151-0116-10L  High Performance Computing for Science and Engineering (HPCSE) for Engineers II

SemesterSpring Semester 2021
LecturersP. Koumoutsakos, S. M. Martin
Periodicityyearly recurring course
Language of instructionEnglish


151-0116-00 GHigh Performance Computing for Science and Engineering (HPCSE) II
Lecture: 14-16h
Exercises: 10-12h. The exercises begin in the second week of the semester.
4 hrs
Mon10-12ML H 44 »
14-16ML H 44 »
P. Koumoutsakos, S. M. Martin

Catalogue data

AbstractThis 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.
ObjectiveThe 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
ContentHigh 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 noteshttps://www.cse-lab.ethz.ch/teaching/hpcse-ii_fs21/
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, D. Sivia and J. Skilling
- An introduction to Bayesian Analysis - Theory and Methods, J. Gosh, N. Delampady and S. Tapas
- Bayesian Data Analysis, A. Gelman, J. Carlin, H. Stern, D. Dunson, A. Vehtari and D. Rubin
- Machine Learning: A Bayesian and Optimization Perspective, S. Theodorides
Prerequisites / NoticeStudents must be familiar with the content of High Performance Computing for Science and Engineering I (151-0107-20L)

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersP. Koumoutsakos
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 180 minutes
Additional information on mode of examinationMost probably a computer based examination involving theoretical questions and coding problems. Parts of the lecture documents and other materials will be made available online during the examination.
Written aidsYou are allowed to bring a HANDWRITTEN summary of 3 A4 sheets, written on the front and back pages (6 pages total). Photocopies are not allowed.
Online examinationThe examination may take place on the computer.
Distance examinationIt is not possible to take a distance examination.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

Main linkCourse web page
Only public learning materials are listed.


No information on groups available.


There are no additional restrictions for the registration.

Offered in

Computer Science BachelorElectivesWInformation
Mechanical Engineering MasterEnergy, Flows and ProcessesWInformation
Mechanical Engineering MasterMechanics, Materials, StructuresWInformation
Mechanical Engineering MasterRobotics, Systems and ControlWInformation
Mechanical Engineering MasterMicro & NanosystemsWInformation
Mechanical Engineering MasterBioengineeringWInformation
Micro- and Nanosystems MasterModelling and SimulationWInformation
Physics MasterGeneral ElectivesWInformation
Robotics, Systems and Control MasterCore CoursesWInformation
Process Engineering MasterCore CoursesWInformation