Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Predictive NoC Architecture for Vision Systems Dedicated to Image Analysis | Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2007 Article ID 97929 13 pages doi 2007 97929 Research Article A Predictive NoC Architecture for Vision Systems Dedicated to Image Analysis Virginie Fresse Alain Aubert and Nathalie Bochard Laboratoire de Traitementdu Signal et Instrumentation CNRS-UMR 5516 Universite Jean Monnet Saint-Étienne BatimentF 18 Rue Benoit Lauras 42000 Saint Etienne Cedex 2 France Received 1 May 2006 Revised 16 October 2006 Accepted 26 December 2006 Recommended by Dietmar Dietrich The aim of this paper is to describe an adaptive and predictive FPGA embedded architecture for vision systems dedicated to image analysis. A large panel of image analysis algorithms with some common characteristics must be mapped onto this architecture. Major characteristics of such algorithms are extracted to define the architecture. This architecture must easily adapt its structure to algorithm modifications. According to required modifications few parts must be either changed or adapted. An NoC approach is used to break the hardware resources down as stand-alone blocks and to improve predictability and reuse aspects. Moreover this architecture is designed using a globally asynchronous locally synchronous approach so that each local part can be optimized separately to run at its best frequency. Timing and resource prediction models are presented. With these models the designer defines and evaluates the appropriate structure before the implementation process. The implementation of a particle image velocimetry algorithm illustrates this adaptation. Experimental results and predicted results are close enough to validate our prediction models for PIV algorithms. Copyright 2007 Virginie Fresse et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION More and .
