@article {1086,
	title = {Structure-aware Linear Solver for Realtime Convex Optimization for Embedded Systems},
	journal = {IEEE Embedded Systems Letters},
	volume = {9},
	year = {2017},
	month = {2017-05},
	pages = {61{\textendash}64},
	abstract = {With the increasing sophistication in the use of optimization algorithms such as deep learning on embedded systems, the convex optimization solvers on embedded systems have found widespread use. This letter presents a novel linear solver technique to reduce the run-time of convex optimization solver by using the property that some parameters are fixed during the solution iterations of a solve instance. Our experimental results show that the run-time can be reduced by two orders of magnitude.},
	keywords = {Karush Kuhn Tucker (KKT), Realtime embedded convex optimization solver},
	doi = {10.1109/LES.2017.2700401},
	url = {http://ieeexplore.ieee.org/document/7917357/},
	author = {Ichitaro Yamazaki and Saeid Nooshabadi and Stanimire Tomov and Jack Dongarra}
}
