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Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications., , , , , , , , , and 18 other author(s). CoRR, (2018)Characterizing Deep Learning Training Workloads on Alibaba-PAI., , , , , , and . IISWC, page 189-202. IEEE, (2019)ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation., , , , , , , , , and 3 other author(s). CVPR, page 11398-11407. Computer Vision Foundation / IEEE, (2019)Caffe, , , , , , , and . Proceedings of the 22nd ACM international conference on Multimedia, ACM, (November 2014)Caffe: An Open Source Convolutional Architecture for Fast Feature Embedding. (2013)TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, , , , , , , , , and 30 other author(s). (2015)Software available from tensorflow.org.Machine Learning at Facebook: Understanding Inference at the Edge., , , , , , , , , and 16 other author(s). HPCA, page 331-344. IEEE, (2019)Learning cross-modality similarity for multinomial data., , and . ICCV, page 2407-2414. IEEE Computer Society, (2011)AntMan: Dynamic Scaling on GPU Clusters for Deep Learning., , , , , , , , and . OSDI, page 533-548. USENIX Association, (2020)Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters., , , , , , , , , and 4 other author(s). Proc. VLDB Endow., 14 (12): 2972-2985 (2021)