Timetable & learning outcomes
Artificial intelligence and deep learning applications currently require consequent amounts of computing resources that are not easily accessible for low-latency applications handling sensitive data. Massive data sources have to be pushed to multiple high-speed computers in remote server farms, raising serious concerns related to security and privacy. A possible solution comes from executing machine learning models on embedded devices, a topic generally known as “Embedded Artificial Intelligence”. This calls for a close integration of software and hardware solutions with highly optimised machine learning models and a new generation of lightweight, energy-efficient embedded hardware suitable for executing neural networks on edge devices.
The educational objectives of the summer school reflect the highly interdisciplinary nature of the Embedded Artificial Intelligence research theme, covering on the one hand topics related to fabrication, characterisation, modelling, design, simulation and exploration of neuromorphic devices; and on the other hand application-specific topics including speech and text processing, 6G communications, and radio frequency oscillators.
The core objective of the summer school is to
cover hardware-related aspects of neural networks while aiming to provide
participants with a basic understanding of neural network implementation. Topics
covered will include:
› Introductory aspects of neural networks
› Hardware enhancement using artificial intelligence
› Electrical characterization of functionality
› Logic cell design
› System simulation and exploration
› TCAD and compact modelling using 3D layout
› Fabrication of vertical Gate All Around (GAA) transistors
› Spintronics for hardware neural network accelerators
› 6G: design of transceivers implemented in an autonomous system
› Communications at sub-THz frequencies in CMOS technology
› Transformer architectures for machine translation and speech processing
› Applications in recognition of RF fingerprints and breast cancer
Tentative programme
Local and international experts from academia and industry will lead the plenary lecturers. A poster session will also be organised, allowing participants to present their research projects and discuss the connections with the summer school topics. Several practical sessions are also planned, during which participants will work with dedicated design software and visit the measurement laboratory.
Over the course of the programme, students learn in a variety of ways, starting with content related to technology layers, followed by circuit design and neural networks implementation, and ending with specific applications.
Please note: the schedule is presented in Central European Summer Time (CEST).
|
Monday June 23rd |
Tuesday June 24th |
Wednesday June 25th |
Thursday June 26th |
Friday June 27th |
| 9.00 – 10.00 Participants welcome |
09.00 – 10.00 Lecutre Advanced 3D fabrication techniques and processes Speaker TBD |
09.00 – 11.30 Hands-on session TCAD and DTCO tools Speaker TBD (GTS) |
09.00 – 12.30 Lecture Hardware software co-optimisations in efficient intelligence as the edge advance Speaker TBD (EFPL) |
10.00 – 12.00 AI memory and computing performances - P. conference - Project focus Speaker TBD (Fixit) |
| 10.00 – 11.00 The Fourth industrial revolution and engineer sciences Speaker TBD |
10.00 – 11.00 Coffee break |
10.00 - 11.00 Coffee break |
10.00 - 11.00 Coffee break |
10.00 - 11.00 Coffee break |
| 11.00 – 12.00 EU funded projects presentations Cristell Maneux |
11.00 – 12.00 Materials confrontation – Ferroelectric devices characterization Marc Bouquet |
11.00 – 12.00 Hands on session Cadence/EDA and DTCO tools trainings Speaker TBD (GTS) |
11.00 – 12.00 Lecture AI applications - Transformers, speech and language technologie Speaker TBD |
11.00 – 12.00 Roundtable Open discussion: Neuromorphic and remote technologies horizons Hussam Amrouch |
| 12.00 – 14.00 Lunch |
12.00 – 14.00 Lunch |
12.00 – 14.00 Lunch |
12.00 – 14.00 Lunch |
12.00 – 14.00 Farewell lunch |
| 14.00 - 15.00 Introduction Nanotechnologies and embedded AI Speakers TBD |
14.00 - 15.00 Hands on session Measurement techniques and practices Speakers TBD |
14.00 - 15.00 Lecture Deepen understanding of neural networks and neuromorphic architecture Speakers TBD |
14.00 – 15.00 FerroFutur: CEA-List: application datalogger Speaker TBD |
|
| 15.00 – 16.00 Coffee break |
15.00 – 16.00 Coffee break |
15.00 – 16.00 Coffee break |
15.00 – 16.00 Coffee break |
|
| 16.00 – 17.00 Technology development methodologies and process Speaker TBD |
16.00 – 17.00 Hands-on session Measurement techniques and practices Speakers TBD |
16.00 – 17.00 Hands-on session NN logic cells (design and architecture) Speakers TBD (INL) |
16.00 – 17.00 Participatory conference Low energy AI – Deep dive into Ferro4edge project Speaker TBD (Ferro4edge) |
|
| 18.00 Poster session - Networking |
18.00 Poster session - Networking |
18.00 Poster session - Networking |
Dinner |
A certificate of participation will be awarded to students upon completion of the course.
Programme may be subject to change.