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Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer. This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster graphics display. The data base applications of the FETCH-AND-ADD instruction, distributed parallel architecture for speech understanding, and two parallel formulations of particle-in-cell models are likewise covered in this text. This publication is suitable for students, researchers and professionals concerned with algorithmically specialized computers.
The use of parallel programming and architectures is essential for simulating and solving problems in modern computational practice. There has been rapid progress in microprocessor architecture, interconnection technology and software devel- ment, which are in?uencing directly the rapid growth of parallel and distributed computing. However, in order to make these bene?ts usable in practice, this dev- opment must be accompanied by progress in the design, analysis and application aspects of parallel algorithms. In particular, new approaches from parallel num- ics are important for solving complex computational problems on parallel and/or distributed systems. The contributions to this book are focused on topics most concerned in the trends of today’s parallel computing. These range from parallel algorithmics, progr- ming, tools, network computing to future parallel computing. Particular attention is paid to parallel numerics: linear algebra, differential equations, numerical integ- tion, number theory and their applications in computer simulations, which together form the kernel of the monograph. We expect that the book will be of interest to scientists working on parallel computing, doctoral students, teachers, engineers and mathematicians dealing with numerical applications and computer simulations of natural phenomena.
This book presents an extensive survey of the state-of-the-art research in parallel computational algorithms and architectures for robot manipulator control and simulation. It deals not only with specifics but also includes general and broader issues which serve as a useful foundation to the topic. The educational flavor of the book makes it a necessary resource for researchers, engineers and students wanting to be familiarized with the potential offered by the application of parallel processing to robotic problems, and its current issues and trends. Contents:Introduction (A K Bejczy & A Fijany)Parallel Algorithms and Architectures for Inverse Dynamics Computation (C S G Lee)Non-Strict Computation of the Manipulator Inertia Matrix (M Amin-Javaheri & D E Orin)Parallel Processing of Robot Control and Simulation (H Kasahara)ASPARC: An Algorithmically Specialized Parallel Architecture for Robotics Computations (A Fijany & A K Bejczy)Multiprocessor Based Trajectory Generation for Multiple Robotic Devices (R Guptill & S Ahmad)Neural Networks for Real-Time Robotic Applications (N B Toomarian et al.) Readership: Computer scientists, applied mathematicians and engineers. keywords:
The Austrian Center for Parallel Computation (ACPC) is a cooperative research organization founded in 1989 to promote research and education in the field of software for parallel computer systems. The areas in which the ACPC is active include algorithms, languages, compilers, programming environments, and applications for parallel and high-performance computing systems. This volume contains the proceedings of the Second International Conference of the ACPC, held in Gmunden, Austria, October 1993. Authors from 17 countries submitted 44 papers, of which 15 were selected for inclusion in this volume, which also includes 4 invited papers by distinguished researchers. The volume is organized into parts on architectures (2 papers), algorithms (7 papers), languages (6 papers), and programming environments (4 papers).
While the architecture of present-day parallel supercomputers is largely based on the concept of a shared memory, with its attendant limitations of common access, advances in semicoductor technology have led to the development of highly parellel computer architectures with decentralized storage and limited connections in which each processor possesses high bandwidth local memory connected to a small number of such architectures, enabling cost-effective high-speed parallel processing for large volumes of data, with ultra-high throughput rates. Algorithms suitable for implementation on systolic arrays find applications in areas such as signal and image processing, pattern matching, linear algebra, recurrence algorithms and graph problems. This book provides an insight into the implementation of systolic arrays and gives a comprehensive overview of the techniques and theories contributing to the design of systolic algorithms.
Even as developments in photorealistic computer graphics continue to affect our work and leisure activities, practitioners and researchers are devoting more and more attention to non-photorealistic (NPR) techniques for generating images that appear to have been created by hand. These efforts benefit every field in which illustrations-thanks to their ability to clarify, emphasize, and convey very precise meanings-offer advantages over photographs. These fields include medicine, architecture, entertainment, education, geography, publishing, and visualization. Non-Photorealistic Computer Graphics is the first and only resource to examine non-photorealistic efforts in depth, providing detailed accounts of the major algorithms, as well as the background information and implementation advice readers need to make headway with these increasingly important techniques. Already, an estimated 10% of computer graphics users require some form of non-photorealism. Strothotte and Schlechtweg's important new book is designed and destined to be the standard NPR reference for this large, diverse, and growing group of professionals. Hard-to-find information needed by a wide range and growing number of computer graphics programmers and applications users. Traces NPR principles and techniques back to their origins in human vision and perception. Focuses on areas that stand to benefit most from advances in NPR, including medical and architectural illustration, cartography, and data visualization. Presents algorithms for two and three-dimensional effects, using pseudo-code where needed to clarify complex steps. Helps readers attain pen-and-ink, pencil-sketch, and painterly effects, in addition to other styles. Explores specific challenges for NPR-including "wrong" marks, deformation, natural media, artistic technique, lighting, and dimensionality. Includes a series of programming projects in which readers can apply the book's concepts and algorithms.
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

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