This course provides insight into a broad variety of High Performance Computing (HPC) concepts and the majority of modern HPC architectures. Moreover, the student will learn to have a feeling about what architectures are suited for several types of algorit ...
Multiprocessors are basic building blocks for all computer systems. This course covers the architecture and organization of modern multiprocessors, prevalent accelerators (e.g., GPU, TPU), and datacenters. It includes a research project on multiprocessors ...
This course explores techniques for exploiting instruction-level parallelism both statically and dynamically. It also addresses the generation of hardware accelerators from programming languages and investigates security issues related to microarchitectura ...
This hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
Learn the concepts, tools and API's that are needed to debug, test, optimize and parallelize a scientific application on a cluster from an existing code or from scratch. Both OpenMP (shared memory) and MPI (distributed memory) paradigms are presented and ...
The students study and apply fundamental concepts and algorithms of computer graphics for rendering, geometry
synthesis, and animation. They design and implement their own interactive graphics programs. ...