pcg-next: Modern PCG Random Number Generation

pcg-next is the modernized, forward-looking branch of the PCG C++ library, hosted by the Total-Random organization.

Why pcg-next?

This project is a fork of Total-Random/pcg-cpp.

The main pcg-cpp branch is dedicated to maintaining strict compatibility with the original repository by Melissa O'Neill (imneme/pcg-cpp). This constraint prevents us from making large-scale improvements to the directory structure or naming conventions.

pcg-next was created to break those chains. It is where we implement:

• Namespaced Headers: Cleanly organized under pcg-next/ to avoid naming collisions.
• Simplified Naming: Removal of redundant prefixes (e.g., pcg_random.hpp ⮕ random.hpp).
• Modern Standards: Faster adoption of modern C++ features and build system improvements.

Key Improvements Integrated:

• Windows ARM64 Support: Integrated native support for MSVC on ARM64 architectures (Surface Pro, Apple Silicon via VM, etc.) using __umulh intrinsics.
• Improved MSVC Compatibility: Fixed ambiguous operator errors (C2678) in set_stream and operator>>.
• Optimized unxorshift: Integrated an optimized version of the inverse xorshift operation for better performance.
• Consistent Typing: Unified integer type handling across different platforms to avoid compiler warnings and errors.

Detailed information about integrated community fixes and contributors can be found in CREDITS.md.

About PCG

PCG is a family of simple fast space-efficient statistically good algorithms for random number generation. Unlike many common generators, it's not just "good enough" — it passes the most stringent statistical tests while being faster and smaller than most alternatives.

For full details on the theory and performance, visit the PCG-Random website.

Usage

This is a header-only library. To use it, simply add the include directory to your project's include path and:

#include "pcg-next/random.hpp"

// Standard 32-bit PCG generator
pcg32 rng;

// Seed it (optional, uses a fixed seed by default)
rng.seed(pcg_extras::seed_seq_from<std::random_device>{});

// Generate a number
uint32_t x = rng();

• Use pcg32 for 32-bit output.
• Use pcg64 for 64-bit output (now highly optimized for 64-bit systems and ARM64).

Building Demos & Tests

While the library itself is header-only, we provide tests and samples:

Unix-style (Linux, macOS, MinGW)

make
make test

Modern CMake (All Platforms)

This is the recommended way to build and integrate the library:

cmake -S . -B build
cmake --build build
cd build
ctest .

Windows (MSVC)

This fork is specifically patched to support building with Visual Studio 2019/2022. You can use the CMake instructions above to generate a Visual Studio solution, or simply include the headers directly in your project.

Directory Structure

• include/ — The core library (header-only).
• sample/ — Readable examples showing how to use the high-level API.
• test-high/ — Functional and statistical tests.
• cmake/ — Build system configuration and modules.

Maintenance & Contributions

We welcome bug fixes and compatibility patches. If you find an issue, especially on newer hardware or compiler versions, please open an issue or pull request in the Total-Random/pcg-cpp repository.

License

This code is distributed under the Apache License, Version 2.0 or the MIT License, at your option. See the header of each file for details.

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Maintained with ❤️ by the Total-Random Team.