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PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel., , , , , , , , , и 8 other автор(ы). Proc. VLDB Endow., 16 (12): 3848-3860 (2023)PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation., , , , , , , , , и 39 other автор(ы). ASPLOS (2), стр. 929-947. ACM, (2024)Power Consumption Analysis of Parallel Algorithms on GPUs, , , , , , и . High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS), 2014 IEEE Intl Conf on, стр. 304-311. (августа 2014)Brief Industry Paper: Evaluating Robustness of Deep Learning-Based Recommendation Systems Against Hardware Errors: A Case Study., , , , , и . RTSS, стр. 468-472. IEEE, (2023)Dr. DNA: Combating Silent Data Corruptions in Deep Learning using Distribution of Neuron Activations., , , , , , и . ASPLOS (3), стр. 239-252. ACM, (2024)PyTorch: An Imperative Style, High-Performance Deep Learning Library, , , , , , , , , и 11 other автор(ы). Advances in Neural Information Processing Systems 32, Curran Associates, Inc., (2019)Efficient Linear Programming for Dense CRFs., , , , , и . CoRR, (2016)Optimization for, and by, machine learning.. University of Oxford, UK, (2019)British Library, EThOS.Fast and Green Computing with Graphics Processing Units for Solving Sparse Linear Systems., , и . HPCC/CSS/ICESS, стр. 129-136. IEEE, (2014)Efficient Linear Programming for Dense CRFs., , , , , и . CVPR, стр. 2934-2942. IEEE Computer Society, (2017)