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Serving systems for Large Language Models (LLMs) are often optimized to improve quality of service (QoS) and throughput.
Xgboost: A scalable tree boosting system. In Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining . 785–794
Tianqi Chen and Carlos Guestrin. 2016 · 2016
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Fast transformer decoding: One write-head is all you need
Noam Shazeer. 2019 · 2019
Earlier work this paper cites.
Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 3505–3506
Jeff Rasley and Rajbhandari et.al. 2020 · 2020
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Faster and Cheaper Serverless Computing on Harvested Resources. In Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles
Yanqi Zhang, Íñigo Goiri, Gohar Irfan Chaudhry, Rodrigo Fonseca, Sameh Elnikety, Christina Delimitrou, and Ricardo Bianchini. 2021 · 2021
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Llm. int8 (): 8-bit matrix multiplication for transformers at scale
Tim Dettmers, Mike Lewis, Younes Belkada, and Luke Zettlemoyer. 2022 · 2022
Earlier work this paper cites.
Introducing ChatGPT
OpenAI. 2022 · 2022
Earlier work this paper cites.
Orca: A Distributed Serving System for Transformer-Based Generative Models. In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22) . USENIX Association, Carlsbad, CA, 521–538
Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, and Byung-Gon Chun. 2022 · 2022
Earlier work this paper cites.
Lightllm: A python-based large language model inference and serving framework
2023 · 2023
Earlier work this paper cites.
Failure Analysis of Big Cloud Service Providers Prior to and During Covid-19 Period
Muhammad Ahsan, Sacheendra Talluri, and Alexandru Iosup. 2023 · 2023
Earlier work this paper cites.
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, and Sumit Sanghai. 2023 · 2023
Earlier work this paper cites.
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, and Jianfeng Gao. 2023 · 2023
Cited alongside, same era.
The False Promise of Imitating Proprietary LLMs
Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, and Dawn Song. 2023 · 2023
Cited alongside, same era.
FlashDecoding++: Faster Large Language Model Inference on GPUs
Ke Hong, Guohao Dai, Jiaming Xu, Qiuli Mao, Xiuhong Li, Jun Liu, Kangdi Chen, Hanyu Dong, and Yu Wang. 2023 · 2023
Cited alongside, same era.
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving
Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E Gonzalez, et al · 2023
Cited alongside, same era.
Fast Distributed Inference Serving for Large Language Models
Bingyang Wu, Yinmin Zhong, Zili Zhang, Gang Huang, Xuanzhe Liu, and Xin Jin. 2023 · 2023
Later among the works it cites.
Smoothquant: Accurate and efficient post-training quantization for large language models. In International Conference on Machine Learning . PMLR, 38087–38099
Guangxuan Xiao, Ji Lin, Mickael Seznec, Hao Wu, Julien Demouth, and Song Han. 2023 · 2023
Later among the works it cites.
Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
Zangwei Zheng, Xiaozhe Ren, Fuzhao Xue, Yang Luo, Xin Jiang, and Yang You. 2023 · 2023
Later among the works it cites.
MemServe: Context Caching for Disaggregated LLM Serving with Elastic Memory Pool
Cunchen Hu, Heyang Huang, Junhao Hu, Jiang Xu, Xusheng Chen, Tao Xie, Chenxi Wang, Sa Wang, Yungang Bao, Ninghui Sun, and Yizhou Shan. 2024 · 2024
Closest in time.
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Xupeng Miao and Gabriele Oliaro et.al. 2023 · 2023
Cited alongside, same era.
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Hongyi Jin, Tianqi Chen, and Zhihao Jia. 2023 · 2023
Cited alongside, same era.
Optimizing inference on large language models with nvidia tensorrt-llm
Oh Neal, Vaidya anf Fred and Comly Nick. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Cited alongside, same era.
Flash-decoding for long-context inference
Dao Tri, Haziza Daniel, Massa Francisco, and Sizov Grigory. 2023 · 2023
Cited alongside, same era.
Azure OpenAI Service
[n. d.]
Cited in the paper.
vLLM: Easy, Fast, and Cheap LLM Serving with PagedAttention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Yu, Joey Gonzalez, Hao Zhang, and Ion Stoica. 2023a
Cited in the paper.
Ruoyu Qin, Zheming Li, Weiran He, Mingxing Zhang, Yongwei Wu, Weimin Zheng, and Xinran Xu. 2024 · 2024
Closest in time.
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion. In The Thirty-eighth Annual Conference on Neural Information Processing Systems
Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu ming Cheung, Amelie Chi Zhou, Bo Han, and Xiaowen Chu. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Machel Reid, Nikolay Savinov, and etc. 2024 · 2024
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DistServe: disaggregating prefill and decoding for goodput-optimized large language model serving. In Proceedings of the 18th USENIX Conference on Operating Systems Design and Implementation (Santa Clara, CA, USA) (OSDI’24) . USENIX Association, USA, Article 11, 18 pages
Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, and Hao Zhang. 2024 · 2024
Closest in time.
Training and Serving System of Foundation Models: A Comprehensive Survey
Jiahang Zhou, Yanyu Chen, Zicong Hong, Wuhui Chen, Yue Yu, Tao Zhang, Hui Wang, Chuanfu Zhang, and Zibin Zheng. 2024 · 2024
Closest in time.