🔗 Who cites «MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs»

134 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · ← back to «MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs»

1. HybridFlow: A Flexible and Efficient RLHF FrameworkarXiv:2409.19256Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.2024 · 624 citations
2. Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI ArchitecturesProceedings - International Symposium on Computer Architecture/ProceedingsChenggang Zhao, Chengqi Deng, Chong Ruan, et al.2025 · 74 citations
3. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
4. FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel FusionarXiv:2406.06858Li-Wen Chang, Wenlei Bao, Qi Hou, et al.2024 · 67 citations
5. Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning2012 International Conference for High Performance Computing, Networking, Storage and AnalysisWei An, Xiao Bi, Guanting Chen, et al.2024 · 34 citations
6. Yi-Lightning Technical ReportarXiv:2412.01253Alan Wake, Bei Chen, C.X. Lv, et al.2024 · 11 citations
7. Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUsarXiv:2504.07866Yichun Yin, Wenyong Huang, Kaikai Song, et al.2025 · 6 citations
8. Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)Journal of SoftwareYanjie Gao (高彦杰), Yueguo Chen (陈跃国)2025

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

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