Feedstock license: BSD-3-Clause
Home: https://developer.nvidia.com/cuquantum-sdk
Package license: LicenseRef-cuQuantum-Software-License-Agreement
Summary: cuQuantum SDK: A High-Performance Library for Accelerating Quantum Information Science
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/index.html
NVIDIA cuQuantum is an SDK of optimized libraries and tools for accelerating quantum computing workflows. Using NVIDIA GPU Tensor Core GPUs, developers can use cuQuantum to speed up quantum circuit simulations based on state vector and tensor network methods by orders of magnitude. Two major components of the SDK are
- cuStateVec: a high-performance library for state vector computations
- cuTensorNet: a high-performance library for tensor network computations
The packages cuquantum, custatevec, and cutensornet are governed by the NVIDIA cuQuantum Software License Agreement (EULA). By downloading and using the packages, you accept the terms and conditions of the NVIDIA cuQuantum EULA - https://docs.nvidia.com/cuda/cuquantum/license.html
Home: https://developer.nvidia.com/cuquantum-sdk
Package license: LicenseRef-cuQuantum-Software-License-Agreement
Summary: cuStateVec: A High-Performance Library for State Vector Quantum Simulators
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/custatevec/
NVIDIA cuStateVec is a high-performance GPU library dedicated to operations with state vectors for expressing quantum algorithms. cuStateVec is a component of the NVIDIA cuQuantum SDK.
The packages cuquantum, custatevec, and cutensornet are governed by the NVIDIA cuQuantum Software License Agreement (EULA). By downloading and using the packages, you accept the terms and conditions of the NVIDIA cuQuantum EULA - https://docs.nvidia.com/cuda/cuquantum/license.html
Home: https://developer.nvidia.com/cuquantum-sdk
Package license: LicenseRef-cuQuantum-Software-License-Agreement
Summary: cuTensorNet: A High-Performance Library for Tensor Network Computations
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/cutensornet/
NVIDIA cuTensorNet is a high-performance GPU library for tensor network computations, a component of the NVIDIA cuQuantum SDK.
The packages cuquantum, custatevec, and cutensornet are governed by the NVIDIA cuQuantum Software License Agreement (EULA). By downloading and using the packages, you accept the terms and conditions of the NVIDIA cuQuantum EULA - https://docs.nvidia.com/cuda/cuquantum/license.html
Home: https://developer.nvidia.com/cuquantum-sdk
Package license: BSD-3-Clause
Summary: cuQuantum Python: Python APIs for NVIDIA cuQuantum SDK
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/python/
NVIDIA cuQuantum Python provides Python bindings and high-level object-oriented models for accessing the full functionalities of NVIDIA cuQuantum SDK from Python.
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Installing cuquantum-sdk from the conda-forge channel can be achieved by adding conda-forge to your channels with:
conda config --add channels conda-forge
conda config --set channel_priority strict
Once the conda-forge channel has been enabled, cuquantum, cuquantum-python, custatevec, cutensornet can be installed with conda:
conda install cuquantum cuquantum-python custatevec cutensornet
or with mamba:
mamba install cuquantum cuquantum-python custatevec cutensornet
It is possible to list all of the versions of cuquantum available on your platform with conda:
conda search cuquantum --channel conda-forge
or with mamba:
mamba search cuquantum --channel conda-forge
Alternatively, mamba repoquery may provide more information:
# Search all versions available on your platform:
mamba repoquery search cuquantum --channel conda-forge
# List packages depending on `cuquantum`:
mamba repoquery whoneeds cuquantum --channel conda-forge
# List dependencies of `cuquantum`:
mamba repoquery depends cuquantum --channel conda-forge
conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.
A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.
To manage the continuous integration and simplify feedstock maintenance
conda-smithy has been developed.
Using the conda-forge.yml within this repository, it is possible to re-render all of
this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.
For more information please check the conda-forge documentation.
feedstock - the conda recipe (raw material), supporting scripts and CI configuration.
conda-smithy - the tool which helps orchestrate the feedstock.
Its primary use is in the construction of the CI .yml files
and simplify the management of many feedstocks.
conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)
If you would like to improve the cuquantum-sdk recipe or build a new
package version, please fork this repository and submit a PR. Upon submission,
your changes will be run on the appropriate platforms to give the reviewer an
opportunity to confirm that the changes result in a successful build. Once
merged, the recipe will be re-built and uploaded automatically to the
conda-forge channel, whereupon the built conda packages will be available for
everybody to install and use from the conda-forge channel.
Note that all branches in the conda-forge/cuquantum-sdk-feedstock are
immediately built and any created packages are uploaded, so PRs should be based
on branches in forks and branches in the main repository should only be used to
build distinct package versions.
In order to produce a uniquely identifiable distribution:
- If the version of a package is not being increased, please add or increase
the
build/number. - If the version of a package is being increased, please remember to return
the
build/numberback to 0.