02032nas a2200277 4500008004100000022001400041245005800055210005700113300001900170490000700189520121400196653002201410653003101432653002301463653003401486100002101520700001801541700001901559700002901578700002701607700002301634700001601657700002301673700001901696856003901715 2017 eng d a1539-908700aTask Transition Scheduling for Data-Adaptable Systems0 aTask Transition Scheduling for DataAdaptable Systems a105:1–105:280 v163 a
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.
10aData adaptability10ahardware/software codesign10amodel-based design10aruntime transition scheduling1 aSandoval, Nathan1 aMackin, Casey1 aWhitsitt, Sean1 aGopinath, Vijay, Shankar1 aMahadevan, Sachidanand1 aMilakovich, Andrew1 aMerry, Kyle1 aSprinkle, Jonathan1 aLysecky, Roman uhttp://doi.acm.org/10.1145/3047498