A modern C++ concurrency library providing tasks, executors, timers, and C++20 coroutines for writing highly concurrent applications.
concurrencpp is a modern C++ concurrency library that provides tasks, executors, timers, and C++20 coroutines to simplify writing highly concurrent applications. It solves the complexity of low-level thread management by offering higher-level abstractions that automatically scale and reduce common concurrency bugs.
C++ developers building high-performance, concurrent applications such as servers, parallel algorithms, or real-time systems who want to leverage modern C++ features without dealing with raw threading primitives.
Developers choose concurrencpp for its seamless integration with C++20 coroutines, comprehensive executor system, and focus on safety—reducing race conditions and deadlocks while providing a clean, task-based API that boosts productivity.
Modern concurrency for C++. Tasks, executors, timers and C++20 coroutines to rule them all
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Supports both eager and lazy coroutines with co_await, enabling non-blocking, synchronous-like code as shown in the parallel Fibonacci example, which simplifies asynchronous programming.
Provides various executor types like thread pool, background, and manual executors, allowing fine-grained control over task scheduling and execution contexts, as detailed in the executor API section.
Reduces race conditions and deadlocks by abstracting low-level threading primitives into high-level tasks with built-in synchronization, emphasizing safety and productivity as per the library philosophy.
Well-tested on various platforms and operating systems, ensuring reliability for production use, as highlighted in the README's claims of maturity and testing.
Requires C++20 standard for coroutine support, which limits adoption in environments with older compilers or legacy codebases that cannot upgrade.
Necessitates creating and managing a runtime object for executor lifecycle, adding initial complexity compared to simpler concurrency models like std::thread or std::async.
The abstraction layer for tasks and executors may introduce overhead compared to manually managed threads, potentially impacting latency-critical applications where raw control is preferred.
Lacks native task cancellation mechanisms; developers must implement custom logic using result promises or other workarounds, which can be cumbersome for dynamic task management.