Algorithms Sequential Parallel Second Edition
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Algorithms : Sequential & Parallel (2Nd Ed.)
With multi-core processors replacing traditional processors and the movement to multiprocessor workstations and servers, parallel computing has moved from a specialty area to the core of computer science. In order to provide efficient and cost-effective solutions to problems, algorithms must be designed for multiprocessor systems. Algorithms: Sequential and Parallel provides a state-of-the-art approach to an algorithms course. The book considers algorithms, paradigms, and the analysis of solutions to critical problems for sequential and parallel models of computation in a unified fashion. This gives practicing engineers and scientists, undergraduates, and beginning graduate students a background in algorithms for sequential and parallel algorithms within one text. Prerequisites include fundamentals of data structures, discrete mathematics, and calculus.
DESIGN METHODS AND ANALYSIS OF ALGORITHMS, Second Edition
Author: BASU, S. K.
language: en
Publisher: PHI Learning Pvt. Ltd.
Release Date: 2013-04-17
The design of correct and efficient algorithms for problem solving lies at the heart of computer science. This concise text, without being highly specialized, teaches the skills needed to master the essentials of this subject. With clear explanations and engaging writing style, the book places increased emphasis on algorithm design techniques rather than programming in order to develop in the reader the problem-solving skills. The treatment throughout the book is primarily tailored to the curriculum needs of B.Tech. students in computer science and engineering, B.Sc. (Hons.) and M.Sc. students in computer science, and MCA students. The book focuses on the standard algorithm design methods and the concepts are illustrated through representative examples to offer a reader-friendly text. Elementary analysis of time complexities is provided for each example-algorithm. A varied collection of exercises at the end of each chapter serves to reinforce the principles/methods involved. New To This Edition • Additional problems • A new Chapter 14 on Bioinformatics Algorithms • The following new sections: » BSP model (Chapter 0) » Some examples of average complexity calculation (Chapter 1) » Amortization (Chapter 1) » Some more data structures (Chapter 1) » Polynomial multiplication (Chapter 2) » Better-fit heuristic (Chapter 7) » Graph matching (Chapter 9) » Function optimization, neighbourhood annealing and implicit elitism (Chapter 12) • Additional matter in Chapter 15 • Appendix
Transactional Memory, 2nd Edition
Author: Tim Harris
language: en
Publisher: Morgan & Claypool Publishers
Release Date: 2010-10-10
The advent of multicore processors has renewed interest in the idea of incorporating transactions into the programming model used to write parallel programs. This approach, known as transactional memory, offers an alternative, and hopefully better, way to coordinate concurrent threads. The ACI (atomicity, consistency, isolation) properties of transactions provide a foundation to ensure that concurrent reads and writes of shared data do not produce inconsistent or incorrect results. At a higher level, a computation wrapped in a transaction executes atomically - either it completes successfully and commits its result in its entirety or it aborts. In addition, isolation ensures the transaction produces the same result as if no other transactions were executing concurrently. Although transactions are not a parallel programming panacea, they shift much of the burden of synchronizing and coordinating parallel computations from a programmer to a compiler, to a language runtime system, or to hardware. The challenge for the system implementers is to build an efficient transactional memory infrastructure. This book presents an overview of the state of the art in the design and implementation of transactional memory systems, as of early spring 2010. Table of Contents: Introduction / Basic Transactions / Building on Basic Transactions / Software Transactional Memory / Hardware-Supported Transactional Memory / Conclusions