Project description
Energy-efficient AI at the edge
Edge computing can lead to deployment of AI in devices like drones, augmented reality and virtual reality gear, or autonomous vehicles, and give rise to transformative applications. However, the energy demands of AI create a major bottleneck, hindering advancements in such applications and related industries. In this context, the EIC-funded CERBERUS project aims to transform in-memory computing, which is designed to boost AI efficiency by processing data directly in memory. CERBERUS targets overcoming key efficiency hurdles through improvements in memristive devices, optimising peripheral circuits and enhancing heat dissipation solutions. Overall, the project’s goal is to triple energy efficiency. This will allow powerful AI models to run on even the smallest edge devices.
Objective
The introduction of the on-device AI paradigm in edge computing could bring significant benefits and enable a plethora of exciting applications in AR/VR gear, industrial automation devices, drones, 5G/6G base stations or autonomous vehicles. However, AI is well-known to be generally power hungry and edge devices are not able to withstand the computational requirements of emerging AI workloads. Therefore, energy efficiency is closing the door important breakthroughs across industries such as ICT, mobility, healthcare, agri-food, industrial automation, leaving an enormous untapped potential behind. To remedy this, academia and industry have proposed in-memory computing (IMC) and the associated non-Von Neumann architectures as a means to dramatically improve the efficiency of AI processing; yet the promise of the IMC paradigm is limited by non-idealities within and around the IMC tiles.
In this light, the CERBERUS project aims to take a radical step forward in the field of IMC by addressing the fundamental efficiency bottlenecks that prevent edge computing stakeholders from unleashing the full potential of this technology. To this end, CERBERUS will employ a three-pillar approach grounded on (i) 2× more efficient memristive devices, (ii) 30% more efficient peripheral circuits also allowing to bypass domain conversions, and (iii) 70% more effective heat dissipation devices to virtually eliminate thermal noise. Thanks to a deeply cross-layer simulation approach integrating models of the developed devices and circuits, our ultimate goal is to show that 3X better energy efficiency can be achieved at the system level for modern and emerging edge AI computing workloads, towards the vision of deploying sizable AI models in virtually any device, even at the extreme edge.
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: The European Science Vocabulary.
This project's classification has been validated by the project's team.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware computer processors
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering analogue electronics
- engineering and technology nanotechnology nanoelectronics
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC - HORIZON EIC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2024-PATHFINDERCHALLENGES-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
08034 BARCELONA
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.