
@conference {MilZha15A,
	title = {A Software Configurable Coprocessor-Based State-Space Controller},
	booktitle = {Proceedings of the International Symposium on Field-Programmable Logic and Applications (FPL)},
	year = {2015},
	month = {September},
	abstract = {We present a software configurable coprocessor-based state-space controller that can control physical processes representable by a linear state-space model.  Our proposed architecture has distinct advantages over purely software or purely hardware approaches. It differs from other hardware controllers in that it is not hardwired to control one or a small range of plant types (e.g. only electric motors). Via software, an embedded systems engineer can easily reconfigure the controller to suit a wide range of controls applications that can be represented as a state-space linear model. Additionally, we introduce a novel design methodology to help bridge the gap between controls and embedded system engineering.  Control of the well-understood inverted pendulum on a cart is used as an illustrative example of how the proposed hardware accelerator architecture supports our envisioned design methodology for helping bridge the gap between controls and embedded software engineering. 
},
	author = {Aaron Mills and Pei Zhang and Sudhanshu Vyas and Joseph Zambreno and Phillip Jones}
}
@conference {KumVya13A,
	title = {Scheduling Challenges in Mixed Critical Real-time Heterogeneous Computing Platforms},
	booktitle = {Proceedings of Dynamic Data Driven Application Systems (DDDAS)},
	year = {2013},
	month = {June},
	abstract = {In Dynamic Data-Driven Application Systems (DDDAS), applications must dynamically adapt their behavior in response to objectives and conditions that change while deployed. Often these applications may be safety critical or tightly resource constrained, with a need for graceful degradation when introduced to unexpected conditions. This paper begins by motivating and providing a vision for a dynamically adaptable mixed critical computing platform to support DDDAS applications. We then specifically focus on the need for advancements in task models and scheduling algorithms to manage the resources of such a platform. We discuss the short comings of existing task models for capturing important attributes of our envisioned computing platform, and identify challenges that must be addressed when developing scheduling algorithms that act upon our proposed extended task model.},
	author = {Chetan Kumar and Sudhanshu Vyas and Ron Cytron and Christopher Gill and Joseph Zambreno and Phillip Jones}
}
