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Who cites «Beyond Data and Model Parallelism for Deep Neural Networks»

140 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← back to «Beyond Data and Model Parallelism for Deep Neural Networks»

  1. On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
  2. Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep LearningOSDI 2022Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.2022 · 279 citations
  3. FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving PerformancearXiv:2305.05176Lingjiao Chen, Matei Zaharia, James Zou2023 · 241 citations
  4. Mesh-TensorFlow: Deep Learning for SupercomputersarXiv:1811.02084Noam Shazeer, Youlong Cheng, Niki Parmar, et al.2018 · 203 citations
  5. PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel ComputationarXiv:2104.12369Wei Zeng, Xiaozhe Ren, Teng Su, et al.2021 · 161 citations
  6. Memory-Efficient Pipeline-Parallel DNN TrainingInternational Conference on Machine Learning (ICML)Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, et al.2020 · 153 citations
  7. DAPPLE: A Pipelined Data Parallel Approach for Training Large ModelsarXiv:2007.01045Shiqing Fan, Yi Rong, Chen Meng, et al.2020 · 107 citations
  8. Accelerating Distributed MoE Training and Inference with LinaarXiv:2210.17223Jiamin Li, Yimin Jiang, Yibo Zhu, et al.2022 · 92 citations
  9. TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph SubstitutionsSOSP 2019Zhihao Jia, Oded Padon, James Thomas, et al.2019 · 72 citations

129 more papers of our library cite it; they have no page here yet.

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