Intelligent Hardware Lab (IHL)
The Intelligent Hardware Lab (IHL) is a cross-institutional initiative within Technology Area 1 (TA1: Instrumentation) of the Cluster of Excellence Color-meets-Flavor. It brings together expertise in FPGA programming, ASIC design, and microelectronics across the participating institutions (Bonn, TU Dortmund, FH Dortmund, Forschungszentrum Jülich, and Siegen).
The IHL provides a coordinated environment for the development of intelligent detector electronics and advanced data acquisition systems. It combines established strengths in ASIC development with modern FPGA-based technologies, enabling real-time data processing and the deployment of AI/ML methods directly on hardware.
A central focus of the IHL is the development of AI-enabled FPGA hardware for detector systems, including:
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mapping of neural networks to FPGA architectures,
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hardware-aware implementation of machine learning algorithms,
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low-latency real-time processing for detector applications.
A second major focus is the integration of local intelligence in detector ASICs covering:
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efficient digital & analog architectures for AI/ML algorithms,
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in-memory computing with SRAM-based implementations and novel devices,
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programmable eFPGA fabrics and embedded microcontroller cores.
The lab operates in close collaboration with partners across the participating institutions and connects microelectronics expertise with detector development efforts across the cluster. It also maintains links to industry partners and provides access to advanced design tools and fabrication technologies.
Beyond project support, the IHL serves as a platform for research and training in intelligent electronics, fostering collaboration between physicists, engineers, and computer scientists. It supports both current detector projects and the exploration of future technologies for next-generation experiments.
The IHL is conceived as a shared platform within the cluster, enabling close collaboration between detector development, microelectronics, and AI-driven data processing.
Leadership
Prof. Dr.-Ing.
Michael Karagounis
FH Dortmund
Dr.
Qader Dorosti
University of Siegen