The authors provide an in-depth, comprehensive examination of hierarchical parallel systems within a comparative and taxonomical framework. They include a general introduction to hierarchical structures, possible topologies, and possible designs; an in-depth discussion of all proposed or built hierarchical parallel systems; and language supports and programming strategies. Their work will serve as both a teacher and reference to programmers and students in computer sciences and electrical engineering.

Create low power, higher performance circuits with shorter design times using this practical guide to asynchronous design. This practical alternative to conventional synchronous design enables performance close to full-custom designs with design times that approach commercially available ASIC standard cell flows. It includes design trade-offs, specific design examples, and end-of-chapter exercises. Emphasis throughout is placed on practical techniques and real-world applications, making this ideal for circuit design students interested in alternative design styles and system-on-chip circuits, as well as circuit designers in industry who need new solutions to old problems.

This book deals with the creation of local innovation systems (LIS) in emerging countries. The authors analyze the role of the government, firms and research centers in the formation of LIS. Special attention is paid to the manner in which different leading actors implement their LIS development strategies. The book presents detailed case studies on different strategies used to implement LIS in Singapore, Dubai, Taiwan and Iran.

Computer vision deals with the problem of manipulating information contained in large quantities of sensory data, where raw data emerge from the transducing 6 7 sensors at rates between 10 to 10 pixels per second. Conventional general purpose computers are unable to achieve the computation rates required to op erate in real time or even in near real time, so massively parallel systems have been used since their conception in this important practical application area. The development of massively parallel computers was initially character ized by efforts to reach a speedup factor equal to the number of processing elements (linear scaling assumption). This behavior pattern can nearly be achieved only when there is a perfect match between the computational struc ture or data structure and the system architecture. The theory of hierarchical modular systems (HMSs) has shown that even a small number of hierarchical levels can sizably increase the effectiveness of very large systems. In fact, in the last decade several hierarchical architectures that support capabilities which can overcome performances gained with the assumption of linear scaling have been proposed. Of these architectures, the most commonly considered in com puter vision is the one based on a very large number of processing elements (PEs) embedded in a pyramidal structure. Pyramidal architectures supply the same image at different resolution lev els, thus ensuring the use of the most appropriate resolution for the operation, task, and image at hand.