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P&S: Neural Network on Low Power FPGA: A Practical Approach
Last Updated: 2026-06-03 00:14:19
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.
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Semesterly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
- Signup Start
- 13.02.2026
- Signup End
- 27.02.2026
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| practical/laboratory course |
P&S: Neural Network on Low Power FPGA: A Practical Approach
Does not take place this semester.
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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):
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.
|
No time listed | 2 h weekly |
Offered In
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Laboratory Courses, Projects, Seminars (A minimum of 15 cp must be achieved in the category "Laboratory Courses, Projects, Seminars")
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Projects & Seminars (only for BSc EEIT) (Enrolment is only possible for students in the BSc Electrical Engineering and Information Technology, from Friday before the start of the semester. Places are allocated using the P&S application tool ( ). For more offers, see "Projects & Seminars (open to all)".)
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