Gustavo Alonso: Katalogdaten im Herbstsemester 2020 |
| Name | Herr Prof. Dr. Gustavo Alonso |
| Lehrgebiet | Informatik |
| Adresse | Institut für Computing Platforms ETH Zürich, STF K 513 Stampfenbachstrasse 114 8092 Zürich SWITZERLAND |
| Telefon | +41 44 632 73 06 |
| alonso@inf.ethz.ch | |
| URL | http://www.inf.ethz.ch/~alonso |
| Departement | Informatik |
| Beziehung | Ordentlicher Professor |
| Nummer | Titel | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|
| 252-0817-00L | Distributed Systems Laboratory Gilt nur für MSc-Reglement 09: 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. | 10 KP | 9P | G. Alonso, T. Hoefler, A. Klimovic, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang | |
| Kurzbeschreibung | This 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. | ||||
| Lernziel | Gain hands-on-experience with real products and the latest technology in distributed systems. | ||||
| Inhalt | This 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. | ||||
| 263-3504-00L | Hardware Acceleration for Data Processing  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 KP | 2S | G. Alonso, A. Klimovic, C. Zhang | |
| Kurzbeschreibung | The seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular. | ||||
| Lernziel | The seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular. | ||||
| Inhalt | The general application areas are big data and machine learning. The systems covered will include systems from computer architecture, high performance computing, data appliances, and data centers. | ||||
| Voraussetzungen / Besonderes | Students taking this seminar should have the necessary background in systems and low level programming. | ||||
| 263-3845-00L | Data Management Systems | 8 KP | 3V + 1U + 3A | G. Alonso | |
| Kurzbeschreibung | The course will cover the implementation aspects of data management systems using relational database engines as a starting point to cover the basic concepts of efficient data processing and then expanding those concepts to modern implementations in data centers and the cloud. | ||||
| Lernziel | The goal of the course is to convey the fundamental aspects of efficient data management from a systems implementation perspective: storage, access, organization, indexing, consistency, concurrency, transactions, distribution, query compilation vs interpretation, data representations, etc. Using conventional relational engines as a starting point, the course will aim at providing an in depth coverage of the latest technologies used in data centers and the cloud to implement large scale data processing in various forms. | ||||
| Inhalt | The course will first cover fundamental concepts in data management: storage, locality, query optimization, declarative interfaces, concurrency control and recovery, buffer managers, management of the memory hierarchy, presenting them in a system independent manner. The course will place an special emphasis on understating these basic principles as they are key to understanding what problems existing systems try to address. It will then proceed to explore their implementation in modern relational engines supporting SQL to then expand the range of systems used in the cloud: key value stores, geo-replication, query as a service, serverless, large scale analytics engines, etc. | ||||
| Literatur | The main source of information for the course will be articles and research papers describing the architecture of the systems discussed. The list of papers will be provided at the beginning of the course. | ||||