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Rigel: flexible multi-rate image processing hardware., , , , , and . ACM Trans. Graph., 35 (4): 85:1-85:11 (2016)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)Just-in-time Length Specialization of Dynamic Vector Code., , and . ARRAY@PLDI, page 20-25. ACM, (2014)MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems., , , , , , , and . CoRR, (2023)torch.fx: Practical Program Capture and Transformation for Deep Learning in Python., , , , and . MLSys, mlsys.org, (2022)The Design of Terra: Harnessing the Best Features of High-Level and Low-Level Languages., and . SNAPL, volume 32 of LIPIcs, page 79-89. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2015)The Next 700 Accelerated Layers: From Mathematical Expressions of Network Computation Graphs to Accelerated GPU Kernels, Automatically., , , , , , , , and . ACM Trans. Archit. Code Optim., 16 (4): 38:1-38:26 (2020)Ebb: A DSL for Physical Simulation on CPUs and GPUs., , , , , , and . ACM Trans. Graph., 35 (2): 21:1-21:12 (2016)Riposte: a trace-driven compiler and parallel VM for vector code in R., , and . PACT, page 43-52. ACM, (2012)Automatic Differentiation in PyTorch, , , , , , , , , and . NIPS 2017 Workshop on Autodiff, (2017)