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AI Waste Prevention: Time and Power Estimation for Edge Tensor Processing Units: Poster.

, , , , and . e-Energy, page 300-301. ACM, (2021)

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Playing Hare and Tortoise: The FigarOS Kernel for Fine-Grained System-Level Energy Optimizations., , , , , and . SBESC, page 80-83. IEEE Computer Society, (2015)AI Waste Prevention: Time and Power Estimation for Edge Tensor Processing Units: Poster., , , , and . e-Energy, page 300-301. ACM, (2021)The Narrow Way: Constructive Measures at Operating-System Level for Low Energy Use., , and . EnviroInfo (2), page 329-333. Shaker Verlag, Aachen, (2016)Automated Selection of Energy-efficient Operating System Configurations., , , , and . e-Energy, page 309-315. ACM, (2021)EnergyBudgets: Integrating Physical Energy Measurement Devices into Systems Software., , , and . SBESC, page 1-8. IEEE, (2020)Energy-demand estimation of embedded devices using deep artificial neural networks., , and . SAC, page 617-624. ACM, (2019)carbond: An Operating-System Daemon for Carbon Awareness., , , , , and . HotCarbon, page 2:1-2:6. ACM, (2023)X-Leep: Leveraging Cross-Layer Pacing for Energy-Efficient Edge Systems., , , , , , , and . e-Energy, page 548-553. ACM, (2020)Towards Automated System-Level Energy-Efficiency Optimisation using Machine Learning: Poster., , , , and . e-Energy, page 274-275. ACM, (2021)Pinpoint the Joules: Unifying Runtime-Support for Energy Measurements on Heterogeneous Systems., , , , , , , and . ROSS@SC, page 31-40. IEEE, (2020)