T-KOS - Terahertz Technologies, e.g. for neuromorphic computing with Fraunhofer FHR, Fraunhofer ENAS, Fraunhofer HHI, Fraunhofer IAF, Fraunhofer IMS, Fraunhofer IPMS, Fraunhofer IZM, Research Fab Microelectronics Germany (FMD), Leibniz FBH, Leibniz IHP
In the T-KOS project, terahertz technology is now to be synergetically developed for industry in the fields of communication and sensor technology for the first time.
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Strategic research topic Neuromorphic Computing @ Fraunhofer EMFT
including expertise in micro- and nanotechnologies for new neuromorphic systems for semiconductor chips I Development of neurologically inspired computer architectures I Memristors - from memory and resistor, memory and electrical resistance as synapses based on new 2D nanomaterials I Circuit Design team develops new integrated memory technologies in innovative concepts for the realization of analog and digital neuromorphic circuits
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Memristive components, e.g. for novel, "low-energy" computing architectures for neuromorphic electronics @ Fraunhofer EMFT
At Fraunhofer EMFT, various novel memristive components and devices are developed and tested. This includes especially thin-film architectures (MIM, metal-isolator-metal) from various metal layers and oxide dielectrics.
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EU project NeurONN - On the way to brain-like computing with Fraunhofer EMFT
Work on extremely energy-efficient elements and architectures for neuromorphic computing. Innovative 2D materials are also used in the process.
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2D materials based on the chalcogenides MoS2 and WS2, e.g. for neuromorphic computing "at the edge" @ Fraunhofer EMFT
On the equipment base, Fraunhofer EMFT contributes with a 3-chamber cluster tool, funded by the Federal Ministry of Education and Research (Project FMD, 16FMD01K). Mature wafer size is 200 mm, but with adapters processing of smaller wafers or samples is possible as well.
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EU project ANDANTE - Development of innovative mixed-signal accelerators for artificial neural networks (ANN) with computation-in-memory (CIM) capability, with Fraunhofer EMFT, Fraunhofer IIS, Fraunhofer IPMS
Fraunhofer EMFT researchers are working together with Fraunhofer IIS and Fraunhofer IPMS as part of the EU ANDANTE project to develop innovative mixed-signal artificial neural network (ANN) accelerator with computation-in-memory (CIM) ability.
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ECSEL project TEMPO (Technology & Hardware for Neuromorphic Computing) with Fraunhofer EMFT, Fraunhofer IPMS
Within the ECSEL project TEMPO (Technology & Hardware for Neuromorphic Computing) the German consortium with participation of Fraunhofer EMFT is working on the development and evaluation of power-saving neuromorphic computing chips in the 22nm FDSOI technology node.
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White paper on memristor technologies with Fraunhofer ENAS
A team at Fraunhofer ENAS is currently developing a technology for the production of BFO memristors at wafer level in crossbar array structures as part of the ATTRACT project "Development of an overall technology for the modular integration of novel electronic components in microelectronic CMOS hybrids - BFO4ICT".
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Beyond-CMOS and RF devices, integrated circuits and technologies - Memristors for the computers of tomorrow @ Fraunhofer ENAS
In view of the increasing challenge in the miniaturization of conventional CMOS circuits, a further increase in performance through miniaturization is economically difficult and can only be maintained by large-volume production.
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Neuromorphic hardware @ Fraunhofer IIS
With the following neuromorphic architectures:
- Analog neuromorphic hardware design
- Digital neuromorphic hardware design
- Pulsed neuromorphic hardware design
- Spiking neural network accelerator
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Hardware for AI - consulting, design and implementation @ Fraunhofer IIS
Fraunhofer IIS covers both microcontroller-based machine learning and the use of embedded chips with deep learning accelerators. For a given problem, researchers analyze the system requirements and determine the appropriate algorithms and the best hardware options.
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Lo3-ML - Low-Power Low-Memory Low-Cost ECG Signal Analysis Using Machine Learning Algorithms - Energy-saving AI chip wins innovation competition @ Fraunhofer IIS
Organized by the German Federal Ministry of Education and Research (BMBF), the "Energy-efficient AI systems" pilot innovation contest posed the challenge: "Which team can produce a chip that detects atrial fibrillation in ECG data with at least 90 percent accuracy while consuming the least energy possible?".
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LODRIC - LOW-Power Digital Deep LeaRning Inference Chip mit Fraunhofer IIS
Eleven teams from universities and research institutes competed in the pilot innovation competition to find the most efficient solution for high-performance electronics that can run artificial intelligence (AI) algorithms.
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SEC-Learn - Sensor-Edge-Cloud for Federated Learning with Fraunhofer EMFT, Fraunhofer IIS, Fraunhofer IIS/EAS, Fraunhofer IPMS
The SEC-Learn project is creating a system of distributed energy-saving edge devices that learn together to solve a complex signal processing problem using machine learning.
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ADELIA - Analog Deep Learning Inference Accelerator with Fraunhofer IIS, Fraunhofer IPMS
Germany’s Federal Ministry of Education and Research (BMBF) has launched its first-ever competition dedicated to the development of an innovative, energy-efficient AI system.
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With neuromorphic hardware to »fast-thinking« AI @ Fraunhofer IIS
It is impossible to speed up artificial intelligence indefinitely on classical computers. The hardware needs time to “think”. Read here how Fraunhofer IIS solves this problem.
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Future Chip Design
Neuromorphic Hardware: We bring AI to the Edge @ Fraunhofer IIS
Newly developed neuromorphic hardware will enable highly efficient processing of sensor data on edge devices.
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Drastically reducing the risk of stroke: Neuromorphic hardware makes it possible! @ Fraunhofer IIS
A research team from Fraunhofer IIS and Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) has developed neuromorphic hardware capable of detecting early signs of atrial fibrillation and considerably reducing the risk of stroke.
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Neuromorphic hardware for autonomous driving @ Fraunhofer IIS
In the KI-FLEX project, researchers are developing neuromorphic hardware that allows artificial intelligence (AI) to be integrated directly into a car – in the form of a flexible platform.
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Fraunhofer IMS launches an initiative for a virtual competence center in chip design
Become part of CHIPS.NRW, e.g. for the areas of Neuromorphic Computing / RISC-V / Open Hardware.
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Neural networks @ Fraunhofer IMS
The Competence Microelectronics Intelligence builds intelligent sensors by integrating advanced micro/nano sensors with artificial intelligent processing by providing reliable neural network circuits built in integrated analog hardware for real-time sensory applications.
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Technologies ASICs - including with artificial intelligence and neuromorphic cores @ Fraunhofer IMS
From high-resolution sensor systems over embedded hardware security, open RISC-V microcontrollers up to artificial intelligence and neuromorphic cores, Fraunhofer IMS offers solutions for direct application and as IPs for the integration into your ASIC.
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Fraunhofer lead project NeurOSmart with Fraunhofer IMS, Fraunhofer IPMS, Fraunhofer ISIT
In the Fraunhofer-Gesellschaft's lead project NeurOSmart five institutes (ISIT, IPMS, IMS, IWU, IAIS) are jointly researching particularly energy-efficient and intelligent sensors for the next generation of autonomous systems.
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Strategic research field Neuromorphic Computing @ Fraunhofer IPMS
Fraunhofer IPMS develops materials, technologies and complete hardware solutions with high energy efficiency, especially for edge applications.
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MEMION - Memristive redox transistors for neuromorphic computer architectures with Fraunhofer IPMS
The development goal in the MEMION project is energy-efficient transistors with multi-stage switching behavior that can be used in neuromorphic computing networks.
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StorAIge - New storage technology for edge AI applications with Fraunhofer IPMS
The project targets chips with very efficient memories and high computing power to reach 10 tops per watt. To make this possible, Fraunhofer IPMS is relying on ferroelectric field-effect transistors (FeFETs).
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Thinking chips: New materials and hardware for next generation computing @ Fraunhofer IPMS
Increasing digitalization is constantly driving up the demands on electronic hardware. Neuromorphic computing, which aims to emulate the self-organizing and self-learning nature of the brain, offers a promising solution.
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Materials for micro- and nanoelectronics - Neuromorphic devices @ Leibniz IHP
In this research program, new materials for micro- and nanoelectronics are investigated. Promising approaches in materials science for future devices in microelectronics are identified in the three working groups of the research program.
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Neuromorphic on-chip recognition of saliva samples @ Leibniz IHP
The research team led by Prof. Dr. Christian Wenger at Leibniz IHP is working on a novel early warning system for the early identification of lung diseases, especially chronic obstructive pulmonary disease (COPD).
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Process development @ Leibniz IHP
New research fields like neuromorphic computing based on fully integrated memrestive cells or epitaxially modified substrates for quantum technologies are investigated within this competence area.
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New Collaborative Research Center (CRC) on Artificial Intelligence to start in 2021 with Leibniz IHP
The aim of the new Collaborative Research Center is to transfer knowledge about the information paths in nervous systems to technical information processing in order to improve pattern and speech recognition or the energy efficiency of existing systems.
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Leibniz IHP offers access to memristive technology for edge AI computing or hardware artificial neural networks applications
By providing the MEMRES module the IHP gives circuit designers around the world the opportunity to create neuromorphic circuits with integrated memristive technologies in the near future.
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Neutronics @ Leibniz IHP
The aim of the DFG's new Collaborative Research Centre (SFB) is to transfer findings about the information pathways in nervous systems to technical information processing in order to improve pattern and speech recognition or the energy efficiency of existing systems.
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Adaptive materials, including the development of memristive arrays for edge computing and neuromorphic circuits @ Leibniz IHP
The research area of plasmonics deals with the properties of electromagnetic near fields in CMOS-compatible nanostructures, which are able to locally increase electromagnetic fields and thus open up a broad field of application.
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