Suchergebnis: Katalogdaten im Herbstsemester 2021
Informatik Bachelor  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Basisprüfung | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 252-0025-01L | Diskrete Mathematik | O | 7 KP | 4V + 2U | U. Maurer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Inhalt: Mathematisches Denken und Beweise, Abstraktion. Mengen, Relationen (z.B. Aequivalenz- und Ordnungsrelationen), Funktionen, (Un-)abzählbarkeit, Zahlentheorie, Algebra (Gruppen, Ringe, Körper, Polynome, Unteralgebren, Morphismen), Logik (Aussagen- und Prädikatenlogik, Beweiskalküle). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Hauptziele der Vorlesung sind (1) die Einführung der wichtigsten Grundbegriffe der diskreten Mathematik, (2) das Verständnis der Rolle von Abstraktion und von Beweisen und (3) die Diskussion einiger Anwendungen, z.B. aus der Kryptographie, Codierungstheorie und Algorithmentheorie. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Siehe Kurzbeschreibung. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | vorhanden (englisch) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0027-00L | Einführung in die Programmierung  | O | 7 KP | 4V + 2U | T. Gross | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Einführung in grundlegende Konzepte der modernen Programmierung. Vermittlung der Fähigkeit, Programme von höchster Qualität zu entwickeln. Einführung in Prinzipien des Software Engineering mit objekt-orientiertem Ansatz. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Viele Menschen können Programme schreiben. Die Ziele der Vorlesung "Einführung in die Programmierung" gehen aber darüber hinaus: sie lehrt die fundamentalen Konzepte und Fertigkeiten, die nötig sind, um professionelle Programme zu erstellen. Nach erfolgreichem Abschluss der Vorlesung beherrschen Studenten die fundamentalen Kontrollstrukturen, Datenstrukturen, die Verfahren zur Problemlösung und Mechanismen von Programmiersprachen, die die moderne Programmierung auszeichnen. Sie kennen die Grundregeln für die Produktion von Software in hoher Qualität. Sie haben die nötigen Vorkenntnisse für weiterführende Vorlesungen, die das Programmieren in spezialisierten Anwendungsgebieten vorstellen. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Grundlagen der objekt-orientierten Programmierung. Objekte und Klassen. Vor- und Nachbedingungen, Invarianten, Design by Contract. Elementare Kontrollstrukturen. Zuweisungen und Referenzierung. Elementare Datenstrukturen und Algorithmen. Rekursion. Vererbung und Interfaces, Grundkonzepte aus Software Engineering wie dem Softwareprozess, Spezifikation und Dokumentation, Debugging, Reuse und Quality Assurance. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Die Vorlesungsfolien werden auf der Vorlesungswebseite zum Download zur Verfügung gestellt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Weitere Literaturangaben auf der Web Seite der Vorlesung. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Die Vorlesung hat keine besonderen Voraussetzungen. Sie erwartet das gleichzeitige Belegen der anderen Informatik Vorlesungen des Basisjahres. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0026-00L | Algorithmen und Datenstrukturen | O | 7 KP | 3V + 2U + 1A | M. Püschel, D. Steurer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The Kurs behandelt die Grundlagen des Entwurfs und der Analyse von Algorithmen und Datenstrukturen. Diese werden anhand von klassischen algorithmischen Problemen einschliesslich Graphenproblemen studiert. Die dazu nötige Einführung in die Graphentheorie ist ebenfalls Teil dieses Kurses. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Verständnis des Entwurfs und der Analyse grundlegender Algorithmen und Datenstrukturen. Verständnis der Grundlagen der Graphentheorie und einiger ihrere grundlegenden Algorithmen, | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Der Kurs ist eine Einführung in die Grundlagen des Designs and der Analyse von Algorithmen. Dazu gehören zum einen klassische Entwurfsmuster für Algorithmen wie Induktion, Divide-and-Conquer und dynamische Programmierung. Diese werden anhand von klassischen Problemen wie zum Beispiel Suchen und Sortieren studiert. Zum anderen geht es um das Zusammenspiel von Algorithmen und Datenstrukturen wie verkettete Listen, Suchbäumen, Heaps und Union-Find Strukturen. Ein besondere Fokus sind Graphenalgorithmen für Probleme wie kürzeste Wege und minimale Spannbäume. Die dazu notwendige erste Einführung in die Graphentheorie ist ebenfalls Teil der Vorlesung. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Ein vollständiges Skript in Deutsch ist in der Entwicklung und bereits als vollständiger Entwurf auf der Vorlesungswebseite verfügbar. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 401-0131-00L | Lineare Algebra | O | 7 KP | 4V + 2U | Ö. Imamoglu, O. Sorkine Hornung | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Einführung in die lineare Algebra (Vektorräume und lineare Abbildungen, Matrizen), Skalarprodukt, Determinanten, Matrixzerlegungen (LR-, QR-, Eigenwert- und Singulärwert-Zerlegung). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die Lernziele sind: - die fundamentalen Konzepte der linearen Algebra gut zu verstehen und anwenden zu können - Anwendungen der linearen Algebra kennenzulernen | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Lineare Algebra: Lineare Gleichungssysteme, Vektoren und Matrizen, Normen und Skalarprodukte, LR-Zerlegung, Vektorräume und lineare Abbildungen, kleinste Quadrate, QR-Zerlegung, Determinanten, Eigenwerte und Eigenvektoren, Singulärwertzerlegung, Anwendungen. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Einige Kapitel aus dem Skript "Lineare Algebra" (Gutknecht). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Empfehlungen auf der Homepage der Lehrveranstaltung | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Der relevante Schulstoff wird am Anfang kurz wiederholt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Basisprüfungsblock 2 Die Fächer des Blocks 2 werden im Frühjahrsemester angeboten. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Grundlagenfächer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0057-00L | Theoretische Informatik | O | 7 KP | 4V + 2U | J. Hromkovic, H.‑J. Böckenhauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Konzepte zur Beantwortung grundlegender Fragen wie: a) Was ist völlig automatisiert machbar (algorithmisch lösbar) b) Wie kann man die Schwierigkeit von Aufgaben (Problemen) messen? c) Was ist Zufall und wie kann er nützlich sein? d) Was ist Nichtdeterminisus und welche Rolle spielt er in der Informatik? e) Wie kann man unendliche Objekte durch Automaten und Grammatiken endlich darstellen? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Vermittlung der grundlegenden Konzepte der Informatik in ihrer geschichtlichen Entwicklung | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Die Veranstaltung ist eine Einführung in die Theoretische Informatik, die die grundlegenden Konzepte und Methoden der Informatik in ihrem geschichtlichen Zusammenhang vorstellt. Wir präsentieren Informatik als eine interdisziplinäre Wissenschaft, die auf einer Seite die Grenzen zwischen Möglichem und Unmöglichem und die quantitativen Gesetze der Informationsverarbeitung erforscht und auf der anderen Seite Systeme entwirft, analysiert, verifiziert und implementiert. Die Hauptthemen der Vorlesung sind: - Alphabete, Wörter, Sprachen, Messung der Informationsgehalte von Wörtern, Darstellung von algorithmischen Aufgaben - endliche Automaten, reguläre und kontextfreie Grammatiken - Turingmaschinen und Berechenbarkeit - Komplexitätstheorie und NP-Vollständigkeit - Algorithmenentwurf für schwere Probleme | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Die Vorlesung ist detailliert durch das Lehrbuch "Theoretische Informatik" bedeckt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Basisliteratur: 1. J. Hromkovic: Theoretische Informatik. 5. Auflage, Springer Vieweg 2014. 2. J. Hromkovic: Theoretical Computer Science. Springer 2004. Weiterführende Literatur: 3. M. Sipser: Introduction to the Theory of Computation, PWS Publ. Comp.1997 4. J.E. Hopcroft, R. Motwani, J.D. Ullman: Einführung in die Automatentheorie, Formale Sprachen und Komplexitätstheorie. Pearson 2002. 5. I. Wegener: Theoretische Informatik. Teubner Weitere Übungen und Beispiele: 6. A. Asteroth, Ch. Baier: Theoretische Informatik | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Während des Semesters werden zwei freiwillige Probeklausuren gestellt. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0061-00L | Systems Programming and Computer Architecture | O | 7 KP | 4V + 2U | T. Roscoe, A. Klimovic | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Introduction to systems programming. C and assembly language, floating point arithmetic, basic translation of C into assembler, compiler optimizations, manual optimizations. How hardware features like superscalar architecture, exceptions and interrupts, caches, virtual memory, multicore processors, devices, and memory systems function and affect correctness, performance, and optimization. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The course objectives are for students to: 1. Develop a deep understanding of, and intuition about, the execution of all the layers (compiler, runtime, OS, etc.) between programs in high-level languages and the underlying hardware: the impact of compiler decisions, the role of the operating system, the effects of hardware on code performance and scalability, etc. 2. Be able to write correct, efficient programs on modern hardware, not only in C but high-level languages as well. 3. Understand Systems Programming as a complement to other disciplines within Computer Science and other forms of software development. This course does not cover how to design or build a processor or computer. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course provides an overview of "computers" as a platform for the execution of (compiled) computer programs. This course provides a programmer's view of how computer systems execute programs, store information, and communicate. The course introduces the major computer architecture structures that have direct influence on the execution of programs (processors with registers, caches, other levels of the memory hierarchy, supervisor/kernel mode, and I/O structures) and covers implementation and representation issues only to the extend that they are necessary to understand the structure and operation of a computer system. The course attempts to expose students to the practical issues that affect performance, portability, security, robustness, and extensibility. This course provides a foundation for subsequent courses on operating systems, networks, compilers and many other courses that require an understanding of the system-level issues. Topics covered include: machine-level code and its generation by optimizing compilers, address translation, input and output, trap/event handlers, performance evaluation and optimization (with a focus on the practical aspects of data collection and analysis). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | - C programmnig - Integers - Pointers and dynamic memory allocation - Basic computer architecture - Compiling C control flow and data structures - Code vulnerabilities - Implementing memory allocation - Linking - Floating point - Optimizing compilers - Architecture and optimization - Caches - Exceptions - Virtual memory - Multicore - Devices | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | The course is based in part on "Computer Systems: A Programmer's Perspective" (3rd Edition) by R. Bryant and D. O'Hallaron, with additional material. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | 252-0029-00L Parallel Programming 252-0028-00L Design of Digital Circuits | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 401-0213-16L | Analysis II | O | 5 KP | 2V + 2U | M. Burger | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Differential- und Integralrechnung in mehreren Variablen, Vektoranalysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Für allgemeine Informationen, sehen Sie bitte die Webseite der Vorlesung | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 401-0663-00L | Numerical Methods for Computer Science | O | 7 KP | 2V + 2U + 2P | R. Hiptmair | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course gives an introduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology. The course focuses on fundamental ideas and algorithmic aspects of numerical methods. The exercises involve actual implementation of numerical methods in C++. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | * Knowledge of the fundamental algorithms in numerical mathematics * Knowledge of the essential terms in numerical mathematics and the techniques used for the analysis of numerical algorithms * Ability to choose the appropriate numerical method for concrete problems * Ability to interpret numerical results * Ability to implement numerical algorithms afficiently | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | * Computing with Matrices and Vectors 2.1 Fundamentals 2.2 Software and Libraries 2.4 Computational Effort 2.5 Machine Arithmetic and Consequences * Direct Methods for (Square) Linear Systems of Equations 3.1 Introduction: Linear Systems of Equations (LSE) 3.2 Theory: Linear Systems of Equations (LSE) 3.5 Survey: Elimination Solvers for Linear Systems of Equations 3.7 Sparse Linear Systems * Direct Methods for Linear Least Squares Problems 4.1 Least Squares Solution Concepts 4.2 Normal Equation Methods 4.3 Orthogonal Transformation Methods 4.3.1 Transformation Idea 4.3.2 Orthogonal/Unitary Matrices 4.3.3 QR-Decomposition 4.3.4 QR-Based Solver for Linear Least Squares Problems 4.4 Singular Value Decomposition (SVD) 4.5 SVD-Based Optimization and Approximation * Filtering Algorithms 5.1 Filters and Convolutions 5.2 Discrete Fourier Transform (DFT) 5.3 Fast Fourier Transform (FFT) * Machine Learning of One-Dimensional Data (Data Interpolation and Data Fitting in 1D) 6.1 Abstract Interpolation (AI) 6.2 Global Polynomial Interpolation 6.4 Splines 6.7 Least Squares Data Fitting * Iterative Methods for Non-Linear Systems of Equations 9.2 Iterative Methods 9.4 Finding Zeros of Scalar Functions 9.5 Newton's Method in Rn 9.7 Non-linear Least Squares | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture materials (PDF documents and codes) will be made available to the participants through the course web page and online repositories. Access information will be communicated in the beginning of the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | U. ASCHER AND C. GREIF, A First Course in Numerical Methods, SIAM, Philadelphia, 2011. A. QUARTERONI, R. SACCO, AND F. SALERI, Numerical mathematics, vol. 37 of Texts in Applied Mathematics, Springer, New York, 2000. W. Dahmen, A. Reusken "Numerik für Ingenieure und Naturwissenschaftler", Springer 2006. W. Gander, M.J. Gander, and F. Kwok "Scientific Computing", Springer 2014. M. Hanke-Bourgeois "Grundlagen der Numerischen Mathematik und des wissenschaftlichen Rechnens", BG Teubner, 2002 P. Deuflhard and A. Hohmann, "Numerische Mathematik I", DeGruyter, 2002 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | The course will be accompanied by programming exercises in C++ relying on the template library EIGEN. Familiarity with C++, object oriented and generic programming is an advantage. Participants of the course are expected to learn C++ by themselves, in case they do not know it already. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| Kernfächer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Vertiefung Information and Data Processing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0206-00L | Visual Computing | O | 8 KP | 4V + 3U | S. Coros, M. Pollefeys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Markus Gross: Computer Graphics, scriptum, 1994-2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Vertiefung Theoretical Computer Science | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0209-00L | Algorithms, Probability, and Computing | O | 8 KP | 4V + 2U + 1A | B. Gärtner, M. Ghaffari, R. Kyng, A. Steger, D. Steurer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Advanced design and analysis methods for algorithms and data structures: Random(ized) Search Trees, Point Location, Minimum Cut, Linear Programming, Randomized Algebraic Algorithms (matchings), Probabilistically Checkable Proofs (introduction). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Studying and understanding of fundamental advanced concepts in algorithms, data structures and complexity theory. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Will be handed out. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Introduction to Algorithms by T. H. Cormen, C. E. Leiserson, R. L. Rivest; Randomized Algorithms by R. Motwani und P. Raghavan; Computational Geometry - Algorithms and Applications by M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Vertiefung Systems and Software Engineering | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0210-00L | Compiler Design | O | 8 KP | 4V + 3U | Z. Su | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course uses compilers as examples to expose students to modern software development techniques. Tentative topics include: compiler organization; lexical analysis; top-down and bottom-up parsing; symbol tables; semantic analysis; code generation; local and global optimization; register allocation; automatic memory management. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Learn principles of compiler design; gain practical experience designing and implementing a medium-scale software system. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course uses compilers as example to expose modern software development techniques. The course introduces the students to the fundamentals of compiler construction. Students will implement a simple yet complete compiler for an object-oriented programming language for a realistic target machine. Students will learn the use of appropriate tools. Throughout the course, students learn to apply their knowledge of theory (automata, grammars, stack machines, program transformation) and well-known programming techniques (module definitions, design patterns, frameworks, software reuse) in a software project. A tentative list of topics: compiler organization; lexical analysis; top-down and bottom-up parsing; symbol tables; semantic analysis; code generation; local and global optimization; register allocation; automatic memory management; optional advanced topics if/when time permits. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Aho/Lam/Sethi/Ullmann, Compilers - Principles, Techniques, and Tools (2nd Edition) Muchnick, Advanced Compiler Design and Implementation, Morgan Kaufmann Publishers, 1997 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Prerequisites: Prior exposure to modern techniques for program construction, knowledge of at least one processor architecture at the assembly language level. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0217-00L | Computer Systems | O | 8 KP | 4V + 2U + 1A | T. Roscoe, S. Shinde, R. Wattenhofer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course is about real computer systems, and the principles on which they are designed and built. We cover both modern OSes and the large-scale distributed systems that power today's online services. We illustrate the ideas with real-world examples, but emphasize common theoretical results, practical tradeoffs, and design principles that apply across many different scales and technologies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The objective of the course is for students to understand the theoretical principles, practical considerations, performance tradeoffs, and engineering techniques on which the software underpinning almost all modern computer systems is based, ranging from single embedded systems-on-chip in mobile phones to large-scale geo-replicated groups of datacenters. By the end of the course, students should be able to reason about highly complex, real, operational software systems, applying concepts such as hierarchy, modularity, consistency, durability, availability, fault-tolerance, and replication. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course subsumes the topics of both "operating systems" and "distributed systems" into a single coherent picture (reflecting the reality that these disciplines are highly converged). The focus is system software: the foundations of modern computer systems from mobile phones to the large-scale geo-replicated data centers on which Internet companies like Amazon, Facebook, Google, and Microsoft are based. We will cover a range of topics, such as: scheduling, network protocol stacks, multiplexing and demultiplexing, operating system structure, inter-process communication, memory managment, file systems, naming, dataflow, data storage, persistence, and durability, computer systems performance, remove procedure call, consensus and agreement, fault tolerance, physical and logical clocks, virtualization, and blockchains. The format of the course is a set of about 25 topics, each covered in a lecture. A script will be published online ahead of each lecture, and the latter will consist of an interactive elaboration of the material in the script. There is no book for the course, but we will refer to books and research papers throughout to provide additional background and explanation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | We will assume knowlege of the "Systems Programming" and "Computer Networks" courses (or equivalent), and their prerequisites, and build upon them. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Wahlfächer Es können auch Lehrveranstaltungen aus dem Master-Studiengang in Informatik gewählt werden. Es liegt in der Verantwortung der Studierenden, sicherzustellen, dass sie die Voraussetzungen für diese Lehrveranstaltungen erfüllen. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-0293-00L | Wireless Networking and Mobile Computing | W | 4 KP | 2V + 1U | S. Mangold | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course gives an overview about wireless standards and summarizes the state of art for Wi-Fi 802.11, Cellular 5G, and Internet-of-Things, including new topics such as contact tracing with Bluetooth, audio communication, cognitive radio, visible light communications. The course combines lectures with a set of assignments in which students are asked to work with a JAVA simulation tool. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The objective of the course is to learn about the general principles of wireless communications, including physics, frequency spectrum regulation, and standards. Further, the most up-to-date standards and protocols used for wireless LAN IEEE 802.11, Wi-Fi, Internet-of-Things, sensor networks, cellular networks, visible light communication, and cognitive radios, are analyzed and evaluated. Students develop their own add-on mobile computing algorithms to improve the behavior of the systems, using a Java-based event-driven simulator. We also hand out embedded systems that can be used for experiments for optical communication. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | New: Starting 2020, we will address contact tracing, radio link budget, location distance measurements, and Bluetooth in more depth. Wireless Communication, Wi-Fi, Contact Tracing, Bluetooth, Internet-of-Things, 5G, Standards, Regulation, Algorithms, Radio Spectrum, Cognitive Radio, Mesh Networks, Optical Communication, Visible Light Communication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | The course material will be made available by the lecturer. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | (1) The course webpage (look for Stefan Mangold's site) (2) The Java 802 protocol emulator "JEmula802" from https://bitbucket.org/lfield/jemula802 (3) WALKE, B. AND MANGOLD, S. AND BERLEMANN, L. (2006) IEEE 802 Wireless Systems Protocols, Multi-Hop Mesh/Relaying, Performance and Spectrum Coexistence. New York U.S.A.: John Wiley & Sons. Nov 2006. (4) BERLEMANN, L. AND MANGOLD, S. (2009) Cognitive Radio for Dynamic Spectrum Access . New York U.S.A.: John Wiley & Sons. Jan 2009. (5) MANGOLD, S. ET.AL. (2003) Analysis of IEEE 802.11e for QoS Support in Wireless LANs. IEEE Wireless Communications, vol 10 (6), 40-50. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Students should have interest in wireless communication, and should be familiar with Java programming. Experience with GNU Octave or Matlab will help too (not required). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-3110-00L | Human Computer Interaction Number of participants limited to 150. | W | 6 KP | 2V + 1U + 2A | O. Hilliges, C. Holz | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course provides an introduction to the field of human-computer interaction, emphasising the central role of the user in system design. Through detailed case studies, students will be introduced to different methods used to analyse the user experience and shown how these can inform the design of new interfaces, systems and technologies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The goal of the course is that students should understand the principles of user-centred design and be able to apply these in practice. As well as understand the basic notions of Computational Design in a HCI context. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The course will introduce students to various methods of analysing the user experience, showing how these can be used at different stages of system development from requirements analysis through to usability testing. Students will get experience of designing and carrying out user studies as well as analysing results. The course will also cover the basic principles of interaction design. Practical exercises related to touch and gesture-based interaction will be used to reinforce the concepts introduced in the lecture. To get students to further think beyond traditional system design, we will discuss issues related to ambient information and awareness. The course website can be found here: https://teaching.siplab.org/human_computer_interaction/2021/ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0107-20L | High Performance Computing for Science and Engineering (HPCSE) I | W | 4 KP | 4G | P. Koumoutsakos, S. M. Martin | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This course gives an introduction into algorithms and numerical methods for parallel computing on shared and distributed memory architectures. The algorithms and methods are supported with problems that appear frequently in science and engineering. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | With manufacturing processes reaching its limits in terms of transistor density on today’s computing architectures, efficient utilization of computing resources must include parallel execution to maintain scaling. The use of computers in academia, industry and society is a fundamental tool for problem solving today while the “think parallel” mind-set of developers is still lagging behind. The aim of the course is to introduce the student to the fundamentals of parallel programming using shared and distributed memory programming models. The goal is on learning to apply these techniques with the help of examples frequently found in science and engineering and to deploy them on large scale high performance computing (HPC) architectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 1. Hardware and Architecture: Moore’s Law, Instruction set architectures (MIPS, RISC, CISC), Instruction pipelines, Caches, Flynn’s taxonomy, Vector instructions (for Intel x86) 2. Shared memory parallelism: Threads, Memory models, Cache coherency, Mutual exclusion, Uniform and Non-Uniform memory access, Open Multi-Processing (OpenMP) 3. Distributed memory parallelism: Message Passing Interface (MPI), Point-to-Point and collective communication, Blocking and non-blocking methods, Parallel file I/O, Hybrid programming models 4. Performance and parallel efficiency analysis: Performance analysis of algorithms, Roofline model, Amdahl’s Law, Strong and weak scaling analysis 5. Applications: HPC Math libraries, Linear Algebra and matrix/vector operations, Singular value decomposition, Neural Networks and linear autoencoders, Solving partial differential equations (PDEs) using grid-based and particle methods | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | https://www.cse-lab.ethz.ch/teaching/hpcse-i_hs21/ Class notes, handouts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | • An Introduction to Parallel Programming, P. Pacheco, Morgan Kaufmann • Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein, CRC Press • Computer Organization and Design, D.H. Patterson and J.L. Hennessy, Morgan Kaufmann • Vortex Methods, G.H. Cottet and P. Koumoutsakos, Cambridge University Press • Lecture notes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Students should be familiar with a compiled programming language (C, C++ or Fortran). Exercises and exams will be designed using C++. The course will not teach basics of programming. Some familiarity using the command line is assumed. Students should also have a basic understanding of diffusion and advection processes, as well as their underlying partial differential equations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0124-00L | Embedded Systems | W | 6 KP | 4G | L. Thiele, M. Magno | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | An embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. The course covers theoretical and practical aspects of embedded system design and includes a series of lab sessions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Understanding specific requirements and problems arising in embedded system applications. Understanding architectures and components, their hardware-software interfaces, the memory architecture, communication between components, embedded operating systems, real-time scheduling theory, shared resources, low-power and low-energy design as well as hardware architecture synthesis. Using the formal models and methods in embedded system design in practical applications using the programming language C, the operating system FreeRTOS, a commercial embedded system platform and the associated design environment. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | An embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. For example, they are part of industrial machines, agricultural and process industry devices, automobiles, medical equipment, cameras, household appliances, airplanes, sensor networks, internet-of-things, as well as mobile devices. The focus of this lecture is on the design of embedded systems using formal models and methods as well as computer-based synthesis methods. Besides, the lecture is complemented by laboratory sessions where students learn to program in C, to base their design on the embedded operating systems FreeRTOS, to use a commercial embedded system platform including sensors, and to edit/debug via an integrated development environment. Specifically the following topics will be covered in the course: Embedded system architectures and components, hardware-software interfaces and memory architecture, software design methodology, communication, embedded operating systems, real-time scheduling, shared resources, low-power and low-energy design, hardware architecture synthesis. More information is available at https://www.tec.ee.ethz.ch/education/lectures/embedded-systems.html . | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | The following information will be available: Lecture material, publications, exercise sheets and laboratory documentation at https://www.tec.ee.ethz.ch/education/lectures/embedded-systems.html . | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | P. Marwedel: Embedded System Design, Springer, ISBN 978-3-319-56045-8, 2018. G.C. Buttazzo: Hard Real-Time Computing Systems. Springer Verlag, ISBN 978-1-4614-0676-1, 2011. Edward A. Lee and Sanjit A. Seshia: Introduction to Embedded Systems, A Cyber-Physical Systems Approach, Second Edition, MIT Press, ISBN 978-0-262-53381-2, 2017. M. Wolf: Computers as Components – Principles of Embedded System Design. Morgan Kaufman Publishers, ISBN 978-0-128-05387-4, 2016. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Prerequisites: Basic knowledge in computer architectures and programming. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-1037-00L | Introduction to Neuroinformatics | W | 6 KP | 2V + 1U + 1A | V. Mante, M. Cook, B. Grewe, G. Indiveri, D. Kiper, W. von der Behrens | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course provides an introduction to the functional properties of neurons. Particularly the description of membrane electrical properties (action potentials, channels), neuronal anatomy, synaptic structures, and neuronal networks. Simple models of computation, learning, and behavior will be explained. Some artificial systems (robot, chip) are presented. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Understanding computation by neurons and neuronal circuits is one of the great challenges of science. Many different disciplines can contribute their tools and concepts to solving mysteries of neural computation. The goal of this introductory course is to introduce the monocultures of physics, maths, computer science, engineering, biology, psychology, and even philosophy and history, to discover the enchantments and challenges that we all face in taking on this major 21st century problem and how each discipline can contribute to discovering solutions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | This course considers the structure and function of biological neural networks at different levels. The function of neural networks lies fundamentally in their wiring and in the electro-chemical properties of nerve cell membranes. Thus, the biological structure of the nerve cell needs to be understood if biologically-realistic models are to be constructed. These simpler models are used to estimate the electrical current flow through dendritic cables and explore how a more complex geometry of neurons influences this current flow. The active properties of nerves are studied to understand both sensory transduction and the generation and transmission of nerve impulses along axons. The concept of local neuronal circuits arises in the context of the rules governing the formation of nerve connections and topographic projections within the nervous system. Communication between neurons in the network can be thought of as information flow across synapses, which can be modified by experience. We need an understanding of the action of inhibitory and excitatory neurotransmitters and neuromodulators, so that the dynamics and logic of synapses can be interpreted. Finally, the neural architectures of feedforward and recurrent networks will be discussed in the context of co-ordination, control, and integration of sensory and motor information in neural networks. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 402-0209-00L | Quantum Physics for Non-Physicists | W | 6 KP | 3V + 2U | L. Pacheco Cañamero B. del Rio | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | This is an introduction to the physics of quantum mechanics, aimed primarily at students with little to no background in physics. We start from the basic postulates and follow an information-theoretical approach to study the behaviour of quantum systems, from a single spin to entangled particles in space and the hydrogen atom. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | This course teaches the basics of quantum physics, and complements courses in quantum computation and information theory. Students are equipped with tools to tackle complex quantum mechanical problems and foundational questions. The course covers approximately the same content as QM1, but from an information-driven perspective. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 1. Quantum formalism, from qubits to particles in space 2. Time and dynamics for quantum systems 3. Problems in 1D 4. Uncertainty and open systems 5. Spin 6. Problems in 3D 7. Non-locality and foundational aspects of quantum theory | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture notes will be distributed through the semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Quantum Processes Systems, and Information, by Benjamin Schumacher and Michael Westmoreland, available at Link | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | This course is aimed at non-physicists, and in particular at students with a background in computer science, mathematics or engineering. Basic linear algebra and calculus knowledge is required (equivalent to first-year courses). Physics knowledge is not required. Physicists and students from a different background than outlined above are welcome at their own risk. Note that while we follow an information-theoretical approach, this is not a course on quantum information theory or quantum computing. It therefore complements those courses offered at ETH in both semesters. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-2300-00L | Dependency Structures and Lexicalized Grammars 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. Number of participants limited to 25. | W | 2 KP | 2S | R. Cotterell | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Dependency parsing is a fundamental task in natural language processing. This seminar explores a variety of algorithms for efficient dependency parsing and their derivatioin in a unified algebraic framework. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The core ideas behind the mathematics of dependency parsing are explored. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Dependency Structures and Lexicalized Grammars: An Algebraic Approach | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 252-2600-05L | Software Engineering Seminar 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. | W | 2 KP | 2S | Z. Su, M. Vechev | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The course is an introduction to research in software engineering, based on reading and presenting high quality research papers in the field. The instructor may choose a variety of topics or one topic that is explored through several papers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The main goals of this seminar are 1) learning how to read and understand a recent research paper in computer science; and 2) learning how to present a technical topic in computer science to an audience of peers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The technical content of this course falls into the general area of software engineering but will vary from semester to semester. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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