cuQuantum SDK: A High-Performance Library for Accelerating Quantum Information Science
NVIDIA cuQuantum SDK is a high-performance library for quantum information science and beyond. Currently its primary target is quantum circuit simulations and it consists of two major components:
cuStateVec: a high-performance library for state vector computations
cuTensorNet: a high-performance library for tensor network computations
In addition to C APIs, cuQuantum also provides Python APIs via cuQuantum Python.
Documentation
Please refer to https://docs.nvidia.com/cuda/cuquantum/index.html for the cuQuantum documentation.
Installation
The cuQuantum wheel can be installed as follows:
pip install cuquantum-cuXX
where XX is the CUDA major version (currently CUDA 11 and 12 are supported). We encourage users to install package with the -cuXX suffix; the package cuquantum (without the -cuXX suffix) currently points to cuquantum-cu11 and is subject to change in the future.
Citing cuQuantum
Metadata
Release files for cuquantum-cu11 23.10.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cuquantum_cu11-23.10.0-py3-none-manylinux2014_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| cuquantum_cu11-23.10.0-py3-none-manylinux2014_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64 | Details |
Total release size: 14.0 kB
Release files / cuquantum_cu11-23.10.0-py3-none-manylinux2014_x86_64.whl
| Download URL | cuquantum_cu11-23.10.0-py3-none-manylinux2014_x86_64.whl |
|---|---|
| Size | 7.0 kB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
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Release files / cuquantum_cu11-23.10.0-py3-none-manylinux2014_aarch64.whl
| Download URL | cuquantum_cu11-23.10.0-py3-none-manylinux2014_aarch64.whl |
|---|---|
| Size | 7.0 kB |
| Tags | Linux glibc 2.17+ ARM64 Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
|