Mastering C++ Multithreading

Description

Master multithreading and concurrent processing with C++ About This Book Delve into the fundamentals of multithreading and concurrency and find out how to implement them Explore atomic operations to optimize code performance Apply concurrency to both distributed computing and GPGPU processing Who This Book Is For This book is for intermediate C++ developers who wish to extend their knowledge of multithreading and concurrent processing. You should have basic experience with multithreading and be comfortable using C++ development toolchains on the command line. What You Will Learn Deep dive into the details of the how various operating systems currently implement multithreading Choose the best multithreading APIs when designing a new application Explore the use of mutexes, spin-locks, and other synchronization concepts and see how to safely pass data between threads Understand the level of API support provided by various C++ toolchains Resolve common issues in multithreaded code and recognize common pitfalls using tools such as Memcheck, CacheGrind, DRD, Helgrind, and more Discover the nature of atomic operations and understand how they can be useful in optimizing code Implement a multithreaded application in a distributed computing environment Design a C++-based GPGPU application that employs multithreading In Detail Multithreaded applications execute multiple threads in a single processor environment, allowing developers achieve concurrency. This book will teach you the finer points of multithreading and concurrency concepts and how to apply them efficiently in C++. Divided into three modules, we start with a brief introduction to the fundamentals of multithreading and concurrency concepts. We then take an in-depth look at how these concepts work at the hardware-level as well as how both operating systems and frameworks use these low-level functions. In the next module, you will learn about the native multithreading and concurrency support available in C++ since the 2011 revision, synchronization and communication between threads, debugging concurrent C++ applications, and the best programming practices in C++. In the final module, you will learn about atomic operations before moving on to apply concurrency to distributed and GPGPU-based processing. The comprehensive coverage of essential multithreading concepts means you will be able to efficiently apply multithreading concepts while coding in C++. Style and approach This book is filled with examples that will help you become a master at writing robust concurrent and parallel applications in C++. Cover Copyright Credits About the Author About the Reviewer www.PacktPub.com Customer Feedback Table of Contents Preface Chapter 1: Revisiting Multithreading Getting started The multithreaded application Makefile Other applications Summary Chapter 2: Multithreading Implementation on the Processor and OS Defining processes and threads Tasks in x86 (32-bit and 64-bit) Process state in ARM The stack Defining multithreading Flynn's taxonomy Symmetric versus asymmetric multiprocessing Loosely and tightly coupled multiprocessing Combining multiprocessing with multithreading Multithreading types Temporal multithreading Simultaneous multithreading (SMT) Schedulers Tracing the demo application Mutual exclusion implementations Hardware Software Summary Chapter 3: C++ Multithreading APIs API overview POSIX threads Windows support PThreads thread management Mutexes Condition variables Synchronization Semaphores Thread local storage (TLC) Windows threads Thread management Advanced management Synchronization Condition variables Thread local storage Boost Qt QThread Thread pools Synchronization QtConcurrent Thread local storage POCO Thread class Thread pool Thread local storage (TLS) Synchronization C++ threads Putting it together Summary Chapter 4: Thread Synchronization and Communication Safety first The scheduler High-level view Implementation Request class Worker class Dispatcher Makefile Output Sharing data Using r/w-locks Using shared pointers Summary Chapter 5: Native C++ Threads and Primitives The STL threading API Boost.Thread API The 2011 standard C++14 C++17 STL organization Thread class Basic use Passing parameters Return value Moving threads Thread ID Sleeping Yield Detach Swap Mutex Basic use Non-blocking locking Timed mutex Lock guard Unique lock Scoped lock Recursive mutex Recursive timed mutex Shared mutex Shared timed mutex Condition variable Condition_variable_any Notify all at thread exit Future Promise Shared future Packaged_task Async Launch policy Atomics Summary Chapter 6: Debugging Multithreaded Code When to start debugging The humble debugger GDB Debugging multithreaded code Breakpoints Back traces Dynamic analysis tools Limitations Alternatives Memcheck Basic use Error types Illegal read / illegal write errors Use of uninitialized values Uninitialized or unaddressable system call values Illegal frees Mismatched deallocation Overlapping source and destination Fishy argument values Memory leak detection Helgrind Basic use Misuse of the pthreads API Lock order problems Data races DRD Basic use Features C++11 threads support Summary Chapter 7: Best Practices Proper multithreading Wrongful expectations - deadlocks Being careless - data races Mutexes aren't magic Locks are fancy mutexes Threads versus the future Static order of initialization Summary Chapter 8: Atomic Operations - Working with the Hardware Atomic operations Visual C++ GCC Memory order Other compilers C++11 atomics Example Non-class functions Example Atomic flag Memory order Relaxed ordering Release-acquire ordering Release-consume ordering Sequentially-consistent ordering Volatile keyword Summary Chapter 9: Multithreading with Distributed Computing Distributed computing, in a nutshell MPI Implementations Using MPI Compiling MPI applications The cluster hardware Installing Open MPI Linux and BSDs Windows Distributing jobs across nodes Setting up an MPI node Creating the MPI host file Running the job Using a cluster scheduler MPI communication MPI data types Custom types Basic communication Advanced communication Broadcasting Scattering and gathering MPI versus threads Potential issues Summary Chapter 10: Multithreading with GPGPU The GPGPU processing model Implementations OpenCL Common OpenCL applications OpenCL versions OpenCL 1.0 OpenCL 1.1 OpenCL 1.2 OpenCL 2.0 OpenCL 2.1 OpenCL 2.2 Setting up a development environment Linux Windows OS X/MacOS A basic OpenCL application GPU memory management GPGPU and multithreading Latency Potential issues Debugging GPGPU applications Summary Index