Suchergebnis: Katalogdaten im Herbstsemester 2018

Informatik Master Information
Vertiefungsfächer
Vertiefung in Distributed Systems
Wahlfächer der Vertiefung in Distributed Systems
NummerTitelTypECTSUmfangDozierende
252-0437-00LVerteilte Algorithmen Information W4 KP3VF. Mattern
KurzbeschreibungModelle verteilter Berechnungen; Raum-Zeit Diagramme; Virtuelle Zeit; Logische Uhren und Kausalität; Wellenalgorithmen; Verteilte und parallele Graphtraversierung; Berechnung konsistenter Schnappschüsse; Wechselseitiger Ausschluss; Election und Symmetriebrechung; Verteilte Terminierung; Garbage-Collection in verteilten Systemen; Beobachten verteilter Systeme; Berechnung globaler Prädikate.
LernzielKennenlernen von Modellen und Algorithmen verteilter Systeme.
InhaltVerteilte Algorithmen sind Verfahren, die dadurch charakterisiert sind, dass mehrere autonome Prozesse gleichzeitig Teile eines gemeinsamen Problems in kooperativer Weise bearbeiten und der dabei erforderliche Informationsaustausch ausschliesslich über Nachrichten erfolgt. Derartige Algorithmen kommen im Rahmen verteilter Systeme zum Einsatz, bei denen kein gemeinsamer Speicher existiert und die Übertragungszeit von Nachrichten i.a. nicht vernachlässigt werden kann. Da dabei kein Prozess eine aktuelle konsistente Sicht des globalen Zustands besitzt, führt dies zu interessanten Problemen.
Im einzelnen werden u.a. folgende Themen behandelt:
Modelle verteilter Berechnungen; Raum-Zeit Diagramme; Virtuelle Zeit; Logische Uhren und Kausalität; Wellenalgorithmen; Verteilte und parallele Graphtraversierung; Berechnung konsistenter Schnappschüsse; Wechselseitiger Ausschluss; Election und Symmetriebrechung; Verteilte Terminierung; Garbage-Collection in verteilten Systemen; Beobachten verteilter Systeme; Berechnung globaler Prädikate.
Literatur- F. Mattern: Verteilte Basisalgorithmen, Springer-Verlag
- G. Tel: Topics in Distributed Algorithms, Cambridge University Press
- G. Tel: Introduction to Distributed Algorithms, Cambridge University Press, 2nd edition
- A.D. Kshemkalyani, M. Singhal: Distributed Computing, Cambridge University Press
- N. Lynch: Distributed Algorithms, Morgan Kaufmann Publ
252-0817-00LDistributed Systems Laboratory
Im Masterstudium können zusätzlich zu den Vertiefungsübergreifenden Fächern nur max. 10 Kreditpunkte über Laboratorien erarbeitet werden. Diese Labs gelten nur für das Masterstudium. Weitere Laboratorien werden auf dem Beiblatt aufgeführt.
W10 KP9PG. Alonso, T. Hoefler, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang
KurzbeschreibungThis course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including wireless networks, ad-hoc networks, RFID, and distributed applications on smartphones.
LernzielGain hands-on-experience with real products and the latest technology in distributed systems.
InhaltThis course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on smartphones. The goal of the project is for the students to gain hands-on-experience with real products and the latest technology in distributed systems. There is no lecture associated to the course.
For information of the course or projects available, see https://www.dsl.inf.ethz.ch/ or contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso.
263-2210-00LComputer Architecture Information W8 KP6G + 1AO. Mutlu
KurzbeschreibungComputer architecture is the science and art of selecting and interconnecting hardware components to create a computer that meets functional, performance and cost goals. This course introduces the basic components of a modern computing system (processors, memory, interconnects, storage). The course takes a hardware/software cooperative approach to understanding and evaluating computing systems.
LernzielWe will learn the fundamental concepts of the different parts of modern computing systems, as well as the latest trends by exploring the recent research in Industry and Academia. We will extensively cover memory technologies (including DRAM and new Non-Volatile Memory technologies), memory scheduling, parallel computing systems (including multicore processors and GPUs), heterogeneous computing, processing-in-memory, interconnection networks, etc.
InhaltThe principles presented in the lecture are reinforced in the laboratory through the design and simulation of a register transfer (RT) implementation of a MIPS-like pipelined processor in System Verilog. In addition, we will develop a cycle-accurate simulator of this processor in C, and we will use this simulator to explore processor design options.
SkriptAll the materials (including lecture slides) will be provided on the course website: https://safari.ethz.ch/architecture/
The video recordings of the lectures are expected to be made available after lectures.
LiteraturWe will provide required and recommended readings in every lecture. They will be mostly recent research papers presented in major Computer Architecture conferences and journals.
Voraussetzungen / BesonderesDesign of Digital Circuits
263-3850-00LInformal Methods Information W4 KP2G + 1AD. Cock
KurzbeschreibungFormal methods are increasingly a key part of the methodological toolkit of systems programmers - those writing operating systems, databases, and distributed systems. This course is about how to apply concepts, techniques, and principles from formal methods to such software systems, and how to get into the habit of thinking formally about systems design even when writing low-level C code.
LernzielThis course is about equipping students whose focus is systems with the insights and conceptual tools provided by formal methods, and therby enabling them to become better systems programmers.
By the end of the course, students should be able to seamlessly integrate basic concepts form formal methods into how they conceive, design, implement, reason about, and debug computer systems.

The goal is not to provide a comprehensive introduction to formal methods - this is well covered by other courses in the department. Instead, it is intended to provide students in computer systems (who may or may not have existing background knowledge of formal methods) with a basis for applying formal methods in their work.
InhaltThis course does not assume prior knowledge of formal methods, and will start with a quick review of topics such static vs. dynamic reasoning, variants and invariants, program algebra and refinement, etc. However, it is strongly recommended that students have already taken one of the introductory formal methods course at ETH (or equivalents elsewhere) before taking this course - the emphasis is on reinforcing these concepts by applying them, not to teach them from scratch.

Instead, the majority of the course will be about how to apply these techniques to actual, practical code in real systems. We will work from real systems code written both by students taking the course, and practical systems developed using formal techniques, in particular the verified seL4 microkernel will be a key case study. We will also focus on informal, pen-and-paper arguments for correctness of programs and systems rather than using theorem provers or automated verification tools; again these latter techniques are well covered in other courses (and recommended as a complement to this one).
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