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An introduction to parallel programm...
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Pacheco, Peter S.
An introduction to parallel programming /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
An introduction to parallel programming // Peter S. Pacheco.
作者:
Pacheco, Peter S.
出版者:
Amsterdam ;Morgan Kaufmann, : 2011.,
面頁冊數:
xix, 370 p. :ill. ; : 25 cm.;
標題:
Parallel programming (Computer science) -
ISBN:
9780123742605 (hbk.) :
An introduction to parallel programming /
Pacheco, Peter S.
An introduction to parallel programming /
Peter S. Pacheco. - Amsterdam ;Morgan Kaufmann,2011. - xix, 370 p. :ill. ;25 cm.
Includes bibliographical references (p. 357-359) and index.
Machine generated contents note: 1 Why Parallel Computing1.1 Why We Need Ever-Increasing Performance 1.2 Why We're Building Parallel Systems 1.3 Why We Need to Write Parallel Programs 1.4 How Do We Write Parallel Programs? 1.5 What We'll Be Doing 1.6 Concurrent, Parallel, Distributed 1.7 The Rest of the Book 1.8 A Word of Warning 1.9 Typographical Conventions 1.10 Summary 1.11 Exercises 2 Parallel Hardware and Parallel Software2.1 Some Background 2.2 Modifications to the von Neumann Model 2.3 Parallel Hardware 2.4 Parallel Software 2.5 Input and Output 2.6 Performance 2.7 Parallel Program Design 2.8 Writing and Running Parallel Programs 2.9 Assumptions 2.10 Summary 2.11 Exercises 3 Distributed Memory Programming with MPI3.1 Getting Started 3.2 The Trapezoidal Rule in MPI 3.3 Dealing with I/O 3.4 Collective Communication 3.5 MPI Derived Datatypes 3.7 A Parallel Sorting Algorithm 3.8 Summary3.9 Exercises 3.10 Programming Assignments 4 Shared Memory Programming with Pthreads4.1 Processes, Threads and Pthreads 4.2 Hello, World4.3 Matrix-Vector Multiplication 4.4 Critical Sections 4.5 Busy-Waiting 4.6 Mutexes 4.7 Producer-Consumer Synchronization and Semaphores 4.8 Barriers and Condition Variables 4.9 Read-Write Locks 4.10 Caches, Cache-Coherence, and False Sharing 4.11 Thread-Safety 4.12 Summary 4.13 Exercises4.14 Programming Assignments 5 Shared Memory Programming with OpenMP5.1 Getting Started 5.2 The Trapezoidal Rule 5.3 Scope of Variables 5.4 The Reduction Clause 5.5 The Parallel For Directive 5.6 More About Loops in OpenMP: Sorting 5.7 Scheduling Loops 5.8 Producers and Consumers 5.9 Caches, Cache-Coherence, and False Sharing 5.10 Thread-Safety 5.11 Summary 5.12 Exercises 5.13 Programming Assignments 6 Parallel Program Development6.1 Two N-Body Solvers 6.2 Tree Search 6.3 A Word of Caution 6.4 Which API? 6.5 Summary 6.6 Exercises 6.7 Programming Assignments 7 Where to Go from Here.
Author Peter Pacheco uses a tutorial approach to show students how to develop effective parallel programs with MPI, Pthreads, and OpenMP. The first undergraduate text to directly address compiling and running parallel programs on the new multi-core and cluster architecture, An Introduction to Parallel Programming explains how to design, debug, and evaluate the performance of distributed and shared-memory programs. User-friendly exercises teach students how to compile, run and modify example programs.
ISBN: 9780123742605 (hbk.) :NT2403
LCCN: 2010039584
Nat. Bib. No.: GBB0B0034bnbSubjects--Topical Terms:
557472
Parallel programming (Computer science)
LC Class. No.: QA76.642 / .P29 2011
Dewey Class. No.: 005.2/75
An introduction to parallel programming /
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An introduction to parallel programming /
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Amsterdam ;
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Includes bibliographical references (p. 357-359) and index.
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Machine generated contents note: 1 Why Parallel Computing1.1 Why We Need Ever-Increasing Performance 1.2 Why We're Building Parallel Systems 1.3 Why We Need to Write Parallel Programs 1.4 How Do We Write Parallel Programs? 1.5 What We'll Be Doing 1.6 Concurrent, Parallel, Distributed 1.7 The Rest of the Book 1.8 A Word of Warning 1.9 Typographical Conventions 1.10 Summary 1.11 Exercises 2 Parallel Hardware and Parallel Software2.1 Some Background 2.2 Modifications to the von Neumann Model 2.3 Parallel Hardware 2.4 Parallel Software 2.5 Input and Output 2.6 Performance 2.7 Parallel Program Design 2.8 Writing and Running Parallel Programs 2.9 Assumptions 2.10 Summary 2.11 Exercises 3 Distributed Memory Programming with MPI3.1 Getting Started 3.2 The Trapezoidal Rule in MPI 3.3 Dealing with I/O 3.4 Collective Communication 3.5 MPI Derived Datatypes 3.7 A Parallel Sorting Algorithm 3.8 Summary3.9 Exercises 3.10 Programming Assignments 4 Shared Memory Programming with Pthreads4.1 Processes, Threads and Pthreads 4.2 Hello, World4.3 Matrix-Vector Multiplication 4.4 Critical Sections 4.5 Busy-Waiting 4.6 Mutexes 4.7 Producer-Consumer Synchronization and Semaphores 4.8 Barriers and Condition Variables 4.9 Read-Write Locks 4.10 Caches, Cache-Coherence, and False Sharing 4.11 Thread-Safety 4.12 Summary 4.13 Exercises4.14 Programming Assignments 5 Shared Memory Programming with OpenMP5.1 Getting Started 5.2 The Trapezoidal Rule 5.3 Scope of Variables 5.4 The Reduction Clause 5.5 The Parallel For Directive 5.6 More About Loops in OpenMP: Sorting 5.7 Scheduling Loops 5.8 Producers and Consumers 5.9 Caches, Cache-Coherence, and False Sharing 5.10 Thread-Safety 5.11 Summary 5.12 Exercises 5.13 Programming Assignments 6 Parallel Program Development6.1 Two N-Body Solvers 6.2 Tree Search 6.3 A Word of Caution 6.4 Which API? 6.5 Summary 6.6 Exercises 6.7 Programming Assignments 7 Where to Go from Here.
520
#
$a
Author Peter Pacheco uses a tutorial approach to show students how to develop effective parallel programs with MPI, Pthreads, and OpenMP. The first undergraduate text to directly address compiling and running parallel programs on the new multi-core and cluster architecture, An Introduction to Parallel Programming explains how to design, debug, and evaluate the performance of distributed and shared-memory programs. User-friendly exercises teach students how to compile, run and modify example programs.
650
# 0
$a
Parallel programming (Computer science)
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557472
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