# Quantuloop Sparse simulator for the Ket Quantum Programming Language
This package provides the multi-GPU accelerated quantum simulator Quantuloop Sparse as a quantum execution target for the quantum programming language Ket. For more information on Ket, access <https://quantumket.org>.
The use of this simulator is exclusively for Quantuloop's customers and partners. Contact your institution to get your access token or visit <https://quantuloop.com.br>.
## Compatibility
* CUDA 11.2 or newer with compatible NVIDIA driver
* NVIDIA GPU with CUDA architecture >= 3.5
* Linux X86_64 with glibc >= 2.17 (compatible with most Linux distributions released after 2014)
* Ubuntu 18.04 or newer.
* Red Hat Enterprise Linux 7 or newer.
* Python 3.7 or newer
* Ket 0.5.x
## Usage
Importing the `quantuloop.sparse` module sets Quantuloop Sparse as the quantum target execution. Although, you can use the `quantuloop.sparse.use_sparse` function for this proposal. Before the quantum execution, you must set your access token with `quantuloop.sparse.set_token`. See the example below.
```py
from ket import *
from quantuloop import sparse
sparse.use_sparse()
sparse.set_token('YOUR_ACCESS_TOKEN')
sparse.set_precision(2) # Optional, default 1
sparse.set_gpu_count(4) # Optional, default use all GPUs
```
---
By installing or using this package, you agree to the Quantuloop Quantum Simulator Suite EULA.
All rights reserved (C) 2023 Quantuloop
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"description": "# Quantuloop Sparse simulator for the Ket Quantum Programming Language\n\nThis package provides the multi-GPU accelerated quantum simulator Quantuloop Sparse as a quantum execution target for the quantum programming language Ket. For more information on Ket, access <https://quantumket.org>.\n\nThe use of this simulator is exclusively for Quantuloop's customers and partners. Contact your institution to get your access token or visit <https://quantuloop.com.br>.\n\n## Compatibility\n\n* CUDA 11.2 or newer with compatible NVIDIA driver\n* NVIDIA GPU with CUDA architecture >= 3.5\n* Linux X86_64 with glibc >= 2.17 (compatible with most Linux distributions released after 2014)\n * Ubuntu 18.04 or newer.\n * Red Hat Enterprise Linux 7 or newer.\n* Python 3.7 or newer\n* Ket 0.5.x\n\n## Usage\n\nImporting the `quantuloop.sparse` module sets Quantuloop Sparse as the quantum target execution. Although, you can use the `quantuloop.sparse.use_sparse` function for this proposal. Before the quantum execution, you must set your access token with `quantuloop.sparse.set_token`. See the example below.\n\n```py\nfrom ket import *\nfrom quantuloop import sparse\nsparse.use_sparse()\nsparse.set_token('YOUR_ACCESS_TOKEN')\nsparse.set_precision(2) # Optional, default 1\nsparse.set_gpu_count(4) # Optional, default use all GPUs\n```\n\n---\n\nBy installing or using this package, you agree to the Quantuloop Quantum Simulator Suite EULA.\n\nAll rights reserved (C) 2023 Quantuloop\n",
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