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https://github.com/DeveloperPaul123/thread-pool

A modern, fast, lightweight thread pool library based on C++20
https://github.com/DeveloperPaul123/thread-pool

c-plus-plus concurrency cplusplus cpp cpp20 cpp20-library fast header-only high-performance high-performance-computing modern-cpp performance thread thread-pool thread-pool-implementations threading threadpool threads

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A modern, fast, lightweight thread pool library based on C++20

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thread-pool

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A simple, *fast* and functional thread pool implementation using pure C++20.

## Features

* Built entirely with C++20
* Enqueue tasks with or without tracking results
* [High performance](#benchmarks)

## Integration

`dp::thread-pool` is a header only library. All the files needed are in `include/thread_pool`.

### vcpkg

`dp::thread-pool` is available on `vcpkg`

```powershell
vcpkg install dp-thread-pool
```

### CMake

`thread-pool` defines the CMake target `dp::thread-pool`.

You can then use `find_package()`:

```cmake
find_package(dp::thread-pool REQUIRED)
```

Alternatively, you can use something like [CPM](https://github.com/TheLartians/CPM) which is based on CMake's `Fetch_Content` module.

```cmake
CPMAddPackage(
NAME thread-pool
GITHUB_REPOSITORY DeveloperPaul123/thread-pool
GIT_TAG 0.6.0 # change this to latest commit or release tag
OPTIONS
"TP_BUILD_TESTS OFF"
"TP_BUILD_BENCHMARKS OFF"
"TP_BUILD_EXAMPLES OFF"
)
```

## Usage

Enqueue tasks without a returned result:

```cpp
// create a thread pool with a specified number of threads.
dp::thread_pool pool(4);

// add tasks, in this case without caring about results of individual tasks
pool.enqueue_detach([](int value) { /*...your task...*/ }, 34);
pool.enqueue_detach([](int value) { /*...your task...*/ }, 37);
pool.enqueue_detach([](int value) { /*...your task...*/ }, 38);
// and so on..
```

Enqueue tasks with a returned value:

```cpp
// create a thread pool with a specified number of threads.
dp::thread_pool pool(4);

auto result = pool.enqueue([](int value) -> int { /*...your task...*/ return value; }, 34);
// get the result, this will block the current thread until the task is complete
auto value = result.get();
```

Enqueue tasks and wait for them to complete:

```cpp
dp::thread_pool pool(4);

// add tasks, in this case without caring about results of individual tasks
pool.enqueue_detach([](int value) { /*...your task...*/ }, 34);
pool.enqueue_detach([](int value) { /*...your task...*/ }, 37);
pool.enqueue_detach([](int value) { /*...your task...*/ }, 38);
pool.enqueue_detach([](int value) { /*...your task...*/ }, 40);

// wait for all tasks to complete
pool.wait_for_tasks();
```

You can see other examples in the `/examples` folder.

## Benchmarks

Benchmarks were run using the [nanobench](https://github.com/martinus/nanobench) library. See the `./benchmark` folder for the benchmark code. The benchmarks are set up to compare matrix multiplication using the `dp::thread_pool` versus other thread pool libraries. These include:

* [ConorWilliams/Threadpool](https://github.com/ConorWilliams/Threadpool)
* [bshoshany/thread-pool](https://github.com/bshoshany/thread-pool) (C++17)
* [alugowski/task-thread-pool](https://github.com/alugowski/task-thread-pool) (C++11, no work stealing)

The benchmarks are set up so that each library is tested against `dp::thread_pool` using `std::function` as the baseline. Relative measurements (in %) are recorded to compare the performance of each library to the baseline.

### Machine Specs

* AMD Ryzen 7 5800X (16 X 3800 MHz CPUs)
* 32 GB RAM

### Results

#### Summary

In general, `dp::thread_pool` is faster than other thread pool libraries in most cases. This is especially the case when `std::move_only_function` is available. `fu2::unique_function` is a close second, and `std::function` is the sloweset when used in `dp::thread_pool`. In certain situations, `riften::ThreadPool` pulls ahead in performance. This is likely due to the fact that this library uses a lock-free queue. There is also a custom semaphore and it seems that there is a difference in how work stealing is handled as well. Interestingly, `task_thread_pool` seems to pull ahead with large numbers of smaller tasks.

#### Details

Below is a portion of the benchmark data from the MSVC results:

| relative | ms/op | op/s | err% | total | matrix multiplication 256x256
|---------:|--------------------:|--------------------:|--------:|----------:|:------------------------------
| 100.0% | 93.27 | 10.72 | 0.7% | 16.69 | `dp::thread_pool - std::function`
| 102.9% | 90.66 | 11.03 | 0.6% | 16.22 | `dp::thread_pool - std::move_only_function`
| 98.7% | 94.50 | 10.58 | 0.2% | 16.91 | `dp::thread_pool - fu2::unique_function`
| 93.5% | 99.73 | 10.03 | 0.4% | 17.86 | `BS::thread_pool`
| 102.2% | 91.29 | 10.95 | 0.6% | 16.39 | `task_thread_pool`
| 100.1% | 93.18 | 10.73 | 1.4% | 16.61 | `riften::Thiefpool`

If you wish to look at the full results, use the links below.

[MSVC Results](./benchmark/results/benchmark_results_msvc.md)

[Clang Results](./benchmark/results/benchmark_results_clang.md)

Some notes on the benchmark methodology:

* Matrix sizes are all square (MxM).
* Each multiplication is `(MxM) * (MxM)` where `*` refers to a matrix multiplication operation.
* Benchmarks were run on Windows, so system stability is something to consider (dynamic CPU frequency scaling, etc.).
* Relative

## Building

This project has been built with:

* Visual Studio 2022
* Clang `10.+` (via WSL on Windows)
* GCC `11.+` (vis WSL on Windows)
* CMake `3.19+`

To build, run:

```bash
cmake -S . -B build
cmake --build build
```

### Build Options

| Option | Description | Default |
|:--------------------|:--------------------------------------------------------------------|:-------:|
| `TP_BUILD_TESTS` | Turn on to build unit tests. Required for formatting build targets. | ON |
| `TP_BUILD_EXAMPLES` | Turn on to build examples | ON |

### Run clang-format

Use the following commands from the project's root directory to check and fix C++ and CMake source style.
This requires *clang-format*, *cmake-format* and *pyyaml* to be installed on the current system. To use this feature you must turn on `TP_BUILD_TESTS`.

```bash
# view changes
cmake --build build/test --target format

# apply changes
cmake --build build/test --target fix-format
```

See [Format.cmake](https://github.com/TheLartians/Format.cmake) for details.

### Build the documentation

The documentation is automatically built and [published](https://developerpaul123.github.io/thread-pool) whenever a [GitHub Release](https://help.github.com/en/github/administering-a-repository/managing-releases-in-a-repository) is created.
To manually build documentation, call the following command.

```bash
cmake -S documentation -B build/doc
cmake --build build/doc --target GenerateDocs
# view the docs
open build/doc/doxygen/html/index.html
```

To build the documentation locally, you will need Doxygen and Graphviz on your system.

## Contributing

Contributions are very welcome. Please see [contribution guidelines for more info](CONTRIBUTING.md).

## License

The project is licensed under the MIT license. See [LICENSE](LICENSE) for more details.

## Author

| [
@DeveloperPaul123](https://github.com/DeveloperPaul123) |
|:----:|