Distributed and Parallel Computing

Preface

Distributed computing, or running programs across multiple computers over a network, is becoming a popular solution to address the demands for increased performance in both high-performance scientific computing and more “general-purpose” applications. In industries like scientific computing, oil exploration, biotechnology, and medicine that demand high processing performance, parallel computing is typically employed. A parallel computer is made up of several identical processing units that work together and communicate to solve complex computing tasks more efficiently. A symmetric multiprocessor with shared memory, a massively parallel system with distributed memory, and a loosely linked cluster of dispersed workstations are examples of common parallel computer design. To tackle computing problems in parallel, certain algorithms are frequently needed. High-speed connections connecting the resources of parallel computers spread globally make remote parallel computing feasible and extremely effective. This is because the cost of communication and work migration is substantially lower than the cost of calculation.

This book addresses many topics related to intelligent and distributed computing, systems, and applications, including adaptivity and learning; agents and multiagent systems; argumentation; case-based reasoning; collaborative systems; distributed algorithms; formal modeling and verification; genetic algorithms; image and signal processing and grid computing; ...