Taming Algorithmic Priority Inversion in Mission-Critical Perception Pipelines

Taming Algorithmic Priority Inversion in Mission-Critical Perception Pipelines

The paper discusses algorithmic priority inversion in mission-critical machine inference pipelines used in modern neural-network-based perception subsystems and describes a solution to mitigate its effect. In general, priority inversion occurs in computing systems when computations that are “less im...

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Bibliographic Details
Main Authors: Liu, Shengzhong, Yao, Shuochao, Fu, Xinzhe, Tabish, Rohan, Yu, Simon, Bansal, Ayoosh, Yun, Heechul, Sha, Liu, Abdelzaher, Tarek
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Format: Article
Language:English
Published: ACM|Communications of the ACM 2024
Online Access:https://hdl.handle.net/1721.1/153445

Internet

https://hdl.handle.net/1721.1/153445

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