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Building a Thread Pool with C++ and STL

Thread Pool Implementation in Plain C++ Using STL: A Comprehensive Guide for Beginners and Experienced Developers

oğuzhan katlı
6 min readOct 6, 2023

Thread pools are a fundamental concept in concurrent programming, providing a way to efficiently manage and execute a large number of tasks concurrently. Thread pools are a group of worker threads that can be used to execute tasks concurrently. Instead of creating a new thread for each task, a thread pool reuses existing threads, which can significantly improve performance and resource utilization.
Boost’s asio::thread_pool is a powerful tool in the Boost library that makes asynchronous I/O and concurrency easier. Inspired by Boost, this article carefully shows how to create a thread pool using only the STL and C++. This article also includes code breakdowns and sequence diagrams to help readers understand the implementation better.
The complete example can be found here or at the end of the article.

Boost Library

The Boost libraries are a collection of open-source C++ libraries that provide a wide range of functionality, including networking, concurrency, filesystem, regular expressions, and testing. Boost aims to provide portable, efficient, and reusable code for C++ developers. The Boost libraries are a valuable source of new features and functionality for the C++ language, and many Boost components have been adopted into the C++ Standard Library over the years.

Boost Asio Library

Boost Asio is a part of the Boost library that provides support for asynchronous I/O and concurrency. It’s commonly used for building network and communication applications. Asynchronous I/O allows the program to perform other tasks while waiting for I/O operations to complete, improving efficiency and responsiveness.

boost::asio::thread_pool

The Asio library in Boost includes a thread pool implementation starting with 1.66 version. boost::asio::thread_pool is a component within boost::asio that provides a simple way to manage a pool of threads.
Here’s a basic overview of using boost::asio::thread_pool:

#include <iostream>
#include <boost/asio/thread_pool.hpp>

int main() {
    boost::asio::thread_pool pool;

    for (int i = 0; i < 5; ++i) {
        boost::asio::post(pool, [i]() {
            std::cout << "Task " << i 
                << " executed by thread " << std::this_thread::get_id() << std::endl;
        });
    }

    std::future<int> r1 = boost::asio::post(pool, asio::use_future([]() { return 2; }));
    std::cout << "Result = " << r1.get() << '\n';

    // Optional: Wait for all tasks to complete
    pool.join();

    return 0;
}

Rewrite It with STL

When I saw the new thread_pool usage and the new definition in the Asio library, I was impressed. To understand how they were able to get return values from asynchronous operations using a single wrapper function and to improve my skills, I decided to rewrite the thread pool implementation in plain C++ using only the STL. I set a requirement for myself to replicate the boost::asio::thread_pool implementation as closely as possible, including the function calls and wrapper. When I finished my implementation, it looked like this:

class thread_pool
{
private:
  std::atomic_bool is_active {true};
  std::vector<std::thread> pool;
  std::condition_variable cv;
  std::mutex guard;
  std::deque<std::packaged_task<void()>> pending_jobs;
public:
  explicit thread_pool(int num_threads = 1) 
  {
    for (int i = 0; i < num_threads; i++) {
      pool.emplace_back(&thread_pool::run, this);
    }
  }
  ~thread_pool() {
    is_active = false;
    cv.notify_all();
    for (auto& th : pool) {
      th.join();
    }
  }

  void post(std::packaged_task<void()> job) {
    std::unique_lock lock(guard);
    pending_jobs.emplace_back(std::move(job));
    cv.notify_one();
  }
private:
  void run() noexcept 
  {
    while (is_active)
    {
      thread_local std::packaged_task<void()> job;
      {
        std::unique_lock lock(guard);
        cv.wait(lock, [&]{ return !pending_jobs.empty() || !is_active; });
        if (!is_active) break;
        job.swap(pending_jobs.front());
        pending_jobs.pop_front();
      }
      job();
    }
  }
};

Let’s break down the key components of the implementation:

  • thread_pool Class: This class encapsulates the entire thread pool.
    It maintains a set of threads, a condition variable (cv), and a mutex ( guard) to synchronize access to the task queue.
  • post Method: Enqueues a new task into the task queue and notifies a waiting thread.
  • run Method: The actual function executed by each worker thread. It continuously waits for tasks in the queue and executes them. In this function, thread_pool doesn’t know and does not care whether the executing function has return value or not. This will be handled by the global post function by using use_future wrapper function.

Note: where the line thread_local std::packaged_task<void()> job; I used thread_local to make sure that the ownership of the executing task is moved to the thread where it will be called.

Let’s write the global post and use_future functions to complete the thread pool implementation:

template <class Executor, class Fn>
void post(Executor& exec, Fn&& func)
{
  using return_type = decltype(func());
  static_assert(std::is_void_v<return_type>, "posting functions with return types must be used with \"use_future\" tag.");
  std::packaged_task<void()> task(std::forward<Fn>(func));
  exec.post(std::move(task));
}

struct use_future_tag {};
template <class Fn>
constexpr auto use_future(Fn&& func) {
  return std::make_tuple(use_future_tag{}, std::forward<Fn>(func));
}

template <class Executor, class Fn>
[[nodiscard]] decltype(auto) 
post(Executor& exec, std::tuple<use_future_tag, Fn>&& tpl)
{
  using return_type = std::invoke_result_t<Fn>;
  auto&& [_, func] = tpl;
  if constexpr (std::is_void_v<return_type>) 
  {
    std::packaged_task<void()> tsk(std::move(func));
    auto ret_future = tsk.get_future();
    exec.post(std::move(tsk));
    return ret_future;
  }
  else
  {
    struct forwarder_t {
      forwarder_t(Fn&& fn) : tsk(std::forward<Fn>(fn)) {}
      void operator()(std::shared_ptr<std::promise<return_type>> promise) noexcept
      {
        promise->set_value(tsk());
      }
    private:
      std::decay_t<Fn> tsk;
    } forwarder(std::forward<Fn>(func));

    auto promise = std::make_shared<std::promise<return_type>>();
    auto ret_future = promise->get_future();
    std::packaged_task<void()> tsk([promise = std::move(promise), forwarder = std::move(forwarder)] () mutable {
      forwarder(promise);
    });
    exec.post(std::move(tsk));
    return ret_future;
  }
}
  • post Function: this is the plain function which only creates a packaged_task from the given lambda or function pointer and puts into queue of the provided Executor class, which is our thread_pool in this instance.
  • use_future Function: Instead of Boost implementation (which they have created an allocator aware wrapper class that holds the callable) what I did here is I simply moved the callable object into a tuple with use_future_tag struct. Therefore I can create an overload version of post function returns a std::future<> object with the return type of the callable object.

All problems in computer science can be solved by another level of indirection. Butler Lampson, 1972

  • Second post Function: As the thread_pool class only accepts std::packaged_task<void()> type of callable into its queue, I had to create a higher order function, a local callable class forwarder_t which makes the actual function call, stores the return value into a promise object and returns void. When the thread_pool run the task which has return value, the following sequence will be executed:

Complete Example

I learned a lot by studying how thread pools work, exploring the Boost boost::asio::thread_pool library, and writing my own thread pool implementation in plain C++. I think this experience has helped me to understand concurrent programming better, especially how thread pools work.
I hope this article has been helpful to you, whether you are using Boost’s thread pool or are looking for a simpler, dependency-free solution.
Happy coding.

Complete example can be found Compiler Explorer

#include <iostream>
#include <memory>
#include <thread>
#include <mutex>
#include <future>
#include <condition_variable>
#include <functional>
#include <vector>
#include <deque>
#include <type_traits>

class thread_pool
{
private:
  std::atomic_bool is_active {true};
  std::vector<std::thread> pool;
  std::condition_variable cv;
  std::mutex guard;
  std::deque<std::packaged_task<void()>> pending_jobs;
public:
  explicit thread_pool(int num_threads = 1) 
  {
    for (int i = 0; i < num_threads; i++) {
      pool.emplace_back(&thread_pool::run, this);
    }
  }
  ~thread_pool() {
    is_active = false;
    cv.notify_all();
    for (auto& th : pool) {
      th.join();
    }
  }

  void post(std::packaged_task<void()> job) {
    std::unique_lock lock(guard);
    pending_jobs.emplace_back(std::move(job));
    cv.notify_one();
  }
private:
  void run() noexcept 
  {
    while (is_active)
    {
      thread_local std::packaged_task<void()> job;
      {
        std::unique_lock lock(guard);
        cv.wait(lock, [&]{ return !pending_jobs.empty() || !is_active; });
        if (!is_active) break;
        job.swap(pending_jobs.front());
        pending_jobs.pop_front();
      }
      job();
    }
  }
};

struct use_future_tag {};

template <class Fn>
constexpr auto use_future(Fn&& func) {
  return std::make_tuple(use_future_tag {}, std::forward<Fn>(func));
}

template <class Executor, class Fn>
void post(Executor& exec, Fn&& func)
{
  using return_type = decltype(func());
  static_assert(std::is_void_v<return_type>, "posting functions with return types must be used with \"use_future\" tag.");
  std::packaged_task<void()> task(std::forward<Fn>(func));
  exec.post(std::move(task));
}

template <class Executor, class Fn>
[[nodiscard]] decltype(auto) 
post(Executor& exec, std::tuple<use_future_tag, Fn>&& tpl)
{
  using return_type = std::invoke_result_t<Fn>;
  auto&& [_, func] = tpl;
  if constexpr (std::is_void_v<return_type>) 
  {
    std::packaged_task<void()> tsk(std::move(func));
    auto ret_future = tsk.get_future();
    exec.post(std::move(tsk));
    return ret_future;
  }
  else
  {
    struct forwarder_t {
      forwarder_t(Fn&& fn) : tsk(std::forward<Fn>(fn)) {}
      void operator()(std::shared_ptr<std::promise<return_type>> promise) noexcept
      {
        promise->set_value(tsk());
      }
    private:
      std::decay_t<Fn> tsk;
    } forwarder(std::forward<Fn>(func));

    auto promise = std::make_shared<std::promise<return_type>>();
    auto ret_future = promise->get_future();
    std::packaged_task<void()> tsk([promise = std::move(promise), forwarder = std::move(forwarder)] () mutable {
      forwarder(promise);
    });
    exec.post(std::move(tsk));
    return ret_future;
  }
} 

using namespace std::chrono_literals;
int main()
{
    thread_pool pool {2};
    auto waiter = 
        post(pool, use_future([] 
        {
            std::this_thread::sleep_for(1s);
            return 2;
        }));

    auto test_lmbda = [] {
        thread_local int count = 1;
        std::cout 
        << "working thread: " << std::this_thread::get_id()
        << "\tcount: " << count++ << std::endl;
        std::this_thread::sleep_for(50ms);
    };
    for (size_t i = 0; i < 10; i++)
    {
        post(pool, test_lmbda);
    }
    return waiter.get();
}

Originally published at https://nixiz.github.io on October 6, 2023.

Cplusplus
Thread Pool
Concurrency
Boost Libraries
Modern Cpp

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oğuzhan katlı

Written by oğuzhan katlı

158 Followers

https://github.com/nixiz

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