Summary
With the rise of deep learning (DL), our world braces for Artificial Intelligence (AI) in every edge device, creating an urgent need for edge-AI processing hardware. Unlike existing solutions, this hardware needs to support high throughput, reliable, and secure AI processing at ultra-low power (ULP), with a very short time to market.
With its strong legacy in edge solutions and open processing platforms, the EU is ideally positioned to become the leader in this edge-AI market. However, certain roadblocks keep the EU from assuming this leadership role: Edge processors need to become 100x more energy efficient; Their complexity demands automated design with 10x design time reduction; They must be secure and reliable to get accepted; Finally, they should be flexible and powerful to support the DL domain.
CONVOLVE addresses these roadblocks and thereby enables EU leadership in Edge-AI. To that end, it will take a holistic approach with innovations at all design stack levels, including:
1.ULP memristive circuits for computation-in-memory
2.Fast compositional design of System-on-Chips (SoC)
3.Transparent compilers supporting automated code optimizations and domain-specific languages
4.Rethinking DL models through dynamic neural networks, event-based execution, and sparsity
5.On-edge continuous learning for improved accuracy, self-healing, and reliable adaptation to non-stationary environments
6.Holistic integration in SoCs supporting secure execution with real-time guarantees
The CONVOLVE consortium includes some of Europe's strongest research groups and industries, covering the whole design stack and value chain. In a community effort, we will demonstrate Edge-AI computing in real-life vision and audio domains. By combining these innovative ULP and fast design solutions, CONVOLVE will, for the first time, enable reliable, smart, and energy-efficient edge-AI devices at a rapid time-to-market and low cost, and as such open the road for EU leadership in edge-processing.
With its strong legacy in edge solutions and open processing platforms, the EU is ideally positioned to become the leader in this edge-AI market. However, certain roadblocks keep the EU from assuming this leadership role: Edge processors need to become 100x more energy efficient; Their complexity demands automated design with 10x design time reduction; They must be secure and reliable to get accepted; Finally, they should be flexible and powerful to support the DL domain.
CONVOLVE addresses these roadblocks and thereby enables EU leadership in Edge-AI. To that end, it will take a holistic approach with innovations at all design stack levels, including:
1.ULP memristive circuits for computation-in-memory
2.Fast compositional design of System-on-Chips (SoC)
3.Transparent compilers supporting automated code optimizations and domain-specific languages
4.Rethinking DL models through dynamic neural networks, event-based execution, and sparsity
5.On-edge continuous learning for improved accuracy, self-healing, and reliable adaptation to non-stationary environments
6.Holistic integration in SoCs supporting secure execution with real-time guarantees
The CONVOLVE consortium includes some of Europe's strongest research groups and industries, covering the whole design stack and value chain. In a community effort, we will demonstrate Edge-AI computing in real-life vision and audio domains. By combining these innovative ULP and fast design solutions, CONVOLVE will, for the first time, enable reliable, smart, and energy-efficient edge-AI devices at a rapid time-to-market and low cost, and as such open the road for EU leadership in edge-processing.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101070374 |
| Start date: | 01-11-2022 |
| End date: | 31-10-2025 |
| Total budget - Public funding: | 7 918 201,25 Euro - 7 916 950,00 Euro |
Cordis data
Original description
With the rise of deep learning (DL), our world braces for Artificial Intelligence (AI) in every edge device, creating an urgent need for edge-AI processing hardware. Unlike existing solutions, this hardware needs to support high throughput, reliable, and secure AI processing at ultra-low power (ULP), with a very short time to market.With its strong legacy in edge solutions and open processing platforms, the EU is ideally positioned to become the leader in this edge-AI market. However, certain roadblocks keep the EU from assuming this leadership role: Edge processors need to become 100x more energy efficient; Their complexity demands automated design with 10x design time reduction; They must be secure and reliable to get accepted; Finally, they should be flexible and powerful to support the DL domain.
CONVOLVE addresses these roadblocks and thereby enables EU leadership in Edge-AI. To that end, it will take a holistic approach with innovations at all design stack levels, including:
1.ULP memristive circuits for computation-in-memory
2.Fast compositional design of System-on-Chips (SoC)
3.Transparent compilers supporting automated code optimizations and domain-specific languages
4.Rethinking DL models through dynamic neural networks, event-based execution, and sparsity
5.On-edge continuous learning for improved accuracy, self-healing, and reliable adaptation to non-stationary environments
6.Holistic integration in SoCs supporting secure execution with real-time guarantees
The CONVOLVE consortium includes some of Europe's strongest research groups and industries, covering the whole design stack and value chain. In a community effort, we will demonstrate Edge-AI computing in real-life vision and audio domains. By combining these innovative ULP and fast design solutions, CONVOLVE will, for the first time, enable reliable, smart, and energy-efficient edge-AI devices at a rapid time-to-market and low cost, and as such open the road for EU leadership in edge-processing.
Status
SIGNEDCall topic
HORIZON-CL4-2021-DIGITAL-EMERGING-01-01Update Date
09-02-2023
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Organisations
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| Eindhoven University of Technology (Coördinator)
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| AXELERA AI
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| COGNITIVEIC B.V.
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| CONFEDERATION DES LABORATOIRES DE RECHERCHE SUR L'INTELLIGENCE ARTIFICIELLE EN EUROPE
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| EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
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| FRIEDRICH MIESCHER INSTITUTE FOR BIOMEDICAL RESEARCH FONDATION
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| GN STORE NORD
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| INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS
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| KATHOLIEKE UNIVERSITEIT LEUVEN
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| NXP SEMICONDUCTORS GERMANY GMBH (NXP)
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| ROBERT BOSCH GMBH
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| RUHR-UNIVERSITAET BOCHUM
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| TECHNISCHE UNIVERSITEIT DELFT
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| THALES ALENIA SPACE ESPANA, SA (TAS-E)
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| THE UNIVERSITY OF EDINBURGH