9781447158882-1447158881-High-Performance Scientific Computing: Algorithms and Applications

High-Performance Scientific Computing: Algorithms and Applications

ISBN-13: 9781447158882
ISBN-10: 1447158881
Edition: 2012
Author: Ananth Grama, Efstratios Gallopoulos, Bernard Philippe, Michael W. Berry, Yousef Saad, Kyle A. Gallivan, Faisal Saied
Publication date: 2014
Publisher: Springer
Format: Paperback 364 pages
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ISBN-13: 9781447158882
ISBN-10: 1447158881
Edition: 2012
Author: Ananth Grama, Efstratios Gallopoulos, Bernard Philippe, Michael W. Berry, Yousef Saad, Kyle A. Gallivan, Faisal Saied
Publication date: 2014
Publisher: Springer
Format: Paperback 364 pages

Summary

High-Performance Scientific Computing: Algorithms and Applications (ISBN-13: 9781447158882 and ISBN-10: 1447158881), written by authors Ananth Grama, Efstratios Gallopoulos, Bernard Philippe, Michael W. Berry, Yousef Saad, Kyle A. Gallivan, Faisal Saied, was published by Springer in 2014. With an overall rating of 3.9 stars, it's a notable title among other Data Processing (Databases & Big Data, Algorithms, Programming, Pure Mathematics, Mathematics) books. You can easily purchase or rent High-Performance Scientific Computing: Algorithms and Applications (Paperback) from BooksRun, along with many other new and used Data Processing books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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; presents outstanding challenges and developing technologies, and puts these in their historical context.
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