151-0116-10L High Performance Computing for Science and Engineering (HPCSE) for Engineers II
| Semester | Spring Semester 2018 |
| Lecturers | P. Koumoutsakos, P. Chatzidoukas |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Abstract | This course focuses on programming methods and tools for parallel computing on multi and many-core architectures. Emphasis will be placed on practical and computational aspects of Uncertainty Quantification and Propagation including the implementation of relevant algorithms on HPC architectures. |
| Learning objective | The course will teach - programming models and tools for multi and many-core architectures - fundamental concepts of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences |
| Content | High Performance Computing: - Advanced topics in shared-memory programming - Advanced topics in MPI - GPU architectures and CUDA programming Uncertainty Quantification: - Uncertainty quantification under parametric and non-parametric modeling uncertainty - Bayesian inference with model class assessment - Markov Chain Monte Carlo simulation |
| Lecture notes | http://www.cse-lab.ethz.ch/index.php/teaching/42-teaching/classes/704-hpcse2 Class notes, handouts |
| Literature | - Class notes - Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein - CUDA by example, J. Sanders and E. Kandrot - Data Analysis: A Bayesian Tutorial, Devinderjit Sivia |