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Inference Time Reduction of Deep Neural Networks on Embedded Devices: A Case Study., , , and . DSD, page 205-213. IEEE, (2022)ApproxDNN: Incentivizing DNN Approximation in Cloud., , and . CCGRID, page 639-648. IEEE, (2020)Data locality and VM interference aware mitigation of data skew in hadoop leveraging modern portfolio theory., and . SAC, page 175-182. ACM, (2018)BatchSizer: Power-Performance Trade-off for DNN Inference., , and . ASP-DAC, page 819-824. ACM, (2021)Communication-Awareness for Energy-Efficiency in Datacenters., and . Advances in Computers, (2016)Mobility-Aware Computation Offloading in Edge Computing Using Machine Learning., , and . IEEE Trans. Mob. Comput., 22 (1): 328-340 (2023)On the Impact of Device-Level Techniques on Energy-Efficiency of Neural Network Accelerators., and . CoRR, (2021)Energy efficiency in cloud-based MapReduce applications through better performance estimation., and . DATE, page 1339-1344. IEEE, (2016)An Overview of Efficient Interconnection Networks for Deep Neural Network Accelerators., , , , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 10 (3): 268-282 (2020)MediatorDNN: Contention Mitigation for Co-Located DNN Inference Jobs., , and . CLOUD, page 502-512. IEEE, (2024)