Multicore and GPU Programming,

Edition 1 An Integrated Approach

Editors: By Gerassimos Barlas

Publication Date: 17 Nov 2014

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Multicore and GPU Programming offers broad coverage of the key parallel computing skillsets: multicore CPU programming and manycore "massively parallel" computing. Using threads, OpenMP, MPI, and CUDA, it teaches the design and development of software capable of taking advantage of today’s computing platforms incorporating CPU and GPU hardware and explains how to transition from sequential programming to a parallel computing paradigm.

Presenting material refined over more than a decade of teaching parallel computing, author Gerassimos Barlas minimizes the challenge with multiple examples, extensive case studies, and full source code. Using this book, you can develop programs that run over distributed memory machines using MPI, create multi-threaded applications with either libraries or directives, write optimized applications that balance the workload between available computing resources, and profile and debug programs targeting multicore machines.

Key Features

Comprehensive coverage of all major multicore programming tools, including threads, OpenMP, MPI, and CUDA
Demonstrates parallel programming design patterns and examples of how different tools and paradigms can be integrated for superior performance
Particular focus on the emerging area of divisible load theory and its impact on load balancing and distributed systems
Download source code, examples, and instructor support materials on the book's companion website

About the author

By Gerassimos Barlas, Professor, Computer Science and Engineering Department, American University of Sharjah, UAE

Dedication
List of Tables
Preface
- What is in this Book
- Using this Book as a Textbook
- Software and Hardware Requirements
- Sample Code
Chapter 1: Introduction
- Abstract
- In this chapter you will
- 1.1 The era of multicore machines
- 1.2 A taxonomy of parallel machines
- 1.3 A glimpse of contemporary computing machines
- 1.4 Performance metrics
- 1.5 Predicting and measuring parallel program performance
- Exercises
Chapter 2: Multicore and parallel program design
- Abstract
- In this chapter you will
- 2.1 Introduction
- 2.2 The PCAM methodology
- 2.3 Decomposition patterns
- 2.4 Program structure patterns
- 2.5 Matching decomposition patterns with program structure patterns
- Exercises
Chapter 3: Shared-memory programming: threads
- Abstract
- In this chapter you will
- 3.1 Introduction
- 3.2 Threads
- 3.3 Design concerns
- 3.4 Semaphores
- 3.5 Applying semaphores in classical problems
- 3.6 Monitors
- 3.7 Applying monitors in classical problems
- 3.8 Dynamic vs. static thread management
- 3.9 Debugging multithreaded applications
- 3.10 Higher-level constructs: multithreaded programming without threads
- Exercises
Chapter 4: Shared-memory programming: OpenMP
- Abstract
- In this chapter you will
- 4.1 Introduction
- 4.2 Your first OpenMP program
- 4.3 Variable scope
- 4.4 Loop-level parallelism
- 4.5 Task parallelism
- 4.6 Synchronization constructs
- 4.7 Correctness and optimization issues
- 4.8 A case study: sorting in OpenMP
Chapter 5: Distributed memory programming
- Abstract
- In this chapter you will
- 5.1 Communicating processes
- 5.2 MPI
- 5.3 Core concepts
- 5.4 Your first MPI program
- 5.5 Program architecture
- 5.6 Point-to-point communication
- 5.7 Alternative point-to-point communication modes
- 5.8 Non blocking communications
- 5.9 Point-to-point communications: summary
- 5.10 Error reporting and handling
- 5.11 Collective communications
- 5.12 Communicating objects
- 5.13 Node management: communicators and groups
- 5.14 One-sided communications
- 5.15 I/O considerations
- 5.16 Combining MPI processes with threads
- 5.17 Timing and performance measurements
- 5.18 Debugging and profiling MPI Programs
- 5.19 The boost.MPI Library
- 5.20 A case study: diffusion-limited aggregation
- 5.21 A case study: brute-force encryption cracking
- 5.22 A case study: MPI implementation of the master-worker pattern
- Exercises
Chapter 6: GPU programming
- Abstract
- In this chapter you will
- 6.1 GPU programming
- 6.2 CUDA’S programming model: Threads, blocks, and grids
- 6.3 CUDA’S execution model: Streaming multiprocessors and warps
- 6.4 CUDA compilation process
- 6.5 Putting together a CUDA project
- 6.6 Memory hierarchy
- 6.7 Optimization techniques
- 6.8 Dynamic parallelism
- 6.9 Debugging CUDA programs
- 6.10 Profiling CUDA programs
- 6.11 CUDA and MPI
- 6.12 Case studies
- Exercises
Chapter 7: The Thrust template library
- Abstract
- In this chapter you will
- 7.1 Introduction
- 7.2 First steps in thrust
- 7.3 Working with thrust datatypes
- 7.4 Thrust algorithms
- 7.5 Fancy iterators
- 7.6 Switching device back ends
- 7.7 Case studies
- Exercises
Chapter 8: Load balancing
- Abstract
- In this chapter you will
- 8.1 Introduction
- 8.2 Dynamic load balancing: the linda legacy
- 8.3 Static load balancing: the divisible load theory approach
- 8.4 Dltlib: a library for partitioning workloads
- 8.5 Case studies
- Exercises
Appendix A: Compiling Qt programs
- A.1 Using an IDE
- A.2 The qmake Utility
Appendix B: Running MPI programs: preparatory configuration steps
- B.1 Preparatory Steps
- B.2 Computing Nodes Discovery for MPI Program Deployment
Appendix C: Time measurement
- C.1 Introduction
- C.2 Posix High-Resolution Timing
- C.3 Timing in Qt
- C.4 Timing in OpenMP
- C.5 Timing in MPI
- C.6 Timing in CUDA
Appendix D: Boost.MPI
- D.1 Mapping from MPI C to Boost.MPI
Appendix E: Setting up CUDA
- E.1 Installation
- E.2 Issues with GCC
- E.3 Running CUDA Without an Nvidia GPU
- E.4 Running CUDA on Optimus-Equipped Laptops
- E.5 Combining CUDA with Third-Party Libraries
Appendix F: DLTlib
- F.1 DLTlib Functions
- F.2 Dltlib Files
Glossary
Bibliography
Index

ISBN: 9780124171374

Page Count: 698

Retail Price :

Pacheco, An Introduction to Parallel Programming, Morgan Kaufmann, 9780123742605, 2011, $79.95
Herlihy & Shavit, The Art of Multiprocessor Programming Revised Ed, Morgan Kaufmann, 9780123973375, 2012, $74.95
Kirk & Hwu, Programming Massively Parallel Programming 2e, Morgan Kaufmann, 9780124159921, 2012, $74.95

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