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Understanding the thermal challenges of high-performance mobile devices with a detailed platform temperature model.

, and . IISWC, page 122-123. IEEE Computer Society, (2017)

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Optimizing User Satisfaction of Mobile Workloads Subject to Various Sources of Uncertainties., , and . IEEE Trans. Mob. Comput., 18 (12): 2941-2953 (2019)Architectural Thermal Energy Harvesting Opportunities for Sustainable Computing.. IEEE Comput. Archit. Lett., 13 (2): 65-68 (2014)The Architectural Implications of Facebook's DNN-based Personalized Recommendation., , , , , , , , , and 5 other author(s). CoRR, (2019)Understanding the Future of Energy Efficiency in Multi-Module GPUs., , , and . HPCA, page 519-532. IEEE, (2019)Chasing Carbon: The Elusive Environmental Footprint of Computing., , , , , , , and . CoRR, (2020)Understanding Capacity-Driven Scale-Out Neural Recommendation Inference., , , , , , and . CoRR, (2020)MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance., , , , , , , , , and 2 other author(s). IEEE Micro, 40 (2): 8-16 (2020)AutoScale: Energy Efficiency Optimization for Stochastic Edge Inference Using Reinforcement Learning., and . MICRO, page 1082-1096. IEEE, (2020)Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference., , , , , , , , and . CoRR, (2023)Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training., , , , , , , , , and 7 other author(s). CoRR, (2021)