Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Torsten Hoefler: Catalogue data in Autumn Semester 2018

Name Prof. Dr. Torsten Hoefler
FieldScalable Parallel Computing
Address
Inst. f. Hochleistungsrechnersyst.
ETH Zürich, CAB F 75
Universitätstrasse 6
8092 Zürich
SWITZERLAND
Telephone+41 44 632 63 44
E-mailtorsten.hoefler@inf.ethz.ch
URLhttp://htor.inf.ethz.ch
DepartmentComputer Science
RelationshipFull Professor

NumberTitleECTSHoursLecturers
252-0817-00LDistributed Systems Laboratory
In the Master Programme max.10 credits can be accounted by Labs on top of the Interfocus Courses. These Labs will only count towards the Master Programme. Additional Labs will be listed on the Addendum.
10 credits9PG. Alonso, T. Hoefler, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang
AbstractThis 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.
ObjectiveGain hands-on-experience with real products and the latest technology in distributed systems.
ContentThis 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.
263-2800-00LDesign of Parallel and High-Performance Computing Information 7 credits3V + 2U + 1AT. Hoefler, M. Püschel
AbstractAdvanced topics in parallel / concurrent programming.
ObjectiveUnderstand concurrency paradigms and models from a higher perspective and acquire skills for designing, structuring and developing possibly large concurrent software systems. Become able to distinguish parallelism in problem space and in machine space. Become familiar with important technical concepts and with concurrency folklore.
263-3504-00LHardware Acceleration for Data Processing Information
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 credits2SG. Alonso, T. Hoefler, C. Zhang
AbstractThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ObjectiveThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ContentThe 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.
Prerequisites / NoticeStudents taking this seminar should have the necessary background in systems and low level programming.