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 Computing Simulations
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/index.html
NVIDIA cuQuantum SDK is a set of high-performance libraries and tools for accelerating quantum computing simulations at both the circuit and device level by orders of magnitude. It consists of five major components:
- cuDensityMat: a high-performance library for quantum dynamics equation solvers
- cuStabilizer: a high-performance library for stabilizer state quantum simulators
- cuPauliProp: a high-performance library for Pauli path propagation quantum simulators
- cuStateVec: a high-performance library for state vector quantum simulators
- cuTensorNet: a high-performance library for tensor network computations
In addition to C APIs, cuQuantum also provides Python APIs via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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: cuDensityMat: A High-Performance Library for composing analog quantum dynamics equation solvers
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/cudensitymat/
NVIDIA cuDensityMat is a high-performance library for composing analog quantum dynamics equation solvers. cuDensityMat is a component of the NVIDIA cuQuantum SDK. In addition to C APIs, cuDensityMat can also be accessed in Python via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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: cuPauliProp: A high-performance library providing primitives for algorithms based on Pauli propagation
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/cupauliprop/
NVIDIA cuPauliProp is a high-performance library providing primitives for algorithms based on Pauli propagation. cuPauliprop is a component of the NVIDIA cuQuantum SDK. In addition to C APIs, cuPauliProp can also be accessed in Python via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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: A High-Performance Library for Accelerating Quantum Computing Simulations in Python
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.
Home: https://developer.nvidia.com/cuquantum-sdk
Package license: LicenseRef-cuQuantum-Software-License-Agreement
Summary: cuStabilizer: A high-performance library for GPU-accelerated simulation of noisy Clifford quantum circuits
Development: https://github.com/NVIDIA/cuQuantum
Documentation: https://docs.nvidia.com/cuda/cuquantum/latest/custabilizer/
NVIDIA cuStabilizer is a high-performance library for GPU-accelerated simulation of noisy Clifford quantum circuits. cuStabilizer is a component of the NVIDIA cuQuantum SDK. In addition to C APIs, cuStabilizer can also be accessed in Python via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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 library dedicated to operations for building state vector quantum simulators. cuStateVec is a component of the NVIDIA cuQuantum SDK. In addition to C APIs, cuStateVec can also be accessed in Python via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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 library for tensor network computations. cuTensorNet is a component of the NVIDIA cuQuantum SDK. In addition to C APIs, cuTensorNet can also be accessed in Python via cuQuantum Python.
The packages cuquantum, cudensitymat, cupauliprop, custabilizer, 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
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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, cudensitymat, cupauliprop, cuquantum, cuquantum-python, custabilizer, custatevec, cutensornet can be installed with conda:
conda install cudensitymat cupauliprop cuquantum cuquantum-python custabilizer custatevec cutensornet
or with mamba:
mamba install cudensitymat cupauliprop cuquantum cuquantum-python custabilizer custatevec cutensornet
It is possible to list all of the versions of cudensitymat available on your platform with conda:
conda search cudensitymat --channel conda-forge
or with mamba:
mamba search cudensitymat --channel conda-forge
Alternatively, mamba repoquery may provide more information:
# Search all versions available on your platform:
mamba repoquery search cudensitymat --channel conda-forge
# List packages depending on `cudensitymat`:
mamba repoquery whoneeds cudensitymat --channel conda-forge
# List dependencies of `cudensitymat`:
mamba repoquery depends cudensitymat --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.
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