After successful completion of the course, students are able to use modern parallel processor architectures efficiently and understand their strengths and weaknesses. Students will get a deep understanding of the main workloads in computational science and how many-core architectures can be leveraged to run larger problems in less time than with conventional approaches.

Topics covered in this course include:

• Ahmdal's Law
• FLOPs, Bandwidth, and Latency
• Performance Modeling
• Graphics Processing Units (SIMT processing, thread block synchronization)
• Programming Models (Annotation-driven such as OpenMP, native such as CUDA)
• Field Programmable Gate Arrays
• Emerging Many-Core Architectures

Presentation of new material via prepared videos for self-study each week. Each week there is an interactive one-hour-lecture (hybrid format) to answer questions and assert clarity. There are hands-on exercises for students to familiarize themselves with the new material in between lectures. Submission of short reports by the students. Review of student submissions, discussion of problems.

• Attendance Required!

Virtual oral exam after positive evaluation of the practical part. Registration in TISS.

Familiarity with at least one programming language (e.g. C or Python)