Unleash The System On Chip Using Fpgas And Handel C
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Unleash the System On Chip using FPGAs and Handel C
Author: Rajanish K. Kamat
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-03-05
With the rapid advances in technology, the conventional academic and research departments of Electronics engineering, Electrical Engineering, Computer Science, Instrumentation Engineering over the globe are forced to come together and update their curriculum with few common interdisciplinary courses in order to come out with the engineers and researchers with muli-dimensional capabilities. The gr- ing perception of the ‘Hardware becoming Soft’ and ‘Software becoming Hard’ with the emergence of the FPGAs has made its impact on both the hardware and software professionals to change their mindset of working in narrow domains. An interdisciplinary field where ‘Hardware meets the Software’ for undertaking se- ingly unfeasible tasks is System on Chip (SoC) which has become the basic pl- form of modern electronic appliances. If it wasn’t for SoCs, we wouldn’t be driving our car with foresight of the traffic congestion before hand using GPS. Without the omnipresence of the SoCs in our every walks of life, the society is wouldn’t have evidenced the rich benefits of the convergence of the technologies such as audio, video, mobile, IPTV just to name a few. The growing expectations of the consumers have placed the field of SoC design at the heart of at variance trends. On one hand there are challenges owing to design complexities with the emergence of the new processors, RTOS, software protocol stacks, buses, while the brutal forces of deep submicron effects such as crosstalk, electromigration, timing closures are challe- ing the design metrics.
Harnessing VLSI System Design with EDA Tools
Author: Rajanish K. Kamat
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-10-03
With the proliferation of VHDL, the reference material also grew in the same order. Today there is good amount of scholarly literature including many books describing various aspects of VHDL. However, an indepth review of these books reveals a different story. Many of them have emerged simply as an improved version of the manual. While some of them deal with the system design issues, they lack appropriate exemplifying to illustrate the concepts. Others give large number of examples, but lack the VLSI system design issues. In nutshell, the fact which gone unnoticed by most of the books, is the growth of the VLSI is not merely due to the language itself, but more due to the development of large number of third party tools useful from the FPGA or semicustom ASIC realization point of view. In the proposed book, the authors have synergized the VHDL programming with appropriate EDA tools so as to present a full proof system design to the readers. In this book along with the VHDL coding issues, the simulation and synthesis with the various toolsets enables the potential reader to visualize the final design. The VHDL design codes have been synthesized using different third party tools such as Xilinx Web pack Ver.11, Modelsim PE, Leonrado Spectrum and Synplify Pro. Mixed flow illustrated by using the above mentioned tools presents an insight to optimize the design with reference to the spatial, temporal and power metrics.
Artificial Neural Networks and Machine Learning -- ICANN 2012
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.