libcu++, the NVIDIA C++ Standard Library, provides a C++ Standard Library for your entire system which can be used in and between CPU and GPU codes.
Overview
libcu++, NVIDIA's open-source C++ Standard Library, facilitates seamless integration between CPU and GPU code. The latest version, 1.4.0, introduces significant enhancements, including support for various C++ features and improved documentation.
What You'll Learn
1
How to utilize libcu++ for GPU-enabled C++ programming
2
Why using an open-source C++ Standard Library can enhance cross-platform development
3
When to apply C++20 and C++17 features in libcu++
Key Questions Answered
What enhancements does libcu++ version 1.4.0 offer?
libcu++ version 1.4.0 introduces several enhancements, including support for <cuda/std/complex>, NVCC + MSVC support for <cuda/std/tuple>, and backports of C++20 <cuda/std/chrono> and C++17 <cuda/std/type_traits> features to C++14. Additionally, it features improved documentation and examples.
Where can I find libcu++ and its documentation?
libcu++ is available on GitHub and included in the NVIDIA HPC SDK and the CUDA Toolkit. Documentation and examples can also be found on the official NVIDIA website.
Technologies & Tools
Library
Libcu++
Provides a C++ Standard Library for CPU and GPU code integration.
Toolkit
Cuda Toolkit
Includes libcu++ and supports GPU programming.
Toolkit
Nvidia Hpc SDK
Includes libcu++ for high-performance computing applications.
Key Actionable Insights
1Explore the new features in libcu++ 1.4.0 to enhance your GPU programming capabilities.Utilizing the latest features can improve performance and code efficiency, making it essential for developers working with NVIDIA technologies.
2Review the revamped documentation and examples provided with libcu++ to better understand its capabilities.Comprehensive documentation can significantly reduce the learning curve and help developers implement GPU-enabled applications more effectively.