Project description
Research explores how physics could do the heavy lifting in neural networks
The growing energy consumption of computing technologies has become an environmental concern, despite advancements in semiconductor technology. Current computing architectures remain energy-inefficient, primarily designed for specific tasks, and are vulnerable to noise, heat and variability. The ERC-funded THERMODON project embraces the concept of 'Let the physics do the computing' by utilising noise, heat and variabilities for energy-efficient computing. The research involves integrating thermodynamics with neuromorphic computing to develop an innovative architecture capable of thermodynamic computing and self-organisation. By applying thermodynamic principles to oscillatory neural networks, researchers will develop a novel computing paradigm that transforms the computing architecture into a dynamic, self-organising system that openly interacts with the environment.
Objective
There is a pressing need to address the power consumption of computing, which keeps rising to the point it has become an environmental concern. Despite the remarkable progress in semiconductor technology, computing architectures are still energy inefficient, engineered for deterministic tasks as well as susceptible to noise, heat, and variations. Instead of massively over-designing architectures to compute with an acceptable degree of reliability, this research aims to “let physics do the computing” and harness noise, heat and variabilities for energy efficient computing.
At the heart of the proposed paradigm is the thermodynamics of open systems entwined with neuromorphic computing. THERMODON aims to develop an unconventional neuromorphic architecture to thermodynamically compute and self-organize (“learn”). I hypothesize that the natural thermodynamics of appropriately engineered architecture can harness noise, heat, and variations to self-organize toward energy efficient “solutions” to “problems” posed by external potentials. I will develop such architecture with neuromorphic oscillatory neural networks that I master in my lab. This research aims to address how thermodynamic principles can be applied to oscillatory neural networks to derive learning rules that are unsupervised, continuously adapting and transforming the architecture into a dynamic “self-organizing” and “open interactive” system that learns, infers and interacts with the environment.
THERMODON will bring breakthrough innovations in thermodynamic computing models and AI-specialized hardware to enable online training and inference to intelligent systems. The interdisciplinary research in this project between neuromorphic computing and thermodynamics opens a new and exciting area in computer architecture, triggering a paradigm shift in edge AI computing as well as an immediate impact as a hardware accelerator platform.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesphysical sciencesthermodynamics
- natural sciencesphysical scienceselectromagnetism and electronicssemiconductivity
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
5612 AE Eindhoven
Netherlands