Search result: Catalogue data in Autumn Semester 2016
Computer Science Bachelor  | ||||||
 Bachelor Studies (Programme Regulations 2008) | ||||||
| Major | ||||||
| Compulsory Major Courses | ||||||
| Major in Computational Science The lecture 151-0107-20L High Performance Computing for Science and Engineering I in the autumn semester can only together with the lecture 401-0686-10L High Performance Computing for Science and Engineering II in the spring semester be accredited as compulsory course. | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|---|
| 252-0206-00L | Visual Computing | O | 8 credits | 4V + 3U | M. Gross, O. Hilliges | |
| Abstract | This course acquaints students with core knowledge in computer graphics, image processing, multimedia and computer vision. Topics include: Graphics pipeline, perception and camera models, transformation, shading, global illumination, texturing, sampling, filtering, image representations, image and video compression, edge detection and optical flow. | |||||
| Learning objective | This course provides an in-depth introduction to the core concepts of computer graphics, image processing, multimedia and computer vision. The course forms a basis for the specialization track Visual Computing of the CS master program at ETH. | |||||
| Content | Course topics will include: Graphics pipeline, perception and color models, camera models, transformations and projection, projections, lighting, shading, global illumination, texturing, sampling theorem, Fourier transforms, image representations, convolution, linear filtering, diffusion, nonlinear filtering, edge detection, optical flow, image and video compression. In theoretical and practical homework assignments students will learn to apply and implement the presented concepts and algorithms. | |||||
| Lecture notes | A scriptum will be handed out for a part of the course. Copies of the slides will be available for download. We will also provide a detailed list of references and textbooks. | |||||
| Literature | Markus Gross: Computer Graphics, scriptum, 1994-2005 | |||||
| 151-0107-20L | High Performance Computing for Science and Engineering (HPCSE) I | W | 4 credits | 4G | M. Troyer, P. Chatzidoukas | |
| Abstract | This course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering. | |||||
| Learning objective | Introduction to HPC for scientists and engineers Fundamental of: 1. Parallel Computing Architectures 2. MultiCores 3. ManyCores | |||||
| Content | Programming models and languages: 1. C++ threading (2 weeks) 2. OpenMP (4 weeks) 3. MPI (5 weeks) Computers and methods: 1. Hardware and architectures 2. Libraries 3. Particles: N-body solvers 4. Fields: PDEs 5. Stochastics: Monte Carlo | |||||
| Lecture notes | http://www.cse-lab.ethz.ch/index.php/teaching/42-teaching/classes/615-hpcse1 Class notes, handouts | |||||
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