🔗 Who cites «AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving»

151 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving»

1. HybridFlow: A Flexible and Efficient RLHF FrameworkarXiv:2409.19256Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.2024 · 624 citations
2. DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model ServingOSDI 2024Yinmin Zhong, Shengyu Liu, Junda Chen, et al.2024 · 409 citations
3. Splitwise: Efficient generative LLM inference using phase splittingISCA 2024Pratyush Patel, Esha Choukse, Chaojie Zhang, et al.2023 · 379 citations
4. DynamoLLM: Designing LLM Inference Clusters for Performance and Energy EfficiencyProceedings - International Symposium on High-Performance Computer Architecture/ProceedingsJovan Stojkovic, Chaojie Zhang, Inigo Goiri, et al.2024 · 218 citations
5. LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence ParallelismACM SIGOPS Symposium on Operating Systems Principles (SOSP)Bingyang Wu, Shengyu Liu, Yinmin Zhong, et al.2024 · 131 citations
6. Fast Distributed Inference Serving for Large Language ModelsarXiv 2023Bingyang Wu, Yinmin Zhong, Zili Zhang, et al.2023 · 123 citations
7. Llumnix: Dynamic Scheduling for Large Language Model ServingOSDI 2024Biao Sun, Ziming Huang, Hanyu Zhao, et al.2024 · 119 citations
8. Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to SystemsACM Computing SurveysXupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.2023 · 110 citations
9. ServerlessLLM: Low-Latency Serverless Inference for Large Language ModelsarXiv:2401.14351Yao Fu, Leyang Xue, Yeqi Huang, et al.2024 · 105 citations
10. S-LoRA: Serving Thousands of Concurrent LoRA AdaptersMLSys 2024Ying Sheng, Shiyi Cao, Dacheng Li, et al.2023 · 80 citations

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

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