Baechi: Fast Device Placement of Machine Learning Graphs

20 January 2023

Papers citing "Baechi: Fast Device Placement of Machine Learning Graphs"

7 / 7 papers shown

Title
Scalable Differential Privacy Mechanisms for Real-Time Machine Learning Applications Jessica Smith David Williams Emily Brown 26 0 0 16 Sep 2024
Moirai: Towards Optimal Placement for Distributed Inference on Heterogeneous Devices Beibei Zhang Hongwei Zhu Feng Gao Zhihui Yang Xiaoyang Sean Wang 22 1 0 07 Dec 2023
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment Shiwei Zhang Xiaodong Yi Lansong Diao Chuan Wu Siyu Wang W. Lin GNN 11 5 0 13 Feb 2023
FuncPipe: A Pipelined Serverless Framework for Fast and Cost-efficient Training of Deep Learning Models Yunzhuo Liu Bo Jiang Tian Guo Zimeng Huang Wen-ping Ma Xinbing Wang Chenghu Zhou 17 9 0 28 Apr 2022
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices Byung Hoon Ahn Jinwon Lee J. Lin Hsin-Pai Cheng Jilei Hou H. Esmaeilzadeh 62 54 0 04 Mar 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 245 1,817 0 17 Sep 2019
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016