Periodic Reporting for period 2 - SPIN-ION (Hybrid Spintronic Synapses for Neuromorphic Computing)
Reporting period: 2024-05-01 to 2025-10-31
The increasing scale of deep neural networks (DNN) and their growing application space have produced demand for more energy-efficient artificial-intelligence-specific hardware. In-Memory-Computing (IMC) approaches based on non-volatile technologies such as Magnetic Random-Access Memory (MRAM) can perfom computation within the memory eliminating completely data transfer. This approach, known as neuromorphic computing, results in a very high power efficiency for edge AI systems. At Spin-Ion Technologies we have developed a new manufacturing solution based on ion beam processes to precisely engineer magnetic properties of spintronic devices at the atomic scale. In this project, we will develop new IMC chips based on low power synapses and composed of MRAM devices customized by our ion beam process. This demonstrator will overcome both catastrophic forgetting (so-called metaplasticity) and reduce device variability, hence greatly advancing the development of highly efficient, robust hardware amenable to neural applications on the edge.
The project has shown very good technical and scientific progress within this 2nd reporting period. The main outcomes of the actions include :
-State of the art Magnetic Tunnel Junctions stacks with high perpendicular anisotropy and high Tunneling Magnetoresistance (WP1)
-Irradiated Magnetic Tunnel Junction stacks with modulated anisotropy (WP1)
-Higher structural quality of MTJ stacks crystallized by ion irradiation (WP1)
-Irradiated memory chips with low variability, modulated anisotropy and high TMR (WP1)
-Irradiated MTJ devices through a mask (WP2)
-Correction of edge damages in dense arrays of nanopillars (WP2)
-Incorporation of metaplasticity in Binary Neural Network algorithms (WP3)
-Developement of local learning algorithms (WP3)
-State of the art of 15X15 crosbar arrays including 25 nm MRAM cells (WP4)
-Demonstrator : all functional building blocks of the adaptative neuromorphic chip have been validated, including hardware demonstrations of on-chip learning and continual learning with numerically stored hidden weights, learning with discrete hidden-weight stored in hardware, and PMNIST continual-learning simulations incorporating real device measurements (WP4)
-State of the art Magnetic Tunnel Junctions stacks with high perpendicular anisotropy and high Tunneling Magnetoresistance (WP1)
-Irradiated Magnetic Tunnel Junction stacks with modulated anisotropy (WP1)
-Higher structural quality of MTJ stacks crystallized by ion irradiation (WP1)
-Irradiated memory chips with low variability, modulated anisotropy and high TMR (WP1)
-Irradiated MTJ devices through a mask (WP2)
-Correction of edge damages in dense arrays of nanopillars (WP2)
-Incorporation of metaplasticity in Binary Neural Network algorithms (WP3)
-Developement of local learning algorithms (WP3)
-State of the art of 15X15 crosbar arrays including 25 nm MRAM cells (WP4)
-Demonstrator : all functional building blocks of the adaptative neuromorphic chip have been validated, including hardware demonstrations of on-chip learning and continual learning with numerically stored hidden weights, learning with discrete hidden-weight stored in hardware, and PMNIST continual-learning simulations incorporating real device measurements (WP4)
Continuous learning is paramount in the vast majority of today's AI applications, operating in real-world settings alongside humans, as they must adapt to remain effective and efficient. By integrating our hardware neuromorphic chip with continual learning algorithms, we ensure the sustainability of edge AI solutions.The ongoing research within the EIC project holds the potential to catalyze significant advancements in both hardware and software solutions capable of implementing metaplasticity at ultra-low power. This could unlock new functionalities and drive the development of products tailored for autonomous lifelong learning applications. Such advances are particularly pertinent in critical sectors like medical monitoring, Industry 4.0 IoT devices, autonomous vehicles, robotics, and defense, where adaptability to evolving environments is paramount without compromising existing knowledge.
While Europe excels in embedded system software, it lags behind in hardware development despite its academic excellence in emerging technologies. Our project aims to bridge this gap, transforming Europe's scientific leadership into an industrial reality and enabling Europe to regain control over its digital supply chain while securing its technological sovereignty. Our aspiration to emerge as a global leader in edge AI computing is fully aligned with the EU digital agenda and the European Chips Act.
The project has made significant strides towards achieving broad technological impact:
• We have identified multiple hardware and software outcomes that will drive the development of metaplastic Binary Neural Networks hardware at ultra-low power for edge AI
• We have validated an ion beam pilot line together with specific metrology tools to address scalability, pre-industralization and meet the requirements of our customers. Ongoing discussions with national foundries aim to establish our pilot line.
• Our technology has attracted interest from 10+ chip makers for potential collaboration and use case development with Spin-Ion Technologies.
• We have been identified by YOLE as an important player in neuromorphic computing (Neuromorphic Computing, Memory and Sensing 2024)
• We have protected our technology through patent filings (up to 5) and trade secrets have started, ensuring its security and future economic viability.
• We have launched our internationalization in north America and Taiwan by developping several partnerships
In term of economic impact, the neuromorphic computing market is expected to take-off from 2026 as neuromorphic-based technologies mature. This timeline aligns well with our transition project, enabling Spin-Ion to onboard initial users by 2025. Spin-Ion will be a key enabler in unlocking and accelerating the market for edge AI chips by:
• Drastically reducing power consumption and facilitating on-chip learning capabilities.
• Accelerating the integration of our manufacturing process through the deployment of our pilot line in France.
• Establishing the company as a leading IP provider, offering both hardware and software platforms.
• Supporting other European SMEs involved in developing edge AI systems.
In term of societal impact, our solution enables reliable, large-scale, and environmentally sustainable deployment of edge/IoT devices and applications which will benefit European society with activities such as monitoring of health, mobility, smart cities, smart home and entertainment. We aim to help the general public understand and appreciate our technologies & ramifications. We have made a concerted effort to foster a gender-balanced workforce, with five women actively involved in the EIC project, including three young researchers. To further promote gender diversity in deep tech start-ups, we have initiated communication activities led by Spin-Ion’s women and aimed at the general public, women in science and stakeholders.
While Europe excels in embedded system software, it lags behind in hardware development despite its academic excellence in emerging technologies. Our project aims to bridge this gap, transforming Europe's scientific leadership into an industrial reality and enabling Europe to regain control over its digital supply chain while securing its technological sovereignty. Our aspiration to emerge as a global leader in edge AI computing is fully aligned with the EU digital agenda and the European Chips Act.
The project has made significant strides towards achieving broad technological impact:
• We have identified multiple hardware and software outcomes that will drive the development of metaplastic Binary Neural Networks hardware at ultra-low power for edge AI
• We have validated an ion beam pilot line together with specific metrology tools to address scalability, pre-industralization and meet the requirements of our customers. Ongoing discussions with national foundries aim to establish our pilot line.
• Our technology has attracted interest from 10+ chip makers for potential collaboration and use case development with Spin-Ion Technologies.
• We have been identified by YOLE as an important player in neuromorphic computing (Neuromorphic Computing, Memory and Sensing 2024)
• We have protected our technology through patent filings (up to 5) and trade secrets have started, ensuring its security and future economic viability.
• We have launched our internationalization in north America and Taiwan by developping several partnerships
In term of economic impact, the neuromorphic computing market is expected to take-off from 2026 as neuromorphic-based technologies mature. This timeline aligns well with our transition project, enabling Spin-Ion to onboard initial users by 2025. Spin-Ion will be a key enabler in unlocking and accelerating the market for edge AI chips by:
• Drastically reducing power consumption and facilitating on-chip learning capabilities.
• Accelerating the integration of our manufacturing process through the deployment of our pilot line in France.
• Establishing the company as a leading IP provider, offering both hardware and software platforms.
• Supporting other European SMEs involved in developing edge AI systems.
In term of societal impact, our solution enables reliable, large-scale, and environmentally sustainable deployment of edge/IoT devices and applications which will benefit European society with activities such as monitoring of health, mobility, smart cities, smart home and entertainment. We aim to help the general public understand and appreciate our technologies & ramifications. We have made a concerted effort to foster a gender-balanced workforce, with five women actively involved in the EIC project, including three young researchers. To further promote gender diversity in deep tech start-ups, we have initiated communication activities led by Spin-Ion’s women and aimed at the general public, women in science and stakeholders.