--- title: "Who cites Memory-Efficient Pipeline-Parallel DNN Training" description: "98 papers of the Elamur Research library cite «Memory-Efficient Pipeline-Parallel DNN Training», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/narayanan-2020-memory-efficient-pipeline-parallel-dnn/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/narayanan-2020-memory-efficient-pipeline-parallel-dnn/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Memory-Efficient Pipeline-Parallel DNN Training](https://md.research.elamur.ai/free/en/papers/narayanan-2020-memory-efficient-pipeline-parallel-dnn/) / cited by # Who cites «Memory-Efficient Pipeline-Parallel DNN Training» 98 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «Memory-Efficient Pipeline-Parallel DNN Training»](https://md.research.elamur.ai/free/en/papers/narayanan-2020-memory-efficient-pipeline-parallel-dnn/) 1. [**PaLM: Scaling Language Modeling with Pathways arXiv:2204.02311**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 4,753 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/) 2. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/) 3. [**GLM-130B: An Open Bilingual Pre-trained Model arXiv:2210.02414**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 786 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/) 4. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/) 5. [**Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022**Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.*2022 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-alpa-automating-inter-intra-operator/) 6. [**Reducing Activation Recomputation in Large Transformer Models arXiv:2205.05198**Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.*2022 · 273 citations*](https://md.research.elamur.ai/free/en/papers/korthikanti-2022-reducing-activation-recomputation-large-transformer/) 7. [**ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning SC 2021**Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, et al.*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/rajbhandari-2021-zero-infinity-breaking-gpu-memory/) 8. [**Ring Attention with Blockwise Transformers for Near-Infinite Context arXiv:2310.01889**Hao Liu, Matei Zaharia, Pieter Abbeel*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ring-attention-blockwise-transformers-near/) 9. [**DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models arXiv:2309.14509**Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/jacobs-2023-deepspeed-ulysses-system-optimizations-enabling/) 10. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities arXiv:2404.17790**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/) 11. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations* 12. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/) 13. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/) 14. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/) 84 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/narayanan-2020-memory-efficient-pipeline-parallel-dnn/) — Memory-Efficient Pipeline-Parallel DNN Training