Projects in the Business Areas High Performance Computing

© Fraunhofer SCAI

QuantumQAP − Hybrid quantum place&route for postquantum cryptographic code synthesis on FPGAs

To develop hardware such as microprocessors, field-programmable gate arrays (FPGAs) are typically used. However, optimizing the interconnection of these logic devices is itself a difficult problem for Turing machines (the so-called Quadratic Assignment Problem or QAP). Quantum or quantum-inspired hardware seems to be a better way to solve this problem. The approach in the QuantumQAP project is to combine quantum hardware and theoretical solution approaches that are applied in the two application fields of FPGA interconnection and post-quantum cryptography.
Project duration: 01/2022 - 12/2024

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Optimization of logistics and production processes – using the example of dynamic route optimization in the warehouse

The dynamic optimization of logistics and production processes in real time is at the top of the wish list of many small and large companies in order to gain a significant reduction of costs while improving machine utilization, workload distribution and product delivery times. Using the example of a fictitious warehouse, it can be shown which optimization measures interlock with each other and how complex processes become manageable even for small companies.

KI Lernlabor

Entering and further training in artificial intelligence

The "Artificial Intelligence Learning Lab" is being set up at the Fraunhofer Institute Center Schloss Birlinghoven in Sankt Augustin. It supports small and medium-sized enterprises (SMEs) in particular in getting started in artificial intelligence (AI), learning about concrete applications, and qualifying employees.
Project duration: 11/2019 - 04/2022

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RoKoRa – secure human-robot collaboration using high-resolution radars

In the RoKoRa project, the aim is to exclude hazards of humans by robots. For this purpose, compact radar systems are used. They offer many advantages: radars operate independently of any lighting and are largely insensitive to environmental conditions. In addition, radar sensors can measure not only the distance to the sensor, but also the motion vector of the detected targets. The sensor system to be developed significantly improves personnel safety in human-robot collaboration, resulting in new degrees of freedom for a safe cooperation with larger robots and at higher distance-dependent execution speeds. In the project, SCAI develops a software component for environmental perception for situational analysis and decision-making using methods of machine learning.

Project duration: 1.7.2017 - 30.6.2020