Leibniz Universität Hannover Faculty Faculty of Electrical Engineering and Computer Science
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Institute of Microelectronic Systems
 
Institute of Microelectronic Systems Research
Architectures and Systems Group

Research Projects of the Architectures and Systems Group

  • KIBI - AI-based surface inspection & automated damage detection for automotive assessment
    Together with Dream Chip Technologies and claimbird GmbH, the Institute for Microelectronic Systems is working on the next generation of vehicle assessment. The development goal: an AI-supported surface inspection solution with automated damage detection through the fusion of computer vision and depth data.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: D. Langhorst
    Year: 2025
    Funding: Europäischen Fonds für regionale Entwicklung (EFRE), Land Niedersachsen
    Duration: 2025-2027
  • Bioprinting
    The IMS conducts research in the field of regenerative medicine at the Lower Saxony Center for Biomedical Engineering, Implant Research and Development (NIFE) in collaboration with the Institute of Technical Chemistry (TCI). This project involves developing and improving processes for manufacturing bioartificial blood vessel prostheses. The IMS aims to further develop the melt electrowriting (MEW) process on a 4-axis bio-3D printer. To make this process more reliable, a control system is to be developed that automatically adjusts the process parameters to achieve the desired fiber diameter. Quality control during and after printing will ensure that the scaffold structure has been printed correctly and contains no defects.
    Year: 2025
  • Biosaftey - Multisensory bio-safety monitoring for actors in safety-critical infrastructure
    Together with Meditech GmbH, the Institute for Microelectronic Systems is working on the next generation of contactless sensor technology for fatigue detection.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Fabian Cholewa, Dr.-Ing.
    Year: 2025
    Funding: Europäischer Fond für regionale Entwicklung (EFRE) und Land Niedersachsen
    Duration: 2025-2027
  • KI-RISC-V for Harsh Environments
    Building on the success of the first RISC-V project at IMS, which developed a high-performance processor for extreme temperatures up to 200°C, the follow-up project aims to expand the existing architecture. The new focus is on integrating a specialized AI accelerator designed to efficiently accelerate classic machine learning operations.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Malte Hawich, M.Sc.
    Year: 2024
    Duration: 2024-2027
  • GreenML
    The project "GreenML" aims to exemplify a holistic AI design process by the highly efficient and resource-optimized implementation of essential FAS functions like object detection, object classification, and scene contextualization on particular hardware. Deep Learning (DL) has become a central approach for modern AI applications. Even though energy-efficient DL has become a target in research, currently isolated solutions are often created that do not unleash the full potential for resource-efficient AI. In this project, we will focus on a holistic approach: from hardware to efficient coding and transfer of data and models to dynamic and resource-adaptive software to enable multi-criteria optimization of all facets of an AI-enabled system. As an example, we demonstrate the potential of this approach using the scenario of a modern driver assistance system (FAS). With about 67 million registered vehicles and increased e-mobility, saving required energy by combining efficient algorithms, communication, and hardware is urgently needed. Our "Green Assisted Driving" project addresses different energy consumption, safety, and flexibility metrics. The consortium combines low-power hardware, learning of efficient representations from large data sets, hyperparameter optimization, and network design using AutoML, as well as methods of transfer learning, semi-supervised learning, and network pruning to prototype highly efficient and dynamically controllable models on a FAS. and demonstrate the savings potential of a holistic approach.
    Led by: Prof. Dr.-Ing. habil H. Blume
    Team: Matthias Lüders
    Year: 2023
    Duration: 2023-2026
  • EcoMobility
    During the European project "EcoMobility", the IMS will improve autonomous electric vehicles in regards to sustainability, connectivity and safety together with 46 partners from all over Europe. The IMS will especially focus on intelligent scheduling of tasks on heterogeneous processor systems.
    Led by: Prof. Dr.-Ing. Holger Blume, M.Sc. Matthias Lüders
    Team: M.Sc. Jonas Hollmann
    Year: 2023
    Funding: KDT JU
    Duration: 2023-2025
    [Translate to English:] Offizielles Logo von "EcoMobility" [Translate to English:] Offizielles Logo von "EcoMobility"
  • KISSKI - AI service center for sensitive and critical infrastructures
    The central approach in KISSKI is research into AI methods and their provision with the aim of enabling a highly available AI service center for critical and sensitive infrastructures with a focus on the fields of medicine and energy. The Architecture and Systems department is involved in this with a design space exploration for heterogeneous hardware architectures, in particular FPGA platforms.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: M. Lüders, J. Drewljau
    Year: 2022
    Duration: 2022-2027
  • RISC-V for Harsh Environments
    In cooperation with an industrial partner, a RISC-V processor is being designed that will be capable of maximum performance even under the special conditions of a harsh environment. The technology, which is specially designed for high-temperature environments, is not particularly fast due to the necessary protective measures. Nevertheless, a target frequency of up to 200MHz is to be achieved. Special architectures are being used for this purpose and adapted to these specifications.
    Led by: Prof. Dr.-Ing. habil H. Blume
    Team: Malte Hawich, M.Sc.
    Year: 2021
    Duration: 2021-2025
  • Compact Realtime SAR-Image processor
    The goals of this project are the generation and compression of high resolution Synthetic Aperture Radar (SAR) images under real time conditions. Compared to camera based electro-optical sensors, a SAR system operates almost independent from daylight and weather conditions. State-of-the-art SAR sensor systems achieve spatial resolutions up to 10 cm at 10 km altitude. By using FPGAs for high performance digital signal processing tasks, aerial images can be generated in real time even in case of very large image dimensions.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: F. Cholewa, C. Fahnemann, N. Rother
    Year: 2020
    Duration: 2008-2020
  • Headlight range control with inertial sensors
    This project involves the development of a real-time control system for the adaptive control of high-resolution vehicle headlights. To this end, the vehicle's inclination is measured using inertial measurement units (IMUs) and used to dynamically adjust the light cone. The aim is to optimize the illumination of the road depending on the situation, avoid glare, and increase road safety.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Richard Pfleiderer, M.Sc.
    Year: 2020
  • BECCAL-II
    As part of the bilateral BECCAL-I project run by DLR and NASA, the Institute of Microelectronic Systems is supporting the development of an experimental platform for atomic optics experiments on board the International Space Station (ISS). This involves developing and evaluating platforms and algorithms for digital signal processing under space conditions.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Tim Oberschulte, M.Sc.
    Year: 2020
    Duration: 2022-2023
  • ZuSE-KI-AVF - Application-specific AI processor for intelligent sensor signal processing in autonomous driving
    Innovative driver assistance systems require new, powerful hardware platforms that are capable of processing high-resolution and multidimensional data sets in real time. Diverse sensor technology such as cameras, lidar, and radar leads to significantly differing requirements, which can be met with application-specific hardware. With the aim of developing such hardware based on a scalable and flexibly programmable architecture platform, the IMS successfully participated in the BMBF's ZuSE tender on topics related to artificial intelligence. In its role as project manager, the institute is working in a consortium on an open-source vector processor architecture that is particularly suitable for resource-intensive AI algorithms. Neural networks can be calculated efficiently through the vertical processing of data vectors and complex addressing modes. Aspects of functional safety and IP security are also being considered for use as an embedded IP core in commercial SoCs. The development of a compiler and an efficient memory controller are also part of the ZuSE-KI-AVF project. The IMS is working on the system architecture, the design and implementation of algorithms such as the processing of lidar point clouds, and a demonstration of the architecture based on an FPGA description.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Oliver Renke M.Sc., M.Sc. Christoph Riggers M.Sc., Till Fiedler M.Sc., Jakob Marten M.Sc., Tobias Stuckenberg M.Sc.
    Year: 2020
    Funding: BMBF
    Duration: Oktober 2020 - März 2025
  • ZuSE-KI-mobil
    Future tasks such as autonomous driving and Industry 4.0 require ever-increasing amounts of data from a growing number of sensors to be analyzed in the shortest possible time using complex algorithms and artificial intelligence (AI). However, the corresponding processors must meet high requirements not only in terms of computing power, but also in terms of energy efficiency, reliability, robustness, and security, which go far beyond current capabilities. The BMBF's ZuSE projects are designed to meet the urgent need of user industries for future-proof, trustworthy processors that are tailored to their specific tasks and deliver high performance.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Matthias Lüders, M.Sc., Martin Friedrich, M.Sc., Sousa Weddige, M.Sc., Oliver Renke, M.Sc., Christoph Riggers, M.Sc.
    Year: 2020
    Funding: BMBF
    Duration: Mai 2020 - Dezember 2025
  • Digital Video-processing for automation in agriculture
    Within this project, algorithms are developed, architectures explored and a final hardware-platform designed and evaluated. The overall system will be tested in a field test.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: J. Hartig, S. Gesper
    Year: 2019
    Duration: a 2017-2019
  • Cluster of Excellence Hearing 4 All 2
    The Cluster of Excellence is an interdisciplinary collaboration between Carl von Ossietzky University Oldenburg, Hannover Medical School, and Leibniz University Hannover. This unique collaboration allows results from algorithmic and medical research to be directly incorporated into the development of demonstrators and prototypes. The IMS focuses on development and research in the field of real-time signal processing of EEG signals (CereBridge) and the acceleration of neural networks for extremely efficient hearing aid processors.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Simon Klein, M.Sc.
    Year: 2019
    Duration: 2019 - 2025

Finished Projects

Analog/Mixed-Signal-Design

  • Multi-Energy Harvesting (MEH) - A Flexible Platform for Energy Harvesting in Home Automation
    In this project, a platform concept for intelligent home automation components is developed, which can serve as a basis for next-generation sensors and actors. The main characteristic of this platform concept is ultra-low power consumption and ultra-low voltage operation. In combination with harvested energy from multiple sources (multi-energy harvesting), an extended lifetime and reduced battery cell requirements become possible compared to current systems.
    Led by: Prof. Dr.-Ing. H. Blume, Prof. Dr.-Ing. B. Wicht, apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: M.Sc. Moritz Weißbrich, M.Sc. Lars-Christian Kähler
    Year: 2019
    Funding: BMBF
    Duration: October 2018 - March 2021
  • GEBO - High Temperature Electronic
    In this project, the design of mixed-signal circuits for signal processing is studied under high temperature conditions. For this, research on analog circuits and digital signal processing architectures will be conducted in order to adapt common design approaches to the requirements of high temperature technology.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Ing. Rochus Nowosielski
    Year: 2014
    Duration: 2009-20111

Biomedical Engineering

  • “Hearing with light” - development of implant electronics for thefrantic optical cochlear implant
    In this project, the implant electronics for a 64-channel optical cochlear implant are being developed. At the IMS, the focus is on an integrated circuit for controlling laser diode arrays, which is incorporated into an overall electronic system with wireless energy and data transmission.
    Led by: Prof. Dr.-Ing. Holger Blume, Prof. Dr.-Ing. Bernhard Wicht
    Team: Henrik Heymann, M.Sc., Adrian Gehl, M.Sc.
    Year: 2024
    Duration: 01.07.2024 - 31.12.2025
  • Smart Hearing Aid Processor (Smart HeaP)
    In the Smart Hearing Aid Processor (Smart HeaP) project, a novel hearing aid processor is designed, developed and built which, despite its simple programmability and wireless Bluetooth interface, is characterized by low power consumption and high computing power.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. J. Karrenbauer, M.Sc. S. Klein, M.Sc. S. Schönewald
    Year: 2018
    Funding: BMBF
    Duration: April 2018 - Juni 2022
  • Smart Hearing Aid Processor (Smart HeaP)
    Im Projekt Smart Hearing Aid Processor (Smart HeaP) wird ein neuartiger Hörgeräteprozessor konzipiert, entwickelt und gebaut, der sich trotz seiner einfachen Programmierbarkeit und der drahtlosen Bluetooth-Schnittstelle durch eine geringe Leistungsaufnahme und hohe Rechenleistung auszeichnet.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. J. Karrenbauer, M.Sc. S. Klein, M.Sc. S. Schönewald
    Year: 2018
    Funding: BMBF
    Duration: April 2018 - Juni 2022
  • Efficient Real-time Processing of EEG-Signals
    A brain-computer interface (BCI) is a system that generates signals to control an artificial system based on measurements of the activity of the central nervous system, for example, to replace, enhance or supplement certain tasks of human action. Modern BCIs are often based on the decoding or interpretation of EEG signals, as such systems are both non-invasive and cost-effectively available. These sensors detect a variety of independent, superimposed signals that make their immediate use for controlling a digital system difficult. Therefore, each application and corresponding application environment requires specifically designed and customized algorithms. This project therefore investigates methods for the efficient real-time processing of EEG signals. For this purpose, the Institute of Microelectronic Systems is developing a complete system of dedicated, configurable hardware in combination with a signal-processing framework specially adapted for the processing of EEG signals.
    Led by: Prof. Dr.-Ing. Holger Blume, Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: Marc-Nils Wahalla, Dipl.-Ing.
    Year: 2017
  • ZIM D-Sense - Development of a Testing System for the Diagnosis of Sensorimotor Regulation Abilities in Athletes
    The aim of the project is to develop a mobile diagnostics system which can be used to to assess the sensorimotor regulation abilities in athletes. The system should consist of multiple sensor units and allow the athlete or coach to quickly and precisely perform different functional sensorimotor tests. The sensor units can be placed at different points on or next to the subject's body, depending on the concrete test being performed. Also depending on the test, different algorithms are to be used for classifying and evaluating the measurements from the sensor units. A database helps the user to interpret the test results and provides reference values for risk assessments regarding injuries.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. Fritz Webering
    Year: 2017
    Funding: „Zentrales Innovationsprogramm Mittelstand“ of the BMWi - Federal Ministry for Economic Affairs and Energy
    Duration: 2017-2019
  • Optogenetic
    Within this cooperation with the Institute of Technical Chemistry and the Institute of Quantum Optics of the Leibniz Universität Hannover, methods are being studied to control the behavior of intracellular processes from the outside with light. Optogenetics can be used to specifically modify light-insensitive cells in order to respond to the influence of light. Due to the common previous experience between the project partners, especially optogenetic questions in the context of tissue engineering are focussed.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Marc-Nils Wahalla, Dipl.-Ing.
    Year: 2016
  • TETRACOM - Mobile platform for real-time sonification of movements for medical rehabilitation
    The rehabilitation of stroke patients is an intense and lengthy process. The common therapy approach is based on movement training in presence of a therapist. Through many repetitions a remobilization of the patient is achieved. Due to this highly time‐consuming treatment, the costs of for the therapy are very high. Therefore, in this research project, we are focusing on the design of a mobile system, which will provide a motion feedback by means of sonification. It will enable therapist‐independent training and as a result lessen the strain on patient and healthcare system.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: M.Sc. Daniel Pfefferkorn
    Year: 2016
    Funding: FP7 ‐ ICT ‐ 2013 ‐ 10
    Duration: September 2013 - August 2016
  • Hearing4All
    The joint venture "Hearing4all" that the IMS-AS participates in with multiple sub-projects, has been chosen as one of the federal cluster of excellence projects Friday June 15th 2012. In the scope of this project the IMS-AS aims to develop high-performance and low-power processor architectures for digital hearing systems, such as cochlear implants or hearing aids.
    Led by: Prof. Dr.-Ing. H. Blume, Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: M.Sc. C. Seifert, Dipl.-Ing. L. Gerlach
    Year: 2015
    Duration: November 2012 - December 2018
  • BIOFABRICATION for NIFE
    BIOFABRICATION for NIFE ist ein interdisciplinary research network between the Hanover Medical School, the Leibniz University of Hanover and the Hanover University of Music, Drama and Media. The goal of this research network is to achieve methods for growing biocompatible organic implants with heavily reduced rejection reactions.
    Led by: Prof. Dr.-Ing. Blume
    Team: Dipl.-Ing. Christian Leibold
    Year: 2014
    Funding: VolkswagenStiftung and County Lower Saxony
    Duration: May 2013 - June 2018
  • Real-time, low-latency sonification of complex movements
    The goal of this research project in the field of biomedical engineering is to generate an auditory feedback (sonification) of human movements. The IMS focuses on examing the performance of different hardware platforms for this application. Relevant performance parameters are the platforms power dissipation and the overall latency. Finally, the project goal is to enhance stroke rehabilitation by additionally providing auditory arm movement feedback. This could lead to shortened rehabilitation periods. Furthermore, the mobile hardware platform developed at the IMS allows home based rehabilitation.
    Led by: Prof. Dr.-Ing. Blume
    Team: Dipl.-Ing. (FH) H.-P. Brückner
    Year: 2013
    Funding: Europäischer Fonds für regionale Entwicklung (EFRE)
    Duration: February 2011 - June 2013

Design Space Exploration

  • EFdiS – Use of airborne SAR with digital interface
    The goal of this research project is the processing of FMCW sensor signals. The first step is intended to digitize the analog data on board through a suitable expansion card. In the second step, the digitized data is to be processed on board, and thus converted to an aerial image.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Ing. M. Wielage
    Year: 2014
    Duration: October 2012 - December 2014
  • OPARO
    In the development of integrated, programmable circuits, the optimization of power dissipation and temperature distribution is becoming increasingly important. So far, however, these can only be determined by very time-consuming simulations. Therefore, precise models for the determination of power dissipation shall be developed and mapped together with the functional emulation on FPGAs. By accelerating the determination of power dissipation and temperature distribution, specific optimizations of the architecture and the application code can then be made taking real input data into account.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Wirtsch.-Ing. Sebastian Hesselbarth
    Year: 2014

Driver Assistance Systems

  • Adaptive glare-free HD headlights
    In this project, signal processing algorithms for high-resolution headlights are designed and implemented in real time on various hardware platforms. Among other things, the adaptive headlight systems prevent glare for road users and increase road safety.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Jens Schleusner, M.Sc., Richard Pfleiderer, M.Sc.
    Year: 2024
    Duration: 2017-2024
  • Privacy-Preserving Camera
    The “Privacy-Preserving Camera” project is developing a mobile platform that uses neural networks to anonymize video sequences, enabling further use of the data in compliance with the GDPR. To this end, object detection networks, tracking algorithms, and anonymization methods are being investigated and implemented on a hardware platform.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. Julian Drewljau
    Year: 2020
    Duration: 2020 - 2022
  • PARIS - Parallel implementation strategies for highly automated driving
    This project focuses on the system design of driver assistance systems, from scenario to architecture. Novel self-learning and sensor fusion algorithms are being developed, as well as an innovative processor architecture. In addition, development steps for embedded MPSoC applications, such as architecture mapping and simulation methods, are being developed.
    Led by: Prof. Dr.-Ing. Holger Blume, Dipl.-Ing. Jakob Arndt
    Team: Dipl.-Ing. Jakob Arndt
    Year: 2017
    Funding: BMBF
    Duration: 04.2017 - 03.2020
  • ifuse - Intelligent fusion of radar and video sensors for demanding, highly automated driving situations
    As part of the BMWi-funded joint project ifuse, algorithms and architectures for the fusion of raw sensor data at a low level of abstraction are being investigated. Compared to previous fusion methods at the object list level, sensor data fusion at the raw data level enables more robust classification of objects and detection of the vehicle environment, even if individual sensors are impaired by environmental influences. Sensor data fusion at the raw data level is based on signals from active and passive vehicle sensors (e.g., LIDAR, RADAR, camera, ultrasound), which, after minimal preprocessing, are referenced to a common coordinate system and located in an environment model.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Nicolai Behmann, M.Sc.
    Year: 2017
    Funding: Bundesministerium für Wirtschaft und Energie
    Duration: Mai 2017 - April 2020
  • THINGS2DO - THIN but Great Silicon 2 Design Objects
    THINGS2DO is an ENIAC project, funded by the European Union and the Federal Ministry of Education and Research. The project aims to develop the new Fully Depleted Silicon On Insulator (FD-SOI) technology and the corresponding tool environment for high efficient and highly integrated circuits. The capabilities of the technology are further demonstrated through a demonstrator in the area of Advanced Driver Assistance Systems (ADAS).
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Gregor Schewior, Nicolai Behmann
    Year: 2016
    Funding: Europäische Union, Bundesministerium für Bildung und Forschung
    Duration: February 2016 - March 2018
  • ZIM Dream Chip Technologies GmbH
    In cooperation with Dream Chip Technologies GmbH, Garben, Germany, the Institute of Microelectronic Systems develops with funding from the Federal Ministry of Economic Affairs and Energy a camera system with integrated algorithms for high quality real time motion estimation in the area of driver assistance systems.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Gregor Schewior, Nicolai Behmann
    Year: 2015
    Funding: Bundesministerium für Wirtschaft und Energie
    Duration: September 2015 - December 2016
  • ASEV
    The goal of this sub-project of the BMBF project "Automatic Situation Interpretation for Event Triggered Video Surveillance" is to elaborate a concept for a hardware architecture that enables a SIFT (Scale Invariant Feature Transform) feature extraction under application-specific processing conditions as performance and power consumption. SIFT features offer a good basis for robust object identification and tracking for event triggered video surveillance. The field of application is thereby the airport apron, which is highly relevant to security. The concept was implemented on a FPGA-based hardware platform to build a demonstrator which was tested at the end of the project at the airport of Braunschweig.
    Led by: Prof. Dr.-Ing. H. Blume, Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: Dipl.-Ing. Nico Mentzer
    Year: 2014
    Funding: Bundesministerium für Bildung und Forschung (BMBF)
    Duration: Mai 2010 - April 2013
  • Efficient Hardware Architectures for Fast Image Sequence Analysis
    In practice, general reliability of modern driver assistance systems under arbitrary traffic, weather and illumination conditions often is a problem. Because more robust algorithms are computationally very intensive, this project deals with the examination of heterogenous hardware architectures and the evaluation of new mechanisms for complex applications in the field of camera-based driver assistance.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Julian Hartig
    Year: 2014
    Funding: Hans L. Merkle Stiftung
    Duration: February 2014 - February 2017
  • mDAS - Implementation of a real-time demonstrator for multicore-based driver assistance systems
    The goal of this Project is the conceptual design of a real-time mutlicore-based demonstrator for video-based driver assistance algorithms. Therefore, different performance metrics will be displayed in order to compare platform-specific performance characteristics.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Dipl.-Ing. Jakob Arndt
    Year: 2014
    Funding: Siemens AG
    Duration: February 2014 - August 2014
  • DESERVE - Development Platform for Safe and Efficient Drive
    DESERVE is a project funded by the European Union. The aim of the project is the promotion and evolution of advanced driver assistance systems (ADAS). These systems are devoted to support the driver in the safe control of the vehicle. For this purpose, the DESERVE platform is planned to be developed. This platform will be the base for future development of advanced driver assistance systems in Europe.
    Led by: Prof. Dr.-Ing. H. Blume, apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: Florian Giesemann, Frank Meinl, Nico Mentzer
    Year: 2013
    Funding: Europäische Union, Bundesministerium für Bildung und Forschung
    Duration: September 2012 - August 2015
  • OpenFAS
    In the scope of this project, a library of modules for driver assistence systems, based on a multicore processor architecture will be created. The project is in collaboration with the videantis corporation.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Dipl.-Ing. Christopher Bartels
    Year: 2012
    Funding: "Zentrales Innovationsprogramm Mittelstand" des Bundesministeriums für Wirtschaft und Technologie (BMWi)
    Duration: Juni 2012 - Oktober 2013
  • PROPEDES - Predictive Pedestrian Protection at Night
    The objectives of the project PROPEDES is the design and demonstration of a flexible hardware archtecture based on a Very Long Instruction Word (VLIW) Softcore microprocessor for a vision-based pedestrian detection. The VLIW processor is to be supported by dedicated hardware accelerators to speed up future high-quality video-based driver assistance systems. Finally the architecture is to be implemented on a real-time FPGA-based demonstrator.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Dipl.-Ing. Gregor Schewior
    Year: 2011
    Funding: Bundesministerium für Bildung und Forschung (BMBF)
    Duration: August 2008 - July 2011

Processor Architectures

  • Multi-Energy Harvesting (MEH) - A Flexible Platform for Energy Harvesting in Home Automation
    In this project, a platform concept for intelligent home automation components is developed, which can serve as a basis for next-generation sensors and actors. The main characteristic of this platform concept is ultra-low power consumption and ultra-low voltage operation. In combination with harvested energy from multiple sources (multi-energy harvesting), an extended lifetime and reduced battery cell requirements become possible compared to current systems.
    Led by: Prof. Dr.-Ing. H. Blume, Prof. Dr.-Ing. B. Wicht, apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: M.Sc. Moritz Weißbrich, M.Sc. Lars-Christian Kähler
    Year: 2019
    Funding: BMBF
    Duration: October 2018 - March 2021
  • CHORUS
    A highly optimized hardware/software module library for intelligent sensor systems in highly automated driver assistance applications based on the reconfigurable Dream Chip Technologies DCT10A SoM platform
    Led by: Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: M.Sc. Sven Gesper
    Year: 2018
    Funding: BMWi
    Duration: 01.11.2018 - 31.03.2021
  • Smart Hearing Aid Processor (Smart HeaP)
    In the Smart Hearing Aid Processor (Smart HeaP) project, a novel hearing aid processor is designed, developed and built which, despite its simple programmability and wireless Bluetooth interface, is characterized by low power consumption and high computing power.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. J. Karrenbauer, M.Sc. S. Klein, M.Sc. S. Schönewald
    Year: 2018
    Funding: BMBF
    Duration: April 2018 - Juni 2022
  • Smart Hearing Aid Processor (Smart HeaP)
    Im Projekt Smart Hearing Aid Processor (Smart HeaP) wird ein neuartiger Hörgeräteprozessor konzipiert, entwickelt und gebaut, der sich trotz seiner einfachen Programmierbarkeit und der drahtlosen Bluetooth-Schnittstelle durch eine geringe Leistungsaufnahme und hohe Rechenleistung auszeichnet.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. J. Karrenbauer, M.Sc. S. Klein, M.Sc. S. Schönewald
    Year: 2018
    Funding: BMBF
    Duration: April 2018 - Juni 2022
  • Design of a Configurable, Massive-Parallel Vector Processor Architecture for Computer Vision and a Framework for the Implementation of Object Recognition Applications for Embedded Systems
    The increasing complexity of current computer vision algorithms for autonomous driving, such as object detection and classification using neural networks, represents a challenge for automotive system designers. Providing a real-time processing system under hard real-time constraints and a low energy (budget a few watts) is difficult to achieve even with current technical platforms. The goal of this project is to design a new approach of application-specific vector processor for FPGA implementation. The well-known overhead of other platforms (e.g. GPUs) shall be avoided by using several strategies: Novel functional mechanisms, a modular and customizable architecture and a suitable development framework, which is especially designed for the implementation of automotive applications.). An FPGA-based prototype will demonstrate the performance of the vector processor concept for a selected application at the end of the project.
    Led by: apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: Dipl.-Ing. S. Nolting, Dipl.-Ing. L. Gerlach
    Year: 2016
    Duration: Mai 2016 - Oktober 2017
  • TETRACOM
    Nowadays, continuous development of digital signal processing applications, e.g., video-based advanced driver assistance systems, are pushing the limits of existing embedded systems and are forcing system developers to spend more time on code optimization. These applications often involve complex mathematical functions like trigonometric, logarithmic, exponential, or square root operations. In particular, these functions can only efficiently be computed on standard general purpose embedded processors, using highly optimized, processor specific arithmetic evaluation software libraries. Another alternative is to extend the embedded processor architectures with a specific hardware accelerator.
    Led by: Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: Dipl.-Ing. S. Nolting, Dipl.-Ing. L. Gerlach
    Year: 2016
    Duration: January 2016 - July 2016
  • Stochastic Processor
    Stochastic computing has recently emerged as a promising approach for designing energy-efficient embedded hardware systems, taking into account the ability of many applications (e.g., computer vision) to tolerate the loss of precision in the computed results. Rather than designing the hardware for worst case scenarios featuring expensive guard-bands, designers can relax the implementation constraints and deliberately expose hardware variability, obtaining significant processing performance improvements and energy benefits.
    Led by: Jun.-Prof. Dr.-Ing. G. Payá-Vayá, Prof. Dr.-Ing. Holger Blume
    Team: M.Sc. Moritz Weißbrich
    Year: 2015
    Funding: Deutsche Forschungsgemeinschaft (DFG)
    Duration: February 2016 - January 2019
  • Hearing4All
    The joint venture "Hearing4all" that the IMS-AS participates in with multiple sub-projects, has been chosen as one of the federal cluster of excellence projects Friday June 15th 2012. In the scope of this project the IMS-AS aims to develop high-performance and low-power processor architectures for digital hearing systems, such as cochlear implants or hearing aids.
    Led by: Prof. Dr.-Ing. H. Blume, Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: M.Sc. C. Seifert, Dipl.-Ing. L. Gerlach
    Year: 2015
    Duration: November 2012 - December 2018
  • High Temperature Measurement While Drilling
    The goal of the research is an MWD processor system for drilling tools used for geothermal drilling in ambient temperatures up to 300 °C. The processing of the project includes research aspects in the fields of hardware design, fault tolerance of digital systems and ASIC design.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Ing. Rochus Nowosielski
    Year: 2014
    Duration: 2012-2014
  • GEBO - High Temperature Electronic
    In this project, the design of mixed-signal circuits for signal processing is studied under high temperature conditions. For this, research on analog circuits and digital signal processing architectures will be conducted in order to adapt common design approaches to the requirements of high temperature technology.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Ing. Rochus Nowosielski
    Year: 2014
    Duration: 2009-20111
  • RAPANUI - Rapid-Prototyping for Media Processor Architecture Exploration
    Design, implementation, and evaluation of a prototyping-based Designmethodology for processor architectures for digital signal processing.
    Led by: Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: M. Sc. Florian Giesemann
    Year: 2014
  • OPARO
    In the development of integrated, programmable circuits, the optimization of power dissipation and temperature distribution is becoming increasingly important. So far, however, these can only be determined by very time-consuming simulations. Therefore, precise models for the determination of power dissipation shall be developed and mapped together with the functional emulation on FPGAs. By accelerating the determination of power dissipation and temperature distribution, specific optimizations of the architecture and the application code can then be made taking real input data into account.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Wirtsch.-Ing. Sebastian Hesselbarth
    Year: 2014

Reconfigurable Architectures

  • Design of a Configurable, Massive-Parallel Vector Processor Architecture for Computer Vision and a Framework for the Implementation of Object Recognition Applications for Embedded Systems
    The increasing complexity of current computer vision algorithms for autonomous driving, such as object detection and classification using neural networks, represents a challenge for automotive system designers. Providing a real-time processing system under hard real-time constraints and a low energy (budget a few watts) is difficult to achieve even with current technical platforms. The goal of this project is to design a new approach of application-specific vector processor for FPGA implementation. The well-known overhead of other platforms (e.g. GPUs) shall be avoided by using several strategies: Novel functional mechanisms, a modular and customizable architecture and a suitable development framework, which is especially designed for the implementation of automotive applications.). An FPGA-based prototype will demonstrate the performance of the vector processor concept for a selected application at the end of the project.
    Led by: apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: Dipl.-Ing. S. Nolting, Dipl.-Ing. L. Gerlach
    Year: 2016
    Duration: Mai 2016 - Oktober 2017
  • TUKUTURI
    In the TUKUTURI-project, a for ASIC-synthesis optimized VHDL-description of a soft core processor architecture will be optimized for FPGA synthesis. The suitability of special functional units for specific applications with regard to performance and area consumption will be analyzed.
    Led by: Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: M. Sc. Florian Giesemann
    Year: 2014
    Funding: Wege in die Forschung II
  • Circuit Design and Physical Design for a Novel FPGA Architecture
    Evaluation and analysis of the implemtability and performance of a new type of field programmable gate array (FPGA).
    Led by: Prof. Dr.-Ing. H. Blume, apl. Prof. Dr.-Ing. G. Payá Vayá
    Team: B. Bredthauer, C. Spindeldreier
    Year: 2013
    Funding: Federal Ministry of Education and Reserach
    Duration: May 2013 - June 2014

System Design

  • BECCAL-I
    Scope of the bilateral BECCAL-I of DLR and NASA is the design of a platform for atom optic experiments on board of the international spece station. Within the project the Institute of Microelectronic Systems will develop and evaluate platforms and algorithms for digital signal processing in space.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: M.Sc. Tim Oberschulte
    Year: 2018
    Funding: "National Space Program" of the Federal Ministry for Economic Affairs and Energy (BMWi)
    Duration: August 2018 - Dezember 2021
  • Efficient Real-time Processing of EEG-Signals
    A brain-computer interface (BCI) is a system that generates signals to control an artificial system based on measurements of the activity of the central nervous system, for example, to replace, enhance or supplement certain tasks of human action. Modern BCIs are often based on the decoding or interpretation of EEG signals, as such systems are both non-invasive and cost-effectively available. These sensors detect a variety of independent, superimposed signals that make their immediate use for controlling a digital system difficult. Therefore, each application and corresponding application environment requires specifically designed and customized algorithms. This project therefore investigates methods for the efficient real-time processing of EEG signals. For this purpose, the Institute of Microelectronic Systems is developing a complete system of dedicated, configurable hardware in combination with a signal-processing framework specially adapted for the processing of EEG signals.
    Led by: Prof. Dr.-Ing. Holger Blume, Jun.-Prof. Dr.-Ing. G. Payá-Vayá
    Team: Marc-Nils Wahalla, Dipl.-Ing.
    Year: 2017
  • ZIM D-Sense - Development of a Testing System for the Diagnosis of Sensorimotor Regulation Abilities in Athletes
    The aim of the project is to develop a mobile diagnostics system which can be used to to assess the sensorimotor regulation abilities in athletes. The system should consist of multiple sensor units and allow the athlete or coach to quickly and precisely perform different functional sensorimotor tests. The sensor units can be placed at different points on or next to the subject's body, depending on the concrete test being performed. Also depending on the test, different algorithms are to be used for classifying and evaluating the measurements from the sensor units. A database helps the user to interpret the test results and provides reference values for risk assessments regarding injuries.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: M.Sc. Fritz Webering
    Year: 2017
    Funding: „Zentrales Innovationsprogramm Mittelstand“ of the BMWi - Federal Ministry for Economic Affairs and Energy
    Duration: 2017-2019
  • TETRACOM - Mobile platform for real-time sonification of movements for medical rehabilitation
    The rehabilitation of stroke patients is an intense and lengthy process. The common therapy approach is based on movement training in presence of a therapist. Through many repetitions a remobilization of the patient is achieved. Due to this highly time‐consuming treatment, the costs of for the therapy are very high. Therefore, in this research project, we are focusing on the design of a mobile system, which will provide a motion feedback by means of sonification. It will enable therapist‐independent training and as a result lessen the strain on patient and healthcare system.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: M.Sc. Daniel Pfefferkorn
    Year: 2016
    Funding: FP7 ‐ ICT ‐ 2013 ‐ 10
    Duration: September 2013 - August 2016
  • Architectures and algorithms for high-temperature signal processing
    In this cooperative industrial project, architectures for high-temperature electronics applications are being developed in collaboration with Baker Hughes. A particular focus here is on researching communication algorithms for this area of application.
    Led by: Prof. Dr.-Ing. habil H. Blume
    Team: M.Sc. Tobias Stuckenberg
    Year: 2016
  • GEBO - High Temperature Electronic
    In this project, the design of mixed-signal circuits for signal processing is studied under high temperature conditions. For this, research on analog circuits and digital signal processing architectures will be conducted in order to adapt common design approaches to the requirements of high temperature technology.
    Led by: Prof. Dr.-Ing. H. Blume
    Team: Dipl.-Ing. Rochus Nowosielski
    Year: 2014
    Duration: 2009-20111
  • Site-optimized Wireless Communication Architectures
    The communication parameters to be expected in an application scenario result from the combination of the employed standards' properties (IEEE 802.11, BLE, IEEE 802.154, ZigBee) and the specific radio wave propagation conditions of the considered building.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: M.Sc. Daniel Pfefferkorn
    Year: 2014
  • QUANTUS IV - MAIUS
    The Institute of Microelectronic Systems supports physical experiments in space in the QUANTUS IV - MAIUS Project. Within the project platforms and algorithms for digital signal processing in space will be delevoped and evaluated.
    Led by: Prof. Dr.-Ing. Holger Blume
    Team: Dipl.-Ing. Christian Spindeldreier
    Year: 2014
    Funding: "National Space Program" of the Federal Ministry for Economic Affairs and Energy (BMWi)
    Duration: August 2014 - December 2021

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