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PagedAttention is a popular approach for dynamic memory allocation in LLM serving systems.
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Attention is All you Need. In Advances in Neural Information Processing Systems , I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30. Curran Associates, Inc
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(Mis)managed: A Novel TLB-based Covert Channel on GPUs. In Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security (Virtual Event, Hong Kong) (ASIA CCS ’21) . Association for Computing Machinery, New York, NY, USA, 872–885
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FlashAttention
2022 · 2022
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PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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Designing Virtual Memory System of MCM GPUs. In 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO) . 404–422
B Pratheek, Neha Jawalkar, and Arkaprava Basu. 2022 · 2022
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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
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Flash-Decoding for long-context inference
2023 · 2023
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FlashInfer: Kernel Library for LLM Serving
2023 · 2023
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LightLLM: A Light and Fast Inference Service for LLM
2023 · 2023
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Performance decay when using paged attention
2023 · 2023
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TensorRT-LLM: A TensorRT Toolbox for Optimized Large Language Model Inference
2023 · 2023
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Use optimized kernels for MQA/GQA
2023 · 2023
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SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills
Amey Agrawal, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, and Ramachandran Ramjee. 2023 · 2023
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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
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Ganesh Bikshandi and Jay Shah. 2023 · 2023
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FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Tri Dao. 2023 · 2023
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Efficient Memory Management for Large Language Model Serving with PagedAttention. In Proceedings of the 29th Symposium on Operating Systems Principles (Koblenz, Germany) (SOSP ’23) . Association for Computing Machinery, New York, NY, USA, 611–626
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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SpotServe: Serving Generative Large Language Models on Preemptible Instances
Xupeng Miao, Chunan Shi, Jiangfei Duan, Xiaoli Xi, Dahua Lin, Bin Cui, and Zhihao Jia. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
FlexGen: high-throughput generative inference of large language models with a single GPU. In Proceedings of the 40th International Conference on Machine Learning (Honolulu, Hawaii, USA) (ICML’23) . JMLR.org, Article 1288, 23 pages
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, and Ce Zhang. 2023 · 2023
Mélange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity
Tyler Griggs, Xiaoxuan Liu, Jiaxiang Yu, Doyoung Kim, Wei-Lin Chiang, Alvin Cheung, and Ion Stoica. 2024 · 2024
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GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching. In Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (La Jolla, CA, USA) (ASPLOS ’24) . Association for Computing Machinery, New York, NY, USA, 450–466
Cong Guo, Rui Zhang, Jiale Xu, Jingwen Leng, Zihan Liu, Ziyu Huang, Minyi Guo, Hao Wu, Shouren Zhao, Junping Zhao, and Ke Zhang. 2024 · 2024
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DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference
Connor Holmes, Masahiro Tanaka, Michael Wyatt, Ammar Ahmad Awan, Jeff Rasley, Samyam Rajbhandari, Reza Yazdani Aminabadi, Heyang Qin, Arash Bakhtiari, Lev Kurilenko, and Yuxiong He. 2024 · 2024
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OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, and Yang Liu. 2023 · 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
Cited alongside, same era.
TunneLs for Bootlegging: Fully Reverse-Engineering GPU TLBs for Challenging Isolation Guarantees of NVIDIA MIG. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (Copenhagen, Denmark) (CCS ’23) . Association for Computing Machinery, New York, NY, USA, 960–974
Zhenkai Zhang, Tyler Allen, Fan Yao, Xing Gao, and Rong Ge. 2023a · 2023
Cited alongside, same era.
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. In Advances in Neural Information Processing Systems , A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, and S. Levine (Eds.), Vol. 36. Curran Associates, Inc., 34661–34710
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang "Atlas" Wang, and Beidi Chen. 2023b · 2023
Cited alongside, same era.
Amazon CodeWhisperer
2024 · 2024
Cited alongside, same era.
ccdv/arxiv-summarization
2024 · 2024
Cited alongside, same era.
CUDA Toolkit Documentation: Virtual Memory Management
2024 · 2024
Cited alongside, same era.
Custom strides to support non-contiguous KV cache
2024 · 2024
Cited alongside, same era.
FlashDecoding++: Faster Large Language Model Inference with Asynchronization, Flat GEMM Optimization, and Heuristics. In Proceedings of Machine Learning and Systems , P. Gibbons, G. Pekhimenko, and C. De Sa (Eds.), Vol. 6. 148–161
Ke Hong, Guohao Dai, Jiaming Xu, Qiuli Mao, Xiuhong Li, Jun Liu, kangdi chen, Yuhan Dong, and Yu Wang. 2024 · 2024
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Inference without Interference: Disaggregate LLM Inference for Mixed Downstream Workloads
Cunchen Hu, Heyang Huang, Liangliang Xu, Xusheng Chen, Jiang Xu, Shuang Chen, Hao Feng, Chenxi Wang, Sa Wang, Yungang Bao, et al · 2024
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POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference
Aditya K Kamath, Ramya Prabhu, Jayashree Mohan, Simon Peter, Ramachandran Ramjee, and Ashish Panwar. 2024 · 2024
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Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs
Ferdi Kossmann, Bruce Fontaine, Daya Khudia, Michael Cafarella, and Samuel Madden. 2024 · 2024
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InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management
Wonbeom Lee, Jungi Lee, Junghwan Seo, and Jaewoong Sim. 2024 · 2024
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Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity
Da Ma, Lu Chen, Situo Zhang, Yuxun Miao, Su Zhu, Zhi Chen, Hongshen Xu, Hanqi Li, Shuai Fan, Lei Pan, and Kai Yu. 2024 · 2024
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MAPLE: A Framework for Active Preference Learning Guided by Large Language Models
Saaduddin Mahmud, Mason Nakamura, and Shlomo Zilberstein. 2024 · 2024
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Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs
Yixuan Mei, Yonghao Zhuang, Xupeng Miao, Juncheng Yang, Zhihao Jia, and Rashmi Vinayak. 2024 · 2024
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Accelerating Transformers with NVIDIA cuDNN 9
Matthew Nicely and NVIDIA. 2024 · 2024
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CUDA C++ Programming Guide
NVIDIA. 2024 · 2024
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Splitwise: Efficient Generative LLM Inference Using Phase Splitting. In 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) . 118–132
Pratyush Patel, Esha Choukse, Chaojie Zhang, Aashaka Shah, Íñigo Goiri, Saeed Maleki, and Ricardo Bianchini. 2024 · 2024
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Lean Attention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Rühle, and Saravan Rajmohan. 2024 · 2024
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FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, and Tri Dao. 2024 · 2024
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Loki: Low-rank Keys for Efficient Sparse Attention
Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, and Abhinav Bhatele. 2024 · 2024
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DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara Mcallister, Amar Phanishayee, Jakub Tarnawski, and Ana Klimovic. 2024 · 2024
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A Multi-Level Superoptimizer for Tensor Programs
Mengdi Wu, Xinhao Cheng, Oded Padon, and Zhihao Jia. 2024 · 2024
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Accelerating Self-Attentions for LLM Serving with FlashInfer
Zihao Ye, Lequn Chen, Ruihang Lai, Yilong Zhao, Size Zheng, Junru Shao, Bohan Hou, Hongyi Jin, Yifei Zuo, Liangsheng Yin, Tianqi Chen, and Luis Ceze. 2024 · 2024
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SGLang: Efficient Execution of Structured Language Model Programs
Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Chuyue Sun, Jeff Huang, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark Barrett, and Ying Sheng. 2024 · 2024
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DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving. In 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI 24) . USENIX Association, Santa Clara, CA, 193–210
Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, and Hao Zhang. 2024 · 2024
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NanoFlow: Towards Optimal Large Language Model Serving Throughput
Kan Zhu, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Yufei Gao, Qinyu Xu, Tian Tang, Zihao Ye, Keisuke Kamahori, Chien-Yu Lin, Stephanie Wang, Arvind Krishnamurthy, and Baris Kasikci. 2024 · 2024
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