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Accelerating Multi-Model Inference by Merging DNNs of Different Weights., , , , and . CoRR, (2020)Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs., , , , , , and . CoRR, (2022)BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 16639-16653. PMLR, (2023)A Tensor Compiler for Unified Machine Learning Prediction Serving., , , , , , and . OSDI, page 899-917. USENIX Association, (2020)Parallax: Automatic Data-Parallel Training of Deep Neural Networks., , , , , , , , and . CoRR, (2018)Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach., , , , , and . CoRR, (2019)Speculative Symbolic Graph Execution of Imperative Deep Learning Programs., , , , , , and . ACM SIGOPS Oper. Syst. Rev., 53 (1): 26-33 (2019)WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele., , , , , , , and . Proc. VLDB Endow., 15 (1): 11-20 (2021)JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs., , , , , and . CoRR, (2018)Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks., , , , , , , , and . EuroSys, page 43:1-43:15. ACM, (2019)