Fetching the paper…
Reading the bibliography…
Distributed LLM serving is costly and often underutilizes hardware accelerators due to three key challenges: bubbles in pipeline-parallel deployments caused by the bimodal latency of prompt and token processing, GPU memory overprovisioning, and long recovery times in case of failures.
Cuda c/c++ streams and concurrency
NVIDIA · 2015
Earlier work this paper cites.
Poseidon: An efficient communication architecture for distributed deep learning on GPU clusters
Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, and Eric P. Xing · 2017
Earlier work this paper cites.
Analysis of Large-Scale Multi-Tenant GPU clusters for DNN training workloads
Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, and Fan Yang · 2019
Earlier work this paper cites.
Pipedream: Generalized pipeline parallelism for dnn training
Deepak Narayanan, Aaron Harlap, Amar Phanishayee, Vivek Seshadri, Nikhil R. Devanur, Gregory R. Ganger, Phillip B. Gibbons, and Matei Zaharia · 2019
Earlier work this paper cites.
fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
Boost.asio
Boost · 2021
Earlier work this paper cites.
Efficient large-scale language model training on gpu clusters using megatron-lm, 2021
Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Anand Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, and Matei Zaharia · 2021
Earlier work this paper cites.
Zero-infinity: breaking the gpu memory wall for extreme scale deep learning
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, and Yuxiong He · 2021
Earlier work this paper cites.
Deepspeed inference: Enabling efficient inference of transformer models at unprecedented scale, 2022
Reza Yazdani Aminabadi, Samyam Rajbhandari, Minjia Zhang, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Jeff Rasley, Shaden Smith, Olatunji Ruwase, and Yuxiong He · 2022
Earlier work this paper cites.
Check-N-Run: a checkpointing system for training deep learning recommendation models
Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Krishnakumar Nair, Misha Smelyanskiy, and Murali Annavaram · 2022
Cited alongside, same era.
Harmony: overcoming the hurdles of gpu memory capacity to train massive dnn models on commodity servers
Youjie Li, Amar Phanishayee, Derek Murray, Jakub Tarnawski, and Nam Sung Kim · 2022
Cited alongside, same era.
Orca: A distributed serving system for Transformer-Based generative models
Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, and Byung-Gon Chun · 2022
Cited alongside, same era.
Opt: Open pre-trained transformer language models, 2022
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Sarathi: Efficient llm inference by piggybacking decodes with chunked prefills, 2023
Amey Agrawal, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, and Ramachandran Ramjee · 2023
Openai developer platform
OpenAI · 2023
Later among the works it cites.
Open mpi: Open source high performance computing
OpenMPI · 2023
Later among the works it cites.
Splitwise: Efficient generative llm inference using phase splitting, 2023
Pratyush Patel, Esha Choukse, Chaojie Zhang, Íñigo Goiri, Aashaka Shah, Saeed Maleki, and Ricardo Bianchini · 2023
Later among the works it cites.
Pci express
Wikipedia · 2023
Later among the works it cites.
Bloom: A 176b-parameter open-access multilingual language model, 2023
BigScience Workshop · 2023
Later among the works it cites.
H 2 o: Heavy-hitter oracle for efficient generative inference of large language models, 2023
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang Wang, and Beidi Chen · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Punica: Multi-tenant lora serving, 2023
Lequn Chen, Zihao Ye, Yongji Wu, Danyang Zhuo, Luis Ceze, and Arvind Krishnamurthy · 2023
Cited alongside, same era.
Longnet: Scaling transformers to 1,000,000,000 tokens, 2023
Jiayu Ding, Shuming Ma, Li Dong, Xingxing Zhang, Shaohan Huang, Wenhui Wang, Nanning Zheng, and Furu Wei · 2023
Cited alongside, same era.
Github copilot
Github · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica · 2023
Cited alongside, same era.
Spotserve: Serving generative large language models on preemptible instances, 2023
Xupeng Miao, Chunan Shi, Jiangfei Duan, Xiaoli Xi, Dahua Lin, Bin Cui, and Zhihao Jia · 2023
Cited alongside, same era.
Nvidia collective communications library (nccl)
NVIDIA
Cited in the paper.
Nvidia fastertransformer
NVIDIA
Cited in the paper.
Lmsys-chat-1m: A large-scale real-world llm conversation dataset, 2023
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric. P Xing, Joseph E. Gonzalez, Ion Stoica, and Hao Zhang · 2023
Later among the works it cites.
Get more with less: Synthesizing recurrence with kv cache compression for efficient llm inference, 2024
Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi, and Beidi Chen · 2024
Closest in time.
Hexgen: Generative inference of large-scale foundation model over heterogeneous decentralized environment, 2024
Youhe Jiang, Ran Yan, Xiaozhe Yao, Yang Zhou, Beidi Chen, and Binhang Yuan · 2024
Closest in time.
Distserve: Disaggregating prefill and decoding for goodput-optimized large language model serving, 2024
Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, and Hao Zhang · 2024
Closest in time.