SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked
Prefills

SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills

31 August 2023

Jayashree Mohan

Bhargav S. Gulavani

Papers citing "SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills"

17 / 17 papers shown

Title
Prefill-Based Jailbreak: A Novel Approach of Bypassing LLM Safety Boundary Yakai Li Jiekang Hu Weiduan Sang Luping Ma Jing Xie Weijuan Zhang Aimin Yu Shijie Zhao Qingjia Huang Qihang Zhou AAML 52 0 0 28 Apr 2025
Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents Yueying Li Jim Dai Tianyi Peng 59 1 0 10 Apr 2025
Seesaw: High-throughput LLM Inference via Model Re-sharding Qidong Su Wei Zhao X. Li Muralidhar Andoorveedu Chenhao Jiang Zhanda Zhu Kevin Song Christina Giannoula Gennady Pekhimenko LRM 72 0 0 09 Mar 2025
Geometric Collaborative Filtering with Convergence Hisham Husain Julien Monteil FedML 23 5 0 04 Oct 2024
Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads on Consumer-Grade Devices Yuxiang Huang Binhang Yuan Xu Han Chaojun Xiao Zhiyuan Liu RALM 73 1 0 02 Oct 2024
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale Jaehong Cho Minsu Kim Hyunmin Choi Guseul Heo Jongse Park 38 8 0 10 Aug 2024
Teola: Towards End-to-End Optimization of LLM-based Applications Xin Tan Yimin Jiang Yitao Yang Hong-Yu Xu 57 5 0 29 Jun 2024
CacheBlend: Fast Large Language Model Serving for RAG with Cached Knowledge Fusion Jiayi Yao Hanchen Li Yuhan Liu Siddhant Ray Yihua Cheng Qizheng Zhang Kuntai Du Shan Lu Junchen Jiang 42 14 0 26 May 2024
Preble: Efficient Distributed Prompt Scheduling for LLM Serving Vikranth Srivatsa Zijian He Reyna Abhyankar Dongming Li Yiying Zhang 40 17 0 08 May 2024
vAttention: Dynamic Memory Management for Serving LLMs without PagedAttention Ramya Prabhu Ajay Nayak Jayashree Mohan R. Ramjee Ashish Panwar VLM 55 24 0 07 May 2024
FlexLLM: A System for Co-Serving Large Language Model Inference and Parameter-Efficient Finetuning Xupeng Miao Gabriele Oliaro Xinhao Cheng Vineeth Kada Ruohan Gao ... April Yang Yingcheng Wang Mengdi Wu Colin Unger Zhihao Jia MoE 88 9 0 29 Feb 2024
Splitwise: Efficient generative LLM inference using phase splitting Pratyush Patel Esha Choukse Chaojie Zhang Aashaka Shah Íñigo Goiri Saeed Maleki Ricardo Bianchini 36 194 0 30 Nov 2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU Ying Sheng Lianmin Zheng Binhang Yuan Zhuohan Li Max Ryabinin ... Joseph E. Gonzalez Percy Liang Christopher Ré Ion Stoica Ce Zhang 144 365 0 13 Mar 2023
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference Haiyang Huang Newsha Ardalani Anna Y. Sun Liu Ke Hsien-Hsin S. Lee Anjali Sridhar Shruti Bhosale Carole-Jean Wu Benjamin C. Lee MoE 65 21 0 10 Mar 2023
Varuna: Scalable, Low-cost Training of Massive Deep Learning Models Sanjith Athlur Nitika Saran Muthian Sivathanu R. Ramjee Nipun Kwatra GNN 28 79 0 07 Nov 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,424 0 23 Jan 2020
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 243 1,791 0 17 Sep 2019