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-cuXXwhere 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
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5 maintainers
Metadata
5 maintainers
Release files for cuquantum-cu12 24.3.0.post1
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_cu12-24.3.0.post1-py3-none-manylinux2014_x86_64.whl | Python 3 | none | Linux glibc 2.17+ x86-64 | Details |
| cuquantum_cu12-24.3.0.post1-py3-none-manylinux2014_aarch64.whl | Python 3 | none | Linux glibc 2.17+ ARM64 | Details |
Total release size: 15.1 kB
Release files / cuquantum_cu12-24.3.0.post1-py3-none-manylinux2014_x86_64.whl
| Download URL | cuquantum_cu12-24.3.0.post1-py3-none-manylinux2014_x86_64.whl |
|---|---|
| Size | 7.5 kB |
| Tags | Linux glibc 2.17+ x86-64 Python 3 |
|
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No |
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twine/5.0.0 CPython/3.10.13
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Release files / cuquantum_cu12-24.3.0.post1-py3-none-manylinux2014_aarch64.whl
| Download URL | cuquantum_cu12-24.3.0.post1-py3-none-manylinux2014_aarch64.whl |
|---|---|
| Size | 7.5 kB |
| Tags | Linux glibc 2.17+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.13
|
