ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2302.11665
  4. Cited By
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep
  Learning Serving

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving

22 February 2023
Zhuohan Li
Lianmin Zheng
Yinmin Zhong
Vincent Liu
Ying Sheng
Xin Jin
Yanping Huang
Zhifeng Chen
Hao Zhang
Joseph E. Gonzalez
Ion Stoica
    MoE
ArXivPDFHTML

Papers citing "AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving"

10 / 10 papers shown
Title
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
179
0
0
08 Jan 2025
Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Vikranth Srivatsa
Zijian He
Reyna Abhyankar
Dongming Li
Yiying Zhang
52
18
0
08 May 2024
Towards Pareto Optimal Throughput in Small Language Model Serving
Towards Pareto Optimal Throughput in Small Language Model Serving
Pol G. Recasens
Yue Zhu
Chen Wang
Eun Kyung Lee
Olivier Tardieu
Alaa Youssef
Jordi Torres
Josep Ll. Berral
40
4
0
04 Apr 2024
MOPAR: A Model Partitioning Framework for Deep Learning Inference
  Services on Serverless Platforms
MOPAR: A Model Partitioning Framework for Deep Learning Inference Services on Serverless Platforms
Jiaang Duan
Shiyou Qian
Dingyu Yang
Hanwen Hu
Jian Cao
Guangtao Xue
MoE
42
1
0
03 Apr 2024
FastDecode: High-Throughput GPU-Efficient LLM Serving using
  Heterogeneous Pipelines
FastDecode: High-Throughput GPU-Efficient LLM Serving using Heterogeneous Pipelines
Jiaao He
Jidong Zhai
39
27
0
18 Mar 2024
Compass: A Decentralized Scheduler for Latency-Sensitive ML Workflows
Compass: A Decentralized Scheduler for Latency-Sensitive ML Workflows
Yuting Yang
Andrea Merlina
Weijia Song
Tiancheng Yuan
Ken Birman
Roman Vitenberg
49
0
0
27 Feb 2024
DEAP: Design Space Exploration for DNN Accelerator Parallelism
DEAP: Design Space Exploration for DNN Accelerator Parallelism
Ekansh Agrawal
Xiangyu Sam Xu
26
1
0
24 Dec 2023
Splitwise: Efficient generative LLM inference using phase splitting
Splitwise: Efficient generative LLM inference using phase splitting
Pratyush Patel
Esha Choukse
Chaojie Zhang
Aashaka Shah
Íñigo Goiri
Saeed Maleki
Ricardo Bianchini
49
197
0
30 Nov 2023
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
89
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
245
1,821
0
17 Sep 2019
1