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SpotServe: Serving Generative Large Language Models on Preemptible
  Instances

SpotServe: Serving Generative Large Language Models on Preemptible Instances

27 November 2023
Xupeng Miao
Chunan Shi
Jiangfei Duan
Xiaoli Xi
Dahua Lin
Bin Cui
Zhihao Jia
    VLM
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Papers citing "SpotServe: Serving Generative Large Language Models on Preemptible Instances"

13 / 13 papers shown
Title
Ascendra: Dynamic Request Prioritization for Efficient LLM Serving
Ascendra: Dynamic Request Prioritization for Efficient LLM Serving
Azam Ikram
Xiang Li
Sameh Elnikety
S. Bagchi
75
0
0
29 Apr 2025
Tempo: Application-aware LLM Serving with Mixed SLO Requirements
Tempo: Application-aware LLM Serving with Mixed SLO Requirements
Wei Zhang
Zhiyu Wu
Yi Mu
Banruo Liu
Myungjin Lee
Fan Lai
51
0
0
24 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
iServe: An Intent-based Serving System for LLMs
iServe: An Intent-based Serving System for LLMs
Dimitrios Liakopoulos
Tianrui Hu
Prasoon Sinha
N. Yadwadkar
VLM
127
0
0
08 Jan 2025
SkyServe: Serving AI Models across Regions and Clouds with Spot Instances
SkyServe: Serving AI Models across Regions and Clouds with Spot Instances
Ziming Mao
Tian Xia
Zhanghao Wu
Wei-Lin Chiang
Tyler Griggs
Romil Bhardwaj
Zongheng Yang
S. Shenker
Ion Stoica
44
1
0
03 Nov 2024
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference
  Serving at Scale
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale
Jaehong Cho
Minsu Kim
Hyunmin Choi
Guseul Heo
Jongse Park
38
9
0
10 Aug 2024
Teola: Towards End-to-End Optimization of LLM-based Applications
Teola: Towards End-to-End Optimization of LLM-based Applications
Xin Tan
Yimin Jiang
Yitao Yang
Hong-Yu Xu
59
5
0
29 Jun 2024
FlexLLM: A System for Co-Serving Large Language Model Inference and Parameter-Efficient Finetuning
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
FlexGen: High-Throughput Generative Inference of Large Language Models
  with a Single GPU
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
366
0
13 Mar 2023
Varuna: Scalable, Low-cost Training of Massive Deep Learning Models
Varuna: Scalable, Low-cost Training of Massive Deep Learning Models
Sanjith Athlur
Nitika Saran
Muthian Sivathanu
R. Ramjee
Nipun Kwatra
GNN
31
80
0
07 Nov 2021
What Makes Good In-Context Examples for GPT-$3$?
What Makes Good In-Context Examples for GPT-333?
Jiachang Liu
Dinghan Shen
Yizhe Zhang
Bill Dolan
Lawrence Carin
Weizhu Chen
AAML
RALM
275
1,312
0
17 Jan 2021
Serverless in the Wild: Characterizing and Optimizing the Serverless
  Workload at a Large Cloud Provider
Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider
Mohammad Shahrad
Rodrigo Fonseca
Íñigo Goiri
G. Chaudhry
Paul Batum
Jason Cooke
Eduardo Laureano
Colby Tresness
M. Russinovich
Ricardo Bianchini
79
601
0
06 Mar 2020
Megatron-LM: Training Multi-Billion Parameter Language Models Using
  Model Parallelism
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
1,817
0
17 Sep 2019
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