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C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

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Welcome to the CUDA-Q repository


DOI

The CUDA-Q Platform for hybrid quantum-classical computers enables integration and programming of quantum processing units (QPUs), GPUs, and CPUs in one system. This repository contains the source code for all C++ and Python tools provided by the CUDA-Q toolkit, including the nvq++ compiler, the CUDA-Q runtime, as well as a selection of integrated CPU and GPU backends for rapid application development and testing.

Getting Started

To learn more about how to work with CUDA-Q, please take a look at the CUDA-Q Documentation. The page also contains installation instructions for officially released packages.

If you would like to install the latest iteration under development in this repository and/or add your own modifications, take a look at the latest packages deployed on the GitHub Container Registry. For more information about building CUDA-Q from source, see these instructions.

Contributing

There are many ways in which you can get involved with CUDA-Q. If you are interested in developing quantum applications with CUDA-Q, this repository is a great place to get started! For more information about contributing to the CUDA-Q platform, please take a look at Contributing.md.

License

The code in this repository is licensed under Apache License 2.0.

Contributing a pull request to this repository requires accepting the Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. A CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately. Simply follow the instructions provided by the bot. You will only need to do this once.

Feedback

Please let us know your feedback and ideas for the CUDA-Q platform in the Discussions tab of this repository, or file an issue. To report security concerns or Code of Conduct violations, please reach out to [email protected].

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C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

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  • C++ 69.0%
  • Python 17.5%
  • C 7.3%
  • CMake 2.4%
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