
SPINEDGE LTD
SPINEDGE LTD
2 Projects, page 1 of 1
Open Access Mandate for Publications and Research data assignment_turned_in Project2024 - 2027Partners:UCL, BIU, SPINEDGE LTD, AMIRES SRO, INESC MICROSISTEMAS E NANOTECNOLGIAS-INSTITUTO DE +7 partnersUCL,BIU,SPINEDGE LTD,AMIRES SRO,INESC MICROSISTEMAS E NANOTECNOLGIAS-INSTITUTO DE,BIU,IFEVS,AMIRES SRO,IFEVS,VUB,INESC MICROSISTEMAS E NANOTECNOLGIAS-INSTITUTO DE,SPINEDGE LTDFunder: European Commission Project Code: 101130046Overall Budget: 3,143,280 EURFunder Contribution: 3,143,280 EURThe rise of technologies such as the Internet of Things (IoT), autonomous vehicles, smart cameras, etc. is generating lots of big data. The volume of data in 2022 was 97ZB and is doubling every 2-3 years. This is leading to unprecedented growth in energy consumption and costs needed for data processing. Sending raw data for remote processing on centralized nodes is limited in terms of speed and bandwidth, and even next-gen tech like 5G or 6G will be insufficient to cope with this growth. Processing data at the Edge, where it's generated, requires increasing power efficiency by several orders of magnitude. However, the use of general-purpose digital processors based on von Neumann architecture is limited, with optimization possibilities nearing natural limits. A new class of chips, neuromorphic hardware, is needed to execute AI algorithms like Deep Learning at high speed, low energy consumption, endurance, and scalability. MultiSpin.AI’s vision is to improve neuromorphic computing by increasing the energy efficiency and processing speed by at least three orders of magnitude over digital computing and >10x compared to the most advanced neuromorphic devices to reach an unparalleled 2,000 Tera operations per second per watt (TOPS/W). To achieve this, MultiSpin.AI will develop an AI co-processor based on a crossbar of multi-level magnetic tunnel junctions (M2TJ) cells/ n-ary state cells. The use of multi-level M2TJs reduces the number of cells, simplifies circuity, and reduces the number of digital-to-analog conversions (DAC) at the input of the crossbar, and analog-to-digital conversions at the crossbar output. The combined effect is realising much higher energy efficiency and faster AI inference at the Edge. This breakthrough will help provide a significant impact by enabling transformative applications like autonomous vehicles, robots, and medical devices and help strengthen strategic autonomy for the EU chips industry and reduce CO2 emissions from AI inference.
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For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications and Research data assignment_turned_in Project2025 - 2028Partners:TU/e, SIRRIS, BIU, ZES ZIMMER ELECTRONIC SYSTEMS GMBH, AVL +69 partnersTU/e,SIRRIS,BIU,ZES ZIMMER ELECTRONIC SYSTEMS GMBH,AVL,SAL,INNOVATION DIS.CO PRIVATE COMPANY,Infineon Technologies (Germany),Xpdeep,Infineon Technologies (Germany),NTUA,AMPERE SAS,SPINEDGE LTD,ITML,AIT,BEE MOBILITY SOLUTIONS OTOMOTIV SANAYI VE TICARET AS,R&S,FAU,BUT,NXP (Netherlands),NXP (Germany),PAXSTER AS,INNOVATION DIS.CO PRIVATE COMPANY,BIU,Graz University of Technology,ANYWI,Harokopio University,Latvian Academy of Sciences,PAXSTER AS,Infineon Technologies (Austria),FORD OTOMOTIV SANAYI ANONIM SIRKETI,LETI,ITML,Polytechnic University of Milan,FHG,EMOTION3D GMBH,ANYWI,BLUEPATH ROBOTICS,VOCSens SRL,EMOTION3D GMBH,VIF,TTControl,NXP (Netherlands),FORD OTOMOTIV SANAYI ANONIM SIRKETI,Infineon Technologies (Austria),SINTEF AS,Gdańsk University of Technology,SINTEF AS,NXTECH AS,NXTECH AS,Technische Universität Braunschweig,SIRRIS,TÜBİTAK,R&S,IMA,SPINEDGE LTD,IMA,VOCSens SRL,NXP (Germany),IECS,ZES ZIMMER ELECTRONIC SYSTEMS GMBH,AVL,INFINEON TECHNOLOGIES ITALIA Srl,SAL,ESC AEROSPACE GMBH,Harokopio University,VIF,BLUEPATH ROBOTICS,INFINEON TECHNOLOGIES ITALIA Srl,TTControl,TU Delft,AU,TÜBİTAK,REKROM OPTOELEKTRONIK MUHENDISLIK SISTEM TEKNOLOJILERI ANONIM SIRKETIFunder: European Commission Project Code: 101194414Overall Budget: 53,320,000 EURFunder Contribution: 16,013,700 EURMOSAIC addresses a grand challenge for European competitiveness: technological independence and filled fabs in the landscape of automated systems. By fostering innovation in Electronic Components and Systems (ECS), MOSAIC aims to propel Europe to excellence and digital autonomy, directly linked to the EU Chips Act. The project achieves this through a comprehensive strategy. It will develop next-generation ECS offering superior, cognitive system intelligence, enabling energy efficiency and robustness. These results will be tailored to the demands of automated systems, enabling rapid data processing and intuitive, AI-enabled decision- making. MOSAIC tackles the challenge of integrating diverse perception hardware configurations, ensuring that automated systems can perceive their surroundings in a non-invasive manner, avoiding a single point of failure, with unparalleled accuracy and decreased complexity. Additionally, the project emphasizes standardized communication protocols and interoperability, fostering a collaborative ecosystem across several industries, namely automotive, aerospace, maritime, industrial automation and infrastructures. By spearheading such advancements, MOSAIC empowers European ECS manufacturers to gain a competitive advantage. The project's achievements will be demonstrated in 31 cutting-edge technical showcases, indicatively global perception through 360° distributed radar, AI-enabled reasoning through magnetic field signature and resilient communications by means of non-terrestrial networks. 2 accompanying impact studies, will solidify Europe's position as a global leader in automated systems. MOSAIC leverages a pan-European consortium encompassing the entire ECS value chain, ensuring a comprehensive effort towards filling the European fabs and ensuring digital sovereignty. In essence, MOSAIC is an investment in Europe's future – a secure digital future of technological leadership, economic prosperity, and strategic independence.
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