Python wrapper for CUDA implementation of OSQP.
The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving problems in the form
minimize 0.5 x' P x + q' x
subject to l <= A x <= uwhere x in R^n is the optimization variable. The objective function is defined by a positive semidefinite matrix P in S^n_+ and vector q in R^n. The linear constraints are defined by matrix A in R^{m x n} and vectors l in R^m U {-inf}^m, u in R^m U {+inf}^m.
Installation -----------You need to install the following:
- NVIDIA CUDA Toolkit
- CMake
- GCC compiler (Linux) or Build Tools for Visual Studio 2017 (Windows)
Make sure the environment variable CUDA_PATH is set to the CUDA Toolkit install directory.
Then run the following commands in your terminal:
git clone --recurse-submodules https://github.com/oxfordcontrol/cuosqp
cd cuosqp
python setup.py installThe interface is documented here.
If you use cuosqp for research, please cite our accompanying paper:
@article{cuosqp,
author = {Schubiger, M. and Banjac, G. and Lygeros, J.},
title = {{GPU} acceleration of {ADMM} for large-scale quadratic programming},
journal = {Journal of Parallel and Distributed Computing},
year = {2020},
volume = {144},
pages = {55--67},
doi = {10.1016/j.jpdc.2020.05.021},
}