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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.
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.
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
cuda-quantum@nvidia.com.
About
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows