CUDA Core Compute Libraries (CCCL) unifies essential CUDA C++ libraries—Thrust, CUB, and libcudacxx—into a single, header-only repository. It targets CUDA C++ developers seeking to simplify the creation of safe, efficient, and high-performance GPU code, offering a streamlined development process and broader leverage of CUDA capabilities.

How It Works

CCCL integrates Thrust's high-level parallel algorithms, CUB's low-level CUDA-specific primitives, and libcudacxx's CUDA C++ Standard Library implementation. This unification provides developers with a cohesive set of building blocks, enhancing productivity and enabling performance portability across GPUs and CPUs via configurable backends. The approach leverages existing, well-regarded libraries into a single, managed entity.

Quick Start & Requirements

CCCL is header-only. Integration is straightforward:

• CUDA Toolkit: Headers are automatically included when compiling with nvcc.
• GitHub: Clone the repository and include headers via -I flags (e.g., nvcc -Icccl/thrust ... main.cu).
• Conda: Install via conda install cccl or conda install cuda-cccl from conda-forge.
• CMake: Standard cmake . && make install or cmake --preset install workflows are supported.

Requirements: CUDA Toolkit, compatible host compiler (e.g., GCC >= 7.x on Linux), C++17/C++20. GPU architectures supported by the CUDA Toolkit. Links: Documentation, Live Demo (Godbolt), GitHub Repository.

Highlighted Details

• Header-only distribution simplifies integration.
• Unified API across Thrust, CUB, and libcudacxx.
• Supports C++17 and C++20 standards.
• Backward compatible with current and preceding CUDA Toolkit major versions.

Maintenance & Community

The project is maintained by NVIDIA. A Discord server is available for community interaction, and a Contributor Guide outlines how to contribute to development.

Licensing & Compatibility

The specific license is not detailed in the provided README excerpt. CCCL is generally compatible with all operating systems and host compilers supported by the CUDA Toolkit. It maintains backward compatibility with CUDA Toolkit versions but is not forward compatible.

Limitations & Caveats

ABI stability is not guaranteed for thrust:: and cub:: namespaces. While cuda:: namespace ABI changes are versioned, users should recompile binaries if ABI breaks occur. Only the latest CCCL version is supported; fixes are not backported. New features may require newer CUDA Toolkit versions.