@article {Sandoval:2017:TTS:3092956.3047498,
	title = {Task Transition Scheduling for Data-Adaptable Systems},
	journal = {ACM Transactions on Embedded Computing Systems (TECS)},
	volume = {16},
	year = {2017},
	pages = {105:1{\textendash}105:28},
	abstract = {<p>Data-adaptable embedded systems operate on a variety of data streams, which requires a large degree of configurability and adaptability to support runtime changes in data stream inputs. Data-adaptable reconfigurable embedded systems, when decomposed into a series of tasks, enable a flexible runtime implementation in which a system can transition the execution of certain tasks between hardware and software while simultaneously continuing to process data during the transition. Efficient runtime scheduling of task transitions is needed to optimize system throughput and latency of the reconfiguration and transition periods. In this article, we provide an overview of a runtime framework enabling the efficient transition of tasks between software and hardware in response to changes in system inputs. We further present and analyze several runtime transition scheduling algorithms and highlight the latency and throughput tradeoffs for two data-adaptable systems. To evaluate the task transition selection algorithms, a case study was performed on an adaptable JPEG2000 implementation as well as three other synchronous dataflow systems characterized by transition latency and communication load.</p>
},
	keywords = {Data adaptability, hardware/software codesign, model-based design, runtime transition scheduling},
	issn = {1539-9087},
	doi = {10.1145/3047498},
	url = {http://doi.acm.org/10.1145/3047498},
	author = {Nathan Sandoval and Casey Mackin and Sean Whitsitt and Gopinath, Vijay Shankar and Sachidanand Mahadevan and Milakovich, Andrew and Merry, Kyle and Jonathan Sprinkle and Roman Lysecky}
}
@conference { c:milakovic2012ecbs,
	title = {Automated Software Generation and Hardware Coprocessor Synthesis for Data-Adaptable Reconfigurable Systems},
	booktitle = {Engineering of Computer Based Systems (ECBS), 2012 IEEE 19th International Conference and Workshops on},
	year = {2012},
	pages = {15-23},
	abstract = {<p>We present an overview of a data-adaptable reconfigurable embedded systems design methodology. The paper presents a novel paradigm for hardware/software code sign and reconfigurable computing driven by data-adaptability. The data-adaptable approach allows designers to directly model the data configurability of the target application, thereby enabling a solution that permits dynamic reconfiguration based on the data profile of the incoming data stream. This approach permits low-power, small form-factor hardware implementations of algorithms that might otherwise consume significant resources, or perhaps exceed the available space of the reconfigurable hardware.</p>},
	keywords = {Data adaptability, hardware/software codesign, model-based design},
	doi = {10.1109/ECBS.2012.16},
	url = {http://dx.doi.org/10.1109/ECBS.2012.16},
	author = {Milakovich, Andrew and Vijay Gopinath and Roman Lysecky and Jonathan Sprinkle}
}
