# QFactor implementation on GPUs using JAX
`bqskit-qfactor-jax` is a Python package that implements circuit instantiation with [QFactor](https://arxiv.org/abs/2306.08152) on GPUs to accelerate [BQSKit](https://github.com/bqskit/bqskit). It uses [JAX](https://jax.readthedocs.io/en/latest/index.html) as an abstraction layer of the GPUs, seamlessly utilizing JIT compilation and GPU parallelism.
## Installation
`bqskit-qfactor-jax` is available for Python 3.8+ on Linux.
First, install JAX with GPU support, you may refer to JAX's [installation instructions](https://github.com/google/jax#installation).
Next, install this package with pip:
```sh
pip install bqskit-qfactor-jax
```
# Running bqskit-qfactor-jax
Please set the environment variable XLA_PYTHON_CLIENT_PREALLOCATE=False when using this package.
Please take a look at the [examples](https://github.com/BQSKit/bqskit-qfactor-jax/tree/main/examples) to see some basic usage.
When using several workers on the same GPU, we recommend using [Nvidia's MPS](https://docs.nvidia.com/deploy/mps/index.html). You may initiate it using the command line
```sh
nvidia-cuda-mps-control -d
```
You can disable it by running this command line:
```sh
echo quit | nvidia-cuda-mps-control
```
# References
Kukliansky, Alon, et al. "QFactor:A Domain-Specific Optimizer for Quantum Circuit Instantiation." arXiv preprint [arXiv:2306.08152](https://arxiv.org/abs/2306.08152) (2023).
## License
The software in this repository is licensed under a **BSD free software
license** and can be used in source or binary form for any purpose as long
as the simple licensing requirements are followed. See the
**[LICENSE](https://github.com/BQSKit/bqskit-qfactor-jax/blob/main/LICENSE)** file
for more information.
## Copyright
Quantum Fast Circuit Optimizer (QFactor) JAX implementation Copyright (c) 2023,
U.S. Federal Government and the Government of Israel. All rights reserved.
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