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Auflistung nach Autor:in "Paul, Johny"

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  • Zeitschriftenartikel
    Acceleration of Optical Flow Computations on Tightly-Coupled Processor Arrays
    (PARS-Mitteilungen: Vol. 30, Nr. 1, 2013) Sousa, Éricles Rodrigues; Tanase, Alexandru; Lari, Vahid; Hannig, Frank; Teich, Jürgen; Paul, Johny; Stechele, Walter; Kröhnert, Manfred; Asfour, Tamin
    Optical flow is widely used in many applications of portable mobile de- vices and automotive embedded systems for the determination of motion of objects in a visual scene. Also in roboticsit is used for motion detection, object segmentation, time-to-contact information, focus of expansion calculations, robot navigation, and automatic parking for vehicles. Similar to many other image processing algorithms, optical flow processes pixel operations repeatedly over whole image frames. Thusit provides a high degree of fine-grained parallelism which can be efficiently exploited on massively parallel processor arrays. In this contextwe propose to accelerate the computation of complex motion estimation vectors on programmable tightly-coupled processor arrays, which offer a high flexibility enabled by coarse-grained reconfiguration capabilities. Novel is also that the degree of parallelism may be adapted to the number of processors that are available to the application. Finallywe present an implementation that is 18 times faster when compared to (a) an FPGA-based soft processor implementationand (b) may be adapted regarding different QoS requirements, hence, being more flexible than a dedicated hardware implementation.
  • Zeitschriftenartikel
    Acceleration of Optical Flow Computations on Tightly-Coupled Processor Arrays
    (PARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware: Vol. 30, No. 1, 2013) Sousa, Éricles; Tanase, Alexandru; Lari, Vahid; Hannig, Frank; Teich, Jürgen; Paul, Johny; Stechele, Walter; Kröhnert, Manfred; Asfour, Tamin
    Optical flow is widely used in many applications of portable mobile devices and automotive embedded systems for the determination of motion of objects in a visual scene. Also in robotics, it is used for motion detection, object segmentation, time-to-contact information, focus of expansion calculations, robot navigation, and automatic parking for vehicles. Similar to many other image processing algorithms, optical flow processes pixel operations repeatedly over whole image frames. Thus, it provides a high degree of fine-grained parallelism which can be efficiently exploited on massively parallel processor arrays. In this context, we propose to accelerate the computation of complex motion estimation vectors on programmable tightly-coupled processor arrays, which offer a high flexibility enabled by coarse-grained reconfiguration capabilities. Novel is also that the degree of parallelism may be adapted to the number of processors that are available to the application. Finally, we present an implementation that is 18 times faster when compared to (a) an FPGA-based soft processor implementation, and (b) may be adapted regarding different QoS requirements, hence, being more flexible than a dedicated hardware implementation.
  • Konferenzbeitrag
    Potentials and challenges for multi-core processors in robotic applications
    (INFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt, 2013) Herkersdorf, Andreas; Paul, Johny; Kumar Pujari, Ravi; Stechele, Walter; Wallentowitz, Stefan; Wild, Thomas; Zaib, Aurang
    Multi-core processors have shown to be superior to single-core with respect to performance and power efficiency. However, multi-core imposes additional challenges on system complexity and application programming. This paper reviews benefits and challenges of multi-core processors in embedded real-time applications like humanoid robotics. Selected approaches towards enabling multi-core processors are shown, covering multiple hardware / software abstraction levels, including isolation of individual applications, differentiated quality-of-service support, thread mpping, and resource-aware programming.