Engineering Applications Of Fpgas


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Partial Reconfiguration on FPGAs


Partial Reconfiguration on FPGAs

Author: Dirk Koch

language: en

Publisher: Springer Science & Business Media

Release Date: 2012-07-25


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This is the first book to focus on designing run-time reconfigurable systems on FPGAs, in order to gain resource and power efficiency, as well as to improve speed. Case studies in partial reconfiguration guide readers through the FPGA jungle, straight toward a working system. The discussion of partial reconfiguration is comprehensive and practical, with models introduced together with methods to implement efficiently the corresponding systems. Coverage includes concepts for partial module integration and corresponding communication architectures, floorplanning of the on-FPGA resources, physical implementation aspects starting from constraining primitive placement and routing all the way down to the bitstream required to configure the FPGA, and verification of reconfigurable systems.

Design for Embedded Image Processing on FPGAs


Design for Embedded Image Processing on FPGAs

Author: Donald G. Bailey

language: en

Publisher: John Wiley & Sons

Release Date: 2011-06-13


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Dr Donald Bailey starts with introductory material considering the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, fine-grained hardware that can readily exploit parallelism within many image processing algorithms. A brief review of FPGA programming languages provides the link between a software mindset normally associated with image processing algorithms, and the hardware mindset required for efficient utilization of a parallel hardware design. The design process for implementing an image processing algorithm on an FPGA is compared with that for a conventional software implementation, with the key differences highlighted. Particular attention is given to the techniques for mapping an algorithm onto an FPGA implementation, considering timing, memory bandwidth and resource constraints, and efficient hardware computational techniques. Extensive coverage is given of a range of low and intermediate level image processing operations, discussing efficient implementations and how these may vary according to the application. The techniques are illustrated with several example applications or case studies from projects or applications he has been involved with. Issues such as interfacing between the FPGA and peripheral devices are covered briefly, as is designing the system in such a way that it can be more readily debugged and tuned. Provides a bridge between algorithms and hardware Demonstrates how to avoid many of the potential pitfalls Offers practical recommendations and solutions Illustrates several real-world applications and case studies Allows those with software backgrounds to understand efficient hardware implementation Design for Embedded Image Processing on FPGAs is ideal for researchers and engineers in the vision or image processing industry, who are looking at smart sensors, machine vision, and robotic vision, as well as FPGA developers and application engineers. The book can also be used by graduate students studying imaging systems, computer engineering, digital design, circuit design, or computer science. It can also be used as supplementary text for courses in advanced digital design, algorithm and hardware implementation, and digital signal processing and applications. Companion website for the book: www.wiley.com/go/bailey/fpga

Engineering Applications of FPGAs


Engineering Applications of FPGAs

Author: Esteban Tlelo-Cuautle

language: en

Publisher: Springer

Release Date: 2016-05-28


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This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. The whole book provides a practical guide to implementing a variety of engineering applications from VHDL programming and co-simulation issues, to FPGA realizations of chaos generators, ANNs for chaotic time-series prediction, RNGs and chaotic secure communications for image transmission.