ranjani_dist_cuda-q
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: RanjaniSundaram
- License: other
- Language: C++
- Default Branch: master
- Size: 25.3 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Welcome to the CUDA-Q repository
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 cuda-quantum@nvidia.com.
Owner
- Login: RanjaniSundaram
- Kind: user
- Repositories: 1
- Profile: https://github.com/RanjaniSundaram
Citation (CITATION.cff)
cff-version: 1.2.0 title: 'CUDA-Q' message: 'If you use this software, please cite it as below.' authors: - name: "The CUDA-Q development team" license: Apache-2.0 license-url: "https://github.com/NVIDIA/cuda-quantum/blob/main/LICENSE" repository-code: "https://github.com/NVIDIA/cuda-quantum" type: software url: "https://github.com/NVIDIA/cuda-quantum" # doi:
GitHub Events
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Dependencies
- ubuntu latest build
- astpretty ~= 3.0
- cuquantum-cu11 ~= 24.03
- graphlib-backport >= 1.0
- numpy >= 1.24
- nvidia-cublas-cu11 == 11.11.3.6; platform_machine == "x86_64"
- nvidia-cuda-runtime-cu11 == 11.8.89; platform_machine == "x86_64"
- nvidia-cusolver-cu11 == 11.4.1.48; platform_machine == "x86_64"
- breathe ==4.34.0
- furo ==2022.6.21
- sphinx ==5.0.2
- sphinx-copybutton ==0.5.0
- sphinxcontrib-moderncmakedomain ==3.21.4
- sphinxcontrib-svg2pdfconverter ==1.2.0
- build * test
- numpy * test
- pytest * test
- pytest-timeout * test
- scipy * test
- numpy *
- asio *
- openssl *
- zlib *