Editorial Reviews Product Description Foundations of Multithreaded, Parallel, and Distributed Programming covers-and then applies-the core concepts and techniques needed for an introductory course in this topic. The book emphasizes the practice and application of parallel systems, using real-world examples throughout. Greg Andrews teaches the fundamental concepts of multithread...(展开全部)

This book covers the breadth of Haskell's diverse selection of programming APIs for concurrent and parallel programming. It is split into two parts. The first part, on parallel programming, covers the techniques for using multiple processors to speed up CPU-intensive computations, including methods for using parallelism in both idiomatic Haskell and numerical array-based algori...(展开全部)

This book covers the breadth of Haskell's diverse selection of programming APIs for concurrent and parallel programming. It is split into two parts. The first part, on parallel programming, covers the techniques for using multiple processors to speed up CPU-intensive computations, including methods for using parallelism in both idiomatic Haskell and numerical array-based algori...(展开全部)

The book focuses on algorithmic principles rather than language syntax with an emphasis on the use of the Spin model checker for modeling concurrent systems and verifying program correctness and includes and explains the implementation of concurrency in the Java and Ada languages. It also helps to facilitate lab work with software tools for learning concurrent and distributed p...(展开全部)

Designed for undergraduate/graduate-level parallel programming courses. This nontheoretical, highly accessible text-which is linked to real parallel programming software-covers the techniques of parallel programming in a practical manner that enables students to write and evaluate their parallel programs. Supported by the National Science Foundation and exhaustively class-teste...(展开全部)

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements....(展开全部)

This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements....(展开全部)

The advent of new architectures and computing platforms mean that synchronization and concurrent computing are among the most important topics in computing science. Concurrent programs are made up of cooperating entities -- processors, processes, agents, peers, sensors -- and synchronization is the set of concepts, rules and mechanisms that allow them to coordinate their local ...(展开全部)