Application-specific regular array processors have been widely used in signal and image processing, multimedia and communication systems, for example, in data compression and HDTV. One of the main problems of application-specific computing is how to map algorithms into hardware. The major achievement of the theory of regular arrays is that an algorithm, represented as a data dependence graph, is embedded into a Euclidean space, where the integer points are the elementary computations and the dependencies between computations are denoted by vectors between points. The process of mapping an algorithm into hardware is reduced to finding, for the given Euclidean space, a new coordinate system that can be associated with the physical properties of space and time - so called space-time. The power of the synthesis method is that it provides a bridge between "abstract" and "physical" representations of algorithms, thus providing a methodological basis for synthesizing computations in space and in time. This book will extend the existing synthesis theory by exploiting the associativity and commutativity of computations. The practical upshot being a controlled increase in the dimensionality of the Euclidean space representing an algorithm. This increase delivers more degrees of freedom in the choice of the space-time mapping and leads, subsequently, to more choice in the selection of cost-effective application-specific designs.

Guest Editor: JOSEF A. NOSSEK This is a special issue of the Journal of VLSI Signal Processing comprising eight contributions invited for publica tion on the basis of novel work presented in a special session on "Parallel Processing on VLSI Arrays" at the International Symposium on Circuits and Systems (ISCAS) held in New Orleans in May 1990. Massive parallelism to cope with high-speed requirements stemming from real-time applications and the restrictions in architectural and circuit design, such as regularity and local connectedness, brought about by the VLSI technology are the key questions addressed in these eight papers. They can be grouped into three subsections elaborating on: • Simulation of continuous physical systems, i. e. , numerically solving partial differential equations. • Neural architectures for image processing and pattern recognition. • Systolic architectures for implementing regular and irregular algorithms in VLSI technology. The paper by A. Fettweis and O. Nitsche advocates a signal processing approach for the numerical integration of partial differential equations (PD Es). It is based on the principles of multidimensional wave digital filters (MDWDFs) thereby preserving the passivity of energy dissipating physical systems. It is particularly suited for systems ofPDEs involving time and finite propagation speed. The basic ideas are explained using Maxwell's equa tions as a vehicle for the derivation of a multidimensional equivalent circuit representing the spatially infinitely extended arrangement with only very few circuit elements.

Computer Systems and Software Engineering is a compilation of sixteen state-of-the-art lectures and keynote speeches given at the COMPEURO '92 conference. The contributions are from leading researchers, each of whom gives a new insight into subjects ranging from hardware design through parallelism to computer applications. The pragmatic flavour of the contributions makes the book a valuable asset for both researchers and designers alike. The book covers the following subjects: Hardware Design: memory technology, logic design, algorithms and architecture; Parallel Processing: programming, cellular neural networks and load balancing; Software Engineering: machine learning, logic programming and program correctness; Visualization: the graphical computer interface.

Algorithm engineering allows computer engineers to produce a computational machine that will execute an algorithm as efficiently and cost-effectively as possible given a set of constraints, such as minimal performance or the availability of technology. Addressing algorithm engineering in a parallel setting, regular array syntheses offer powerful co

The past few years have seen a rapid growth in image processing and image communication technologies. New video services and multimedia applications are continuously being designed. Essential for all these applications are image and video compression techniques. The purpose of this book is to report on recent advances in VLSI architectures and their implementation for video signal processing applications with emphasis on video coding for bit rate reduction.Efficient VLSI implementation for video signal processing spans a broad range of disciplines involving algorithms, architectures, circuits, and systems. Recent progress in VLSI architectures and implementations has resulted in the reduction in cost and size of video signal processing equipment and has made video applications more practical.The topics covered in this volume demonstrate the increasingly interdisciplinary nature of VLSI implementation of video signal processing applications, involving interactions between algorithms, VLSI architectures, circuit techniques, semiconductor technologies and CAD for microelectronics.