computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies.

The course will cover popular programming interface for graphics processors (CUDA for NVIDIA processors), internal architecture of graphics processors and how it impacts performance, and implementations of parallel algorithms on graphics processors. The curriculum will be delivered in ~29 lectures. The class has heavy programming components, including six hands-on assignmentsand a final project.