Intel Threading Building Blocks: Outfitting C++ for Multi-core Processor Parallelism (Paperback)

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Intel Threading Building Blocks: Outfitting C++ for Multi-core Processor Parallelism (Paperback)

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Description

Multi-core chips from Intel and AMD offer a
dramatic boost in speed and responsiveness, and plenty of opportunities for
multiprocessing on ordinary desktop computers. But they also present a
challenge: More than ever, multithreading is a requirement for good
performance. This guide explains how to maximize the benefits of these
processors through a portable C++ library that works on Windows, Linux,
Macintosh, and Unix systems. With it, you'll learn how to use Intel Threading
Building Blocks (TBB) effectively for parallel programming -- without having
to be a threading expert.Written by James Reinders, Chief Evangelist
of Intel Software Products, and based on the experience of Intel's developers
and customers, this book explains the key tasks in multithreading and how to
accomplish them with TBB in a portable and robust manner. With plenty of
examples and full reference material, the book lays out common patterns of
uses, reveals the gotchas in TBB, and gives important guidelines for choosing
among alternatives in order to get the best performance.You'll learn
how Intel Threading Building Blocks:

Enables you to specify tasks instead of threads for better
portability, easier programming, more understandable source code, and better
performance and scalability in general
Focuses on the goal of parallelizing computationally intensive work
to deliver high-level solutions
Is compatible with other threading packages, and doesn't force you
to pick one package for your entire program
Emphasizes scalable, data-parallel programming, which allows program
performance to increase as you add processors
Relies on generic programming, which enables you to write the best
possible algorithms with the fewest constraints Any C++
programmer who wants to write an application to run on a multi-core system
will benefit from this book. TBB is also very approachable for a C programmer
or a C++ programmer without much experience with templates. Best of all, you
don't need experience with parallel programming or multi-core processors to
use this book.
Table of Contents

Foreword
Note from the Lead Developer of Intel Threading Building Blocks
Preface

1. Why Threading Building Blocks?    
    Overview      Benefits

2. Thinking Parallel      Elements of
   Thinking Parallel      Decomposition  
      Scaling and Speedup      What Is a
   Thread?      Mutual Exclusion and Locks
        Correctness      Abstraction
        Patterns      Intuition

3. Basic Algorithms      Initializing and
   Terminating the Library      Loop Parallelization
        Recursive Range Specifications  
      Summary of Loops

4. Advanced Algorithms      Parallel
   Algorithms for Streams
5. Containers      concurrent_queue
        concurrent_vector    
    concurrent_hash_map
6. Scalable Memory Allocation    
    Limitations      Problems in Memory Allocation
        Memory Allocators    
    Replacing malloc, new, and delete
7. Mutual Exclusion      When to Use Mutual
   Exclusion      Mutexes    
    Mutexes      Atomic Operations
8. Timing
9. Task Scheduler      When Task-Based
   Programming Is Inappropriate      Much Better Than Raw
   Native Threads      Initializing the Library Is Your
   Job      Example Program for Fibonacci Numbers
        Task Scheduling Overview    
    How Task Scheduling Works      Recommended Task
   Recurrence Patterns      Making Best Use of the
   Scheduler      Task Scheduler Interfaces
        Task Scheduler Summary
10. Keys to Success      Key Steps to Success
         Relaxed Sequential Execution  
       Safe Concurrency for Methods and Libraries    
     Debug Versus Release      For Efficiency's Sake
         Enabling Debugging Features  
       Mixing with Other Threading Packages    
     Naming Conventions
11. Examples      The Aha! Factor
         A Few Other Key Points    
     parallel_for Examples      The Game of Life
         Parallel_reduce Examples    
     CountStrings: Using concurrent_hash_map    
     Quicksort: Visualizing Task Stealing      A
    Better Matrix Multiply (Strassen)      Advanced Task
    Programming      Packet Processing Pipeline
         Memory Allocation      Game
    Threading Example      Physics Interaction and Update
    Code      Open Dynamics Engine
12. History and Related Projects    
     Libraries      Languages    
     Pragmas      Generic Programming  
       Caches      Costs of Time Slicing
         Quick Introduction to Lambda Functions
         Further Reading
    Index