Task Transition Scheduling for Data-Adaptable Systems

Author:

Sandoval Nathan1,Mackin Casey1,Whitsitt Sean1,Gopinath Vijay Shankar1,Mahadevan Sachidanand1,Milakovich Andrew1,Merry Kyle1,Sprinkle Jonathan1,Lysecky Roman1

Affiliation:

1. University of Arizona, Tucson, AZ

Abstract

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.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A case for design space exploration of context-aware adaptive embedded systems;Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion;2019-10-13

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