IEEE CASS RJ Chapter Lecture - Humans and Semiconductors Interface: Energy Efficiency and Edge Artificial Intelligence
Title
Humans and Semiconductors Interface: Energy Efficiency and Edge Artificial Intelligence
Abstract
Humans' and Semiconductors' relationship have reshaped history for the past five decades. From Moore's Law, the semiconductor industry has favored a fast and low-cost development of technology. During the crisis, supply chain ruptures and resource scarcity have changed such equilibrium. It is time for the microelectronic research field to bring out some paradigms breakthroughs in terms of extreme energy efficient systems and bringing artificial intelligence to the sensor's edge. This tutorial summarizes the state of the art in this field and brings some recent scientific results of our team. Few of them includes: (a) low area, low power eNeurons suitable for Spiking Neural Networks; (b) spiking frequency modulation over audio bandwidth suggesting a Smart IoT hearing; (c) spiking frequency responsiveness over input waves suggesting a Smart IoT vision; (d) deep learning and energy efficiency trade-offs in analog spiking neurons.
Short-bio
Pietro FERREIRA (IEEE S'03-SG'06-M'12-SM'18) received the B.Eng. cum lauda in Electronics and Computer Eng. in 2006 the M.Sc. in Microelectronics in 2008 from the Federal University of Rio de Janeiro (UFRJ), Brazil; and the Ph.D. degree in Communications and Electronics from the Télécom Paris, IPP, France. Researching high-performance high-reliability circuits and systems, he joined IM2NP lab. (UMR CNRS 7334) for one year and IEMN lab. (UMR CNRS 8520) for two years during his tenure track. Since 2014, he has been an Associate Professor at Université Paris-Saclay, CentraleSupélec, GeePs (UMR 8507), France. In 2019, he defended his Research Direction Project (HDR) in Physics from the Université Paris-Saclay. His research interest is design methodologies for harsh environments, microwave, and ultra-low power integrated circuits. Recent projects aim at the Internet of Things industry considering IA-edge and reliability.
Date and Time
Location
Hosts
Registration
- Date: 14 Dec 2022
- Time: 02:00 PM to 04:00 PM
- All times are (UTC-03:00) Brasilia
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- Cidade Universitária
- Centro de Tecnologia da UFRJ
- Rio de Janeiro, Rio de Janeiro
- Brazil
- Building: Bloco H
- Room Number: Sala 322
- Click here for Map
- Starts 07 December 2022 09:51 AM
- Ends 14 December 2022 02:00 PM
- All times are (UTC-03:00) Brasilia
- No Admission Charge
Speakers
Pietro Ferreira
Humans and Semiconductors Interface: Energy Efficiency and Edge Artificial Intelligence
Humans' and Semiconductors' relationship have reshaped history for the past five decades. From Moore's Law, the semiconductor industry has favored a fast and low-cost development of technology. During the crisis, supply chain ruptures and resource scarcity have changed such equilibrium. It is time for the microelectronic research field to bring out some paradigms breakthroughs in terms of extreme energy efficient systems and bringing artificial intelligence to the sensor's edge. This tutorial summarizes the state of the art in this field and brings some recent scientific results of our team. Few of them includes: (a) low area, low power eNeurons suitable for Spiking Neural Networks; (b) spiking frequency modulation over audio bandwidth suggesting a Smart IoT hearing; (c) spiking frequency responsiveness over input waves suggesting a Smart IoT vision; (d) deep learning and energy efficiency trade-offs in analog spiking neurons.
Biography:
Pietro FERREIRA (IEEE S'03-SG'06-M'12-SM'18) received the B.Eng. cum lauda in Electronics and Computer Eng. in 2006 the M.Sc. in Microelectronics in 2008 from the Federal University of Rio de Janeiro (UFRJ), Brazil; and the Ph.D. degree in Communications and Electronics from the Télécom Paris, IPP, France. Researching high-performance high-reliability circuits and systems, he joined IM2NP lab. (UMR CNRS 7334) for one year and IEMN lab. (UMR CNRS 8520) for two years during his tenure track. Since 2014, he has been an Associate Professor at Université Paris-Saclay, CentraleSupélec, GeePs (UMR 8507), France. In 2019, he defended his Research Direction Project (HDR) in Physics from the Université Paris-Saclay. His research interest is design methodologies for harsh environments, microwave, and ultra-low power integrated circuits. Recent projects aim at the Internet of Things industry considering IA-edge and reliability.