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Mastering C++ Multithreading
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++.
244 pages, Kindle Edition
Published July 28, 2017
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December 6, 2022Feels like reviewing an os book like three easy pieces before or at the same time as reading this one might help see what's happening more clearly.
Found the sentence about rwlock amusing: "... it has the additional feature of allowing infinite threads to read simultaneously, while only restricting write access to a singular thread."
Compared to the standard library, usage of both pthreads and windows threads are wordy, the latter being wordier. However windows threads do have fiber, fiber local storage, thread pool. Windows mutex can be used to synchronize multiple processes as well. Within a single process critical section is a cheaper version of mutex not requiring kernel space calls.
Threads are implemented in STL, not in core. The main objects are: thread, mutex, and condition variable. There are wrappers around mutex to help manage lock/unlock calls or deadlock-safe acquiring of multiple mutexes at once. Shared mutex for example works as an rwlock. STL condition variable is prone to spurious wake-up, better check cond_status or a boolean explicitly set by the notifying thread. A higher level wrapper pattern using future/promise eases asynchronous programming. The consumer uses "future" to wait and then to get result and the producer uses "promise" to set result. Promise/future pair can be used to communicate a value from one thread (sets value on promise) to another (waits to get value from future) almost like there is a channel between the pair. Shared future can be used to communicate value (from the associated promise) to multiple threads, almost like another way of condition variable, perhaps more generic since a value of choice, not only signal, can be passed. Packaged task simplifies management of promise/future pair in the sense that one does not need to explicitly create a promise and get the associated future and pass that to the child thread. Simpler even is std::async. The default launch policy of std::async is deferred which means be lazy, launch a thread only when get/wait is called on the associated future, one could go eager with async launch policy.
Found the sentence about rwlock amusing: "... it has the additional feature of allowing infinite threads to read simultaneously, while only restricting write access to a singular thread."
Compared to the standard library, usage of both pthreads and windows threads are wordy, the latter being wordier. However windows threads do have fiber, fiber local storage, thread pool. Windows mutex can be used to synchronize multiple processes as well. Within a single process critical section is a cheaper version of mutex not requiring kernel space calls.
Threads are implemented in STL, not in core. The main objects are: thread, mutex, and condition variable. There are wrappers around mutex to help manage lock/unlock calls or deadlock-safe acquiring of multiple mutexes at once. Shared mutex for example works as an rwlock. STL condition variable is prone to spurious wake-up, better check cond_status or a boolean explicitly set by the notifying thread. A higher level wrapper pattern using future/promise eases asynchronous programming. The consumer uses "future" to wait and then to get result and the producer uses "promise" to set result. Promise/future pair can be used to communicate a value from one thread (sets value on promise) to another (waits to get value from future) almost like there is a channel between the pair. Shared future can be used to communicate value (from the associated promise) to multiple threads, almost like another way of condition variable, perhaps more generic since a value of choice, not only signal, can be passed. Packaged task simplifies management of promise/future pair in the sense that one does not need to explicitly create a promise and get the associated future and pass that to the child thread. Simpler even is std::async. The default launch policy of std::async is deferred which means be lazy, launch a thread only when get/wait is called on the associated future, one could go eager with async launch policy.
April 14, 2019
Well structured and well explained information.
unfortunately some piece of code contains errors(like using undeclared variable). I would say that is a minor issue.
unfortunately some piece of code contains errors(like using undeclared variable). I would say that is a minor issue.
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