NeuroSysStatusSeminar2024

Our Projects

Neuromorphic Hardware for Autonomous Artificial Intelligence Systems

The NeuroSys future cluster encompasses the entire value chain in seven projects, thus driving development in the individual areas. Cross-project collaboration enables the joint design of materials, components, algorithms/hardware, and applications. Our goal is to achieve European technological independence in the field of AI hardware.

Projects
Publications
Partner & Advisor

Projekt A1:
AI application-specific technology maturation of memristive components

Project leader: Prof. Dr.-Ing. Max Lemme, ELD –Chair of electronic Devices

The research project aims to further develop memristors based on two-dimensional materials and VCM metal oxide memristors for neuromorphic computing. Technological hurdles will be overcome by optimizing MOCVD technology and integrating functional layers. Precise programming schemes and specific device models will be developed. The results will be used scientifically and commercially to promote technology transfer and strengthen the region and Germany as a business location.

here a listing

Projekt A2:
Metrology for memristive materials

Project leader: Prof. Dr-Ing. Max Lemme, AMO GmbH –Society for Applied Micro- and Optoelectronics mbH

New 2D materials are being explored as potential active materials for memristive components due to
their atomic thickness and miniaturization potential. Their chemical and structural properties,
especially within the devices, can significantly influence device behavior under electrical bias
conditions due to microscopic mechanisms. Project A2 thus aims to take the metrology of memristive
materials to a new level, enabling the precise and local characterization of material properties and compositions.
erheblich beeinflussen. Das Projekt A2 strebt damit an, die Metrologie von
memristiven Materialien auf eine neue Stufe zu heben, um die präzise und lokale
Charakterisierung der Materialeigenschaften und Materialzusammensetzungen zu
ermöglichen.

Projekt B1:
Scalable optoelectronic AI hardware

Project leader: Prof Witzens, RWTH Aachen University, Chair of Integrated Photonics (IPH)

Project B1 aims to realize neuromorphic hardware using integrated photonic circuits in which information is transmitted using light. Optical transmission systems enable extremely high data rates and a substantial reduction in latency during signal transmission. The neuromorphic hardware system will be demonstrated in a silicon photonics chiplet combined with high-frequency electronics. Additionally, the use of vertically emitting lasers (VCSELs) for co-packaged optics in AI centers will be investigated.

Projekt B2:
Integrated photonic neuromorphic circuits with ultrascaled graphene phase modulators

Project leader: Prof. Dr.- Ing. Max Lemme, AMO GmbH – Society for Applied Micro- and Optoelectronics mbH

Project B2 focuses on a component that is essential for extremely fast and energy-efficient neuromorphic photonic computations: electro-optical modulators. To this end, we aim to research a novel graphene-based modulator whose dimensions can be minimized by maximizing light-matter interaction. The new modulators will be implemented in a so-called photonic tensor core for vector-matrix multiplication and used for initial demonstration experiments. Black Semiconductor, as an associated partner, is supporting the high-frequency characterization of the modulators and is interested in further exploiting these components.

Project C:
Algorithm-Hardware Co-Design

Project leader: Prof Gemmeke, RWTH Aachen University, Chair of Integrated Digital Systems and Circuit Design (IDS)

The long-term vision of the NeuroSys cluster is the future technological independence of Germany and Europe in the field of hardware for artificial intelligence applications. Our goal is to lay the scientific, technological, and socio-economic foundations to attract the large-scale investments required to establish a production line for AI hardware in the Aachen region. With our goals, we pursue the vision of technology development committed to the European community of values. Project C, "Algorithm-Hardware Co-Design," plays an integrative role between the more technology-oriented projects A and B and the application- and transfer-oriented projects D and E.

Project D:
Efficient AI methods for neuromorphic computing in practice

Project manager: Prof. Dr.-Ing. Anke Schmeink, RWTH Aachen University, Lehrstuhl für Informationstheorie und Datenanalytik

Project D aims to efficiently implement machine learning applications on future neuromorphic hardware and ensure their optimal use from a user perspective. The focus is on persistent network architectures developed specifically for neuromorphic hardware, algorithmic approaches to complexity reduction, and practice-oriented software tools. Practical solutions will be demonstrated using a variety of data formats, for example, in medical systems for improving diagnostics and therapy or in speech technology applications. Technology transfer is ensured through close collaborations with companies that translate research results into practice and simultaneously incorporate application requirements into research to promote sustainable innovations.

Project E:
Transformed design of innovation ecosystems and business model development

Project manager: Prof Letmathe, RWTH Aachen University, Chair of Controlling

Project E completes the seven interlocking projects from science, business, and society. The accompanying innovation processes and business model developments are analyzed to ensure long-term economic success and social and moral benefits. This type of strategy lays the foundation for subsequent transfer into business practice.