New PDF release: Algorithm-Architecture Matching for Signal and Image

By Xiaolin Chen, Nishan Canagarajah, Jose L. Nunez-Yanez (auth.), Guy Gogniat, Dragomir Milojevic, Adam Morawiec, Ahmet Erdogan (eds.)

ISBN-10: 9048199646

ISBN-13: 9789048199648

ISBN-10: 9048199654

ISBN-13: 9789048199655

Advances in sign and picture processing including expanding computing strength are bringing cellular know-how towards purposes in quite a few domain names like car, health and wellbeing, telecommunication, multimedia, leisure and so forth. the advance of those major functions, concerning a wide variety of algorithms (e.g. sign, snapshot, video, 3D, verbal exchange, cryptography) is classically divided into 3 consecutive steps: a theoretical research of the algorithms, a learn of the objective structure, and at last the implementation. this type of linear layout circulation is achieving its limits as a result of extreme strain on layout cycle and strict functionality constraints. The procedure, referred to as Algorithm-Architecture Matching, goals to leverage layout flows with a simultaneous examine of either algorithmic and architectural concerns, considering a number of layout constraints, in addition to set of rules and structure optimizations, that couldn’t be completed in a different way if thought of individually. Introducing new layout methodologies is needed while dealing with the recent rising purposes as for instance complicated cellular verbal exchange or pictures utilizing sub-micron production applied sciences or 3D-Integrated Circuits. This variety varieties a driver for the longer term evolutions of embedded method designs methodologies.

The major expectancies from method designers’ standpoint are on the topic of tools, instruments and architectures assisting program complexity and layout cycle aid. complicated optimizations are necessary to meet layout constraints and to allow a large popularity of those new technologies.

Algorithm-Architecture Matching for sign and photo Processing offers a suite of chosen contributions from either and academia, addressing assorted facets of Algorithm-Architecture Matching method starting from sensors to architectures layout. The scope of this booklet displays the variety of capability algorithms, together with sign, verbal exchange, picture, video, 3D-Graphics carried out onto quite a few architectures from FPGA to multiprocessor structures. a number of synthesis and source administration recommendations leveraging layout optimizations also are defined and utilized to varied algorithms.

Algorithm-Architecture Matching for sign and photograph Processing will be on every one designer’s and EDA software developer’s shelf, in addition to on people with an curiosity in electronic process layout optimizations facing complex algorithms.

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Read Online or Download Algorithm-Architecture Matching for Signal and Image Processing: Best papers from Design and Architectures for Signal and Image Processing 2007 & 2008 & 2009 PDF

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Extra resources for Algorithm-Architecture Matching for Signal and Image Processing: Best papers from Design and Architectures for Signal and Image Processing 2007 & 2008 & 2009

Example text

To maximize the cache efficiency, the original kernel is transformed to a “phase locked” ray-packet based propagation algorithm. Our results show that well-suited caching strategies can indeed yield significant performance gains during the traversal of both uniform and hierarchical grids. This emphasizes the relevance of semi-general purpose multidimensional predictive caches. 1 Introduction The management of high quantities of data is a challenge for many digital systems. This problem is getting more and more complex with the increase of the quantity of memory embedded in digital integrated systems such as System on Chip (SoC).

Depth ← depth of the c u r r e n t c e l l max_depth ← maximum d e p t h o f t h e t r e e Listing 1 Variables characterizing a ray state octree. On a side note, this approach works for adapting pretty much any algorithm working on octrees to recursive grids, and without increasing its asymptotic cost. To sum up everything, let us consider that a ray propagation state is fully characterized by the variables of Listing 1. The “parameters increments” are the differences between the parameters of the intersection points between the ray and two opposite faces of our cell, for each of the three possible such pairs of faces.

In: Proc data compression conf, pp 501–510 2. Benazza-Benyahia A, Pesquet J-C, Hamdi M (2002) Vector-lifting schemes for lossless coding and progressive archival of multispectral images. IEEE Trans Geosci Remote Sens 40(9):2011–2024 3. Chen X, Canagarajah N, Nunez-Yanez JL, Vitulli R (2007) Hardware architecture for lossless image compression based on context-based modelling and arithmetic coding. In: Proc IEEE int system on chip conf, pp 251–254 4. Dragotti PL, Poggi G, Ragozini ARP (2000) Compression of multispectral images by threedimensional SPIHT algorithm.

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Algorithm-Architecture Matching for Signal and Image Processing: Best papers from Design and Architectures for Signal and Image Processing 2007 & 2008 & 2009 by Xiaolin Chen, Nishan Canagarajah, Jose L. Nunez-Yanez (auth.), Guy Gogniat, Dragomir Milojevic, Adam Morawiec, Ahmet Erdogan (eds.)

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