Markus Püschel: Catalogue data in Autumn Semester 2022 |  |
| Name | Prof. Dr. Markus Püschel |
| Field | Computer Science |
| Address | Dep. Informatik ETH Zürich, CAB H 69.3 Universitätstrasse 6 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 73 03 |
| pueschel@inf.ethz.ch | |
| URL | http://people.inf.ethz.ch/markusp/ |
| Department | Computer Science |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 252-0026-00L | Algorithms and Data Structures   | 7 credits | 3V + 2U + 1A | M. Püschel, D. Steurer | |
| Abstract | The course provides the foundation of the design and analysis of algorithms. The material is introduced using classical algorithmic problems including graph problems. The necessary basic introduction to graph theory is provided as part of this course. | ||||
| Learning objective | An understanding of the design and analysis of fundamental algorithms and data structures. A basic understanding of graph theory and several basic graph algorithms. | ||||
| Content | This course is an introduction into the design and analysis of algorithms. On the one hand this includes classical algorithm design patterns including induction, divide-and-conquer and dynamic programming. We study these using classical example such as searching and sorting. On the other hand the course covers the interaction between algorithms and data structures including linked lists, search trees, heaps, and union-find structures. A particular focus are graph algorithms for shortest path and minimal spanning tree problems. We provide the necessary introduction into graph theory as part of this course. | ||||
| Lecture notes | A complete script in German is under development. A complete draft is already available on the course website. | ||||
| Literature | Abgesehen vom Skript und Vorlesungsunterlagen empfehlen wir die folgenden Bücher als zusätzliches Nachschlagewerk. Th. Ottmann, P. Widmayer: Algorithmen und Datenstrukturen, Spektrum-Verlag, 5. Auflage, Heidelberg, Berlin, Oxford, 2011 Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein: An Introduction to Algorithms, 3rd edition, MIT Press, 2009 | ||||
| 263-2100-00L | Research Topics in Software Engineering Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | 2 credits | 2S | P. Müller, M. Püschel | |
| Abstract | This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research. | ||||
| Learning objective | Each student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis. Active participation is required (a presentation of a paper as well as participation in discussions). | ||||
| Content | The aim of this seminar is to introduce students to recent research results in the area of programming languages and software engineering. To accomplish that, students will study and present research papers in the area as well as participate in paper discussions. The papers will span topics in both theory and practice, including papers on program verification, program analysis, testing, programming language design, and development tools. A particular focus will be on domain-specific languages. | ||||
| Literature | The publications to be presented will be announced on the seminar home page at least one week before the first session. | ||||
| Prerequisites / Notice | Organizational note: the seminar will meet only when there is a scheduled presentation. Please consult the seminar's home page for information. | ||||
| 263-2800-00L | Design of Parallel and High-Performance Computing Number of participants limited to 125. | 9 credits | 3V + 2U + 3A | T. Hoefler, M. Püschel | |
| Abstract | Advanced topics in parallel and high-performance computing. | ||||
| Learning objective | Understand concurrency paradigms and models from a higher perspective and acquire skills for designing, structuring and developing possibly large parallel high-performance software systems. Become able to distinguish parallelism in problem space and in machine space. Become familiar with important technical concepts and with concurrency folklore. | ||||
| Content | We will cover all aspects of high-performance computing ranging from architecture through programming up to algorithms. We will start with a discussion of caches and cache coherence in practical computer systems. We will dive into parallel programming concepts such as memory models, locks, and lock-free. We will cover performance modeling and parallel design principles as well as basic parallel algorithms. | ||||
| Prerequisites / Notice | This class is intended for the Computer Science Masters curriculum. Students must have basic knowledge in programming in C as well as computer science theory. Students should be familiar with the material covered in the ETH computer science first-year courses "Parallele Programmierung (parallel programming)" and "Algorithmen und Datenstrukturen (algorithm and data structures)" or equivalent courses. | ||||