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PyTorch: An Imperative Style, High-Performance Deep Learning Library, , , , , , , , , and 11 other author(s). Advances in Neural Information Processing Systems 32, Curran Associates, Inc., (2019)Rigel: flexible multi-rate image processing hardware., , , , , and . ACM Trans. Graph., 35 (4): 85:1-85:11 (2016)Just-in-time Length Specialization of Dynamic Vector Code., , and . ARRAY@PLDI, page 20-25. ACM, (2014)Automatic Differentiation in PyTorch, , , , , , , , , and . NIPS 2017 Workshop on Autodiff, (2017)Generative AI Beyond LLMs: System Implications of Multi-Modal Generation., , , , , , , , , and 1 other author(s). CoRR, (2023)Using Python for Model Inference in Deep Learning., , , , , and . CoRR, (2021)PyTorch: An Imperative Style, High-Performance Deep Learning Library., , , , , , , , , and 11 other author(s). NeurIPS, page 8024-8035. (2019)MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems., , , , , , , and . CoRR, (2023)PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation., , , , , , , , , and 39 other author(s). ASPLOS (2), page 929-947. ACM, (2024)torch.fx: Practical Program Capture and Transformation for Deep Learning in Python., , , , and . MLSys, mlsys.org, (2022)