227-0085-06L Projects & Seminars: Neural Network on Low Power FPGA: A Practical Approach
Semester | Spring Semester 2021 |
Lecturers | |
Periodicity | every semester recurring course |
Course | Does not take place this semester. |
Language of instruction | English |
Comment | Only for Electrical Engineering and Information Technology BSc. The course unit can only be taken once. Repeated enrollment in a later semester is not creditable. |
Courses
Number | Title | Hours | Lecturers | |
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227-0085-06 P | Projekte & Seminare: Neural Network on Low Power FPGA: A Practical Approach
Does not take place this semester. Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account): Link Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitag im Semester mittags möglich. To access the offer and to enroll for courses log in (with your n.ethz account): Link Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester. Zeit: Dienstag, 16:00 - 18:30 Uhr. | 2 hrs |
Catalogue data
Abstract | The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work. |
Objective | Artifical Intelligence and in particular neural networks are inspired by biological systems, such as the human brain. Through the combination of powerful computing resources and novel architectures for neurons, neural networks have achieved state-of-the-art results in many domains such as computer vision. FPGAs are one of the most powerful platform to implement neural networks as they can handle different algorithms in computing, logic, and memory resources in the same device. Faster performance comparing to competitive implementations as the user can hardcore operations into the hardware. This course will give to the student the basis of Machine Learning to understand how they work and how they can be trained and giving hand-on experiences with the training tools such as Keras. Moreover the course will focus in deploy algorithms in low power FPGA such as the Lattice sensAI platform to have energy efficient running algorithms. The course will provide to the students the tools and know-how to implement neural netwok on an FPGA, and the student will challenge theirself in a 5 weeks piratical project that they will present at the end of the course. Experience in FPGA programming is desirable but not mandatory. The course will be taught in English. |
Performance assessment
Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
ECTS credits | 2 credits |
Examiners | M. Magno |
Type | ungraded semester performance |
Language of examination | English |
Repetition | Repetition only possible after re-enrolling for the course unit. |
Learning materials
No public learning materials available. | |
Only public learning materials are listed. |
Groups
No information on groups available. |
Restrictions
General | : Special students and auditors need a special permission from the lecturers |
Places | Limited number of places. Special selection procedure. |
Beginning of registration period | Registration possible from 19.02.2021 |
Priority | Registration for the course unit is only possible for the primary target group |
Primary target group | Electrical Engin. + Information Technology BSc (228000) |
Waiting list | until 12.03.2021 |
End of registration period | Registration only possible until 05.03.2021 |
Offered in
Programme | Section | Type | |
---|---|---|---|
Electrical Engineering and Information Technology Bachelor | Projects & Seminars | W |