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"This volume presents the locality-sensitive approach to distributed network algorithms-the utilization of locality to simplify control structures and algorithms and reduce their costs. The author begins with an introductory exposition of distributed network algorithms focusing on topics that illustrate the role of locality in distributed algorithmic techniques. He then introduces locality-preserving network representations and describes sequential and distributed techniques for their construction. Finally, the applicability of the locality-sensitive approach is demonstrated through several applications. Distributed Computing: A Locality-Sensitive Approach is the only book that gives a thorough exposition of network spanners and other locality-preserving network representations such as sparse covers and partitions. The book is useful for computer scientists interested in distributed computing, electrical engineers interested in network architectures and protocols, and for discrete mathematicians and graph theorists."

"This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. Features : includes contributions from an international selection of world-class authorities, examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques, reviews emerging applications of numerical methods in information retrieval and data mining, discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems, and presents outstanding challenges and developing technologies, and puts these in their historical context."