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Chapman and Hall/CRC Computational Science Ser.: Scientific Computing LIKE NEW
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- ¡Cómpralo ya!Chapman and Hall/CRC Computational Science Ser.: Scientific Computing LIKE NEW
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Características del artículo
- Estado
- Como nuevo
- Notas del vendedor
- “No hi-lighting writing or notes in text. Cover has very little shelf wear. Binding is strong.”
- ISBN
- 9781439825365
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Product Identifiers
Publisher
CRC Press LLC
ISBN-10
143982536X
ISBN-13
9781439825365
eBay Product ID (ePID)
12038822646
Product Key Features
Number of Pages
514 Pages
Language
English
Publication Name
Scientific Computing with Multicore and Accelerators
Publication Year
2010
Subject
Engineering (General), Number Systems, General, Arithmetic
Type
Textbook
Subject Area
Mathematics, Computers, Technology & Engineering
Series
Chapman and Hall/Crc Computational Science Ser.
Format
Hardcover
Dimensions
Item Height
1.3 in
Item Weight
29.7 Oz
Item Length
9.5 in
Item Width
6.5 in
Additional Product Features
Intended Audience
College Audience
LCCN
2010-037123
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
502.85
Table Of Content
Dense Linear Algebra Implementing Matrix Multiplication on the Cell B.E, Wesley Alvaro, Jakub Kurzak, and Jack Dongarra Implementing Matrix Factorizations on the Cell BE, Jakub Kurzak and Jack Dongarra Dense Linear Algebra for Hybrid GPU-Based Systems, Stanimire Tomov and Jack Dongarra BLAS for GPUs, Rajib Nath, Stanimire Tomov, and Jack Dongarra Sparse Linear Algebra Sparse Matrix-Vector Multiplication on Multicore and Accelerators, Samuel Williams, Nathan Bell, Jee Whan Choi, Michael Garland, Leonid Oliker, and Richard Vuduc Multigrid Methods Hardware-Oriented Multigrid Finite Element Solvers on GPU-Accelerated Clusters, Stefan Turek, Dominik Göddeke, Sven H.M. Buijssen, and Hilmar Wobker Mixed-Precision GPU-Multigrid Solvers with Strong Smoothers, Dominik Göddeke and Robert Strzodka Fast Fourier Transforms Designing Fast Fourier Transform (FFT) for the IBM Cell BE, Virat Agarwal and David A. Bader Implementing FFTs on Multicore Architectures, Alex Chunghen Chow, Gordon C. Fossum, and Daniel A. Brokenshire Combinatorial Algorithms Combinatorial Algorithm Design on the Cell/BE Processor, David A. Bader, Virat Agarwal, Kamesh Madduri, and Fabrizio Petrini Stencil Algorithms Auto-Tuning Stencil Computations on Multicore and Accelerators, Kaushik Datta, Samuel Williams, Vasily Volkov, Jonathan Carter, Leonid Oliker, John Shalf, and Katherine Yelick Manycore Stencil Computations in Hyperthermia Applications, Matthias Christen, Olaf Schenk, Esra Neufeld, Maarten Paulides, and Helmar Burkhart Bioinformatics Enabling Bioinformatics Algorithms on the Cell/BE Processor, Vipin Sachdeva, Michael Kistler, and Tzy-Hwa Kathy Tzeng Pairwise Computations on the Cell Processor, Abhinav Sarje, Jaroslaw Zola, and Srinivas Aluru Molecular Modeling Drug Design on the Cell BE, Cecilia González-Álvarez, Harald Servat, Daniel Cabrera-Benítez, Xavier Aguilar, Carles Pons, Juan Fernández-Recio, and Daniel Jiménez-González GPU Algorithms for Molecular Modeling, John E. Stone, David J. Hardy, Barry Isralewitz, and Klaus Schulten Complementary Topics Dataflow Frameworks for Emerging Heterogeneous Architectures and Their Application to Biomedicine, Umit V. Catalyurek, Renato Ferreira, Timothy D.R. Hartley, George Teodoro, and Rafael Sachetto Accelerator Support in the Charm++ Parallel Programming Model, Laxmikant V. Kalé, David M. Kunzman, and Lukasz Wesolowski Efficient Parallel Scan Algorithms for Manycore GPUs, Shubhabrata Sengupta, Mark Harris, Michael Garland, and John D. Owens High Performance Topology-Aware Communication in Multicore Processors, Hari Subramoni, Fabrizio Petrini, Virat Agarwal, and Davide Pasetto Index
Synopsis
The hybrid/heterogeneous nature of future microprocessors and large high-performance computing systems will result in a reliance on two major types of components: multicore/manycore central processing units and special purpose hardware/massively parallel accelerators. While these technologies have numerous benefits, they also pose substantial performance challenges for developers, including scalability, software tuning, and programming issues. Researchers at the Forefront Reveal Results from Their Own State-of-the-Art Work Edited by some of the top researchers in the field and with contributions from a variety of international experts, Scientific Computing with Multicore and Accelerators focuses on the architectural design and implementation of multicore and manycore processors and accelerators, including graphics processing units (GPUs) and the Sony Toshiba IBM (STI) Cell Broadband Engine (BE) currently used in the Sony PlayStation 3. The book explains how numerical libraries, such as LAPACK, help solve computational science problems; explores the emerging area of hardware-oriented numerics; and presents the design of a fast Fourier transform (FFT) and a parallel list ranking algorithm for the Cell BE. It covers stencil computations, auto-tuning, optimizations of a computational kernel, sequence alignment and homology, and pairwise computations. The book also evaluates the portability of drug design applications to the Cell BE and illustrates how to successfully exploit the computational capabilities of GPUs for scientific applications. It concludes with chapters on dataflow frameworks, the Charm++ programming model, scan algorithms, and a portable intracore communication framework. Explores the New Computational Landscape of Hybrid Processors By offering insight into the process of constructing and effectively using the technology, this volume provides a thorough and practical introduction to the area of hybrid computing. It discusses introductory concepts and simple examples of parallel computing, logical and performance debugging for parallel computing, and advanced topics and issues related to the use and building of many applications.
LC Classification Number
QA76.57
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