Titlebook: Applied Reconfigurable Computing; 12th International S Vanderlei Bonato,Christos Bouganis,Marek Gorgon Conference proceedings 2016 Springer

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The VINEYARD Approach: Versatile, Integrated, Accelerator-Based, Heterogeneous Data Centresof servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy efficiency of customized accelerators. VINEYARD aims to develop an integrated platform for energy-efficient data centres based on new servers with novel, coarse-grain an

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A Design Methodology for the Next Generation Real-Time Vision Processorsughput with complex applications, under real-time embedded constraints (time, fault-tolerance, silicon area and power consumption). To achieve these goals, we propose the fusion of two key concepts: the Focal-Plane Image Processing (FPIP) and the Many-Core architectures. We show the concepts and ide

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An Efficient Hardware Architecture for Block Based Image Processing Algorithmsck based image processing. For case study a?block based optical flow histogram computation application was selected. The proposed solution allows for a?2.3x and 6.3x speed-up for fixed-point and floating-point calculations respectively. This enables real-time operations for . pixels or higher resolu

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An FPGA Stereo Matching Processor Based on the Sum of Hamming Distancesg mapping and three-dimensional reconstruction of objects. In area-based algorithms, the similarity between one pixel of an image (key frame) and one pixel of another image is measured using a correlation index computed on neighbors of these pixels (correlation windows). In order to preserve edges,

Hemodialysis

安心地散步

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A Scalable Dataflow Accelerator for Real Time Onboard Hyperspectral Image Classificationt Support Vector Machines (SVMs) can achieve high classification accuracy, but unfortunately it is very computationally expensive. This paper presents a scalable dataflow accelerator on FPGA for real-time SVM classification of hyperspectral images.To address data dependencies, we adapt multi-class c

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