Niels Ole Salscheider

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Recently, a variety of accelerator architectures became available in the field of high performance computing. Intel's MIC (Many Integrated Core) and both GPU architectures, NVIDIA's Kepler and AMD's Graphics Core Next, all represent the latest innovation in the field of general purpose computing accelerators. This paper explores several important(More)
With the advent of accelerator-based heterogeneous parallel systems, the need for a solution of the task-device matching problem is increasing. Due to the enormously growing diversity in existing computing architectures, optimal matching promises to deliver high performance at reduced energy costs. By means of OpenCL and particularly the LLVM compiler(More)
Automated vehicles are complex systems with a high degree of interdependencies between its components. This complexity sets increasing demands for the underlying software framework. This paper firstly analyzes the requirements for software frameworks. Afterwards an overview on existing software frameworks, that have been used for automated driving projects,(More)
Cooperative motion planning is still a challenging task for robots. Recently, Value Iteration Networks (VINs) were proposed to model motion planning tasks as Neural Networks. In this work, we extend VINs to solve cooperative planning tasks under non-holonomic constraints. For this, we interconnect multiple VINs to pay respect to each other’s outputs.(More)
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