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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12008/38796 How to cite
Title: Dataflow-based mapping of computer vision algorithms onto FPGAs
Authors: Sen, Mainak
Corretjer, I
Haim, Fiorella
Silveyra, Andrés
Schlessman, Jason
Thiehan, Lv
Bhattacharyya, Shuvra S
Wolf, Wayne
Type: artículo
Issue Date: 2007
Abstract: We develop a design methodology for mapping computer vision algorithms onto an FPGA through the use of coarse-grain reconfigurable dataflow graphs as a representation to guide the designer. We first describe a new dataflow modeling technique called homogeneous parameterized dataflow (HPDF), which effectively captures the structure of an important class of computer vision applications. This form of dynamic dataflow takes advantage of the property that in a large number of image processing applications, data production and consumption rates can vary, but are equal across dataflow graph edges for any particular application iteration. After motivating and defining the HPDF model of computation, we develop an HPDF-based design methodology that offers useful properties in terms of verifying correctness and exposing performance-enhancing transformations, we discuss and address various challenges in efficiently mapping an HPDF-based application representation into target-specific HDL code, and we present experimental results pertaining to the mapping of a gesture recognition application onto the Xilinx Virtex II FPGA.
Publisher: Hindawi Publishing Corporation
IN: EURASIP Journal on Embedded Systems, 2007, Article ID 49236
Citation: Sen, M, Corretjer, I, Haim, F, Silveyra, A, Schlessman, J, Thiehan, Lv, Bhattacharyya, S, Wolf, W. “Dataflow-based mapping of computer vision algorithms onto FPGAs”. EURASIP Journal on Embedded Systems, 2007, Article ID 49236. Doi 10.1155/2007/49236
License: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Appears in Collections:Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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