Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

8 September 2018

Papers citing "Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform"

19 / 19 papers shown

Title
Nesterov Method for Asynchronous Pipeline Parallel Optimization Thalaiyasingam Ajanthan Sameera Ramasinghe Yan Zuo Gil Avraham Alexander Long 24 0 0 02 May 2025
PipeOptim: Ensuring Effective 1F1B Schedule with Optimizer-Dependent Weight Prediction Lei Guan Dongsheng Li Jiye Liang Wenjian Wang Wenjian Wang Xicheng Lu 32 1 0 01 Dec 2023
A Survey From Distributed Machine Learning to Distributed Deep Learning Mohammad Dehghani Zahra Yazdanparast 23 0 0 11 Jul 2023
DISCO: Distributed Inference with Sparse Communications Minghai Qin Chaowen Sun Jaco A. Hofmann D. Vučinić FedML 27 1 0 22 Feb 2023
Weight Prediction Boosts the Convergence of AdamW Lei Guan 21 15 0 01 Feb 2023
Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression Jaeyong Song Jinkyu Yim Jaewon Jung Hongsun Jang H. Kim Youngsok Kim Jinho Lee GNN 24 25 0 24 Jan 2023
LOFT: Finding Lottery Tickets through Filter-wise Training Qihan Wang Chen Dun Fangshuo Liao C. Jermaine Anastasios Kyrillidis 23 3 0 28 Oct 2022
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network Vitaliy Chiley Vithursan Thangarasa Abhay Gupta Anshul Samar Joel Hestness D. DeCoste 50 8 0 28 Jun 2022
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 24 9 0 28 Apr 2022
Efficient Pipeline Planning for Expedited Distributed DNN Training Ziyue Luo Xiaodong Yi Guoping Long Shiqing Fan Chuan Wu Jun Yang Wei Lin 28 16 0 22 Apr 2022
DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices Xueyu Hou Yongjie Guan Tao Han Ning Zhang 19 41 0 03 Feb 2022
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training Chen Dun Cameron R. Wolfe C. Jermaine Anastasios Kyrillidis 16 21 0 02 Jul 2021
Parareal Neural Networks Emulating a Parallel-in-time Algorithm Zhanyu Ma Jiyang Xie Jingyi Yu AI4CE 18 9 0 16 Mar 2021
A Study of Checkpointing in Large Scale Training of Deep Neural Networks Elvis Rojas A. Kahira Esteban Meneses L. Bautista-Gomez Rosa M. Badia 21 22 0 01 Dec 2020
Integrating Deep Learning in Domain Sciences at Exascale Rick Archibald E. Chow E. DÁzevedo Jack J. Dongarra M. Eisenbach ... Florent Lopez Daniel Nichols S. Tomov Kwai Wong Junqi Yin PINN 23 5 0 23 Nov 2020
DAPPLE: A Pipelined Data Parallel Approach for Training Large Models Shiqing Fan Yi Rong Chen Meng Zongyan Cao Siyu Wang ... Jun Yang Lixue Xia Lansong Diao Xiaoyong Liu Wei Lin 21 232 0 02 Jul 2020
HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism Jay H. Park Gyeongchan Yun Chang Yi N. T. Nguyen Seungmin Lee Jaesik Choi S. Noh Young-ri Choi MoE 25 128 0 28 May 2020
Pipelined Backpropagation at Scale: Training Large Models without Batches Atli Kosson Vitaliy Chiley Abhinav Venigalla Joel Hestness Urs Koster 35 33 0 25 Mar 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 299 2,890 0 15 Sep 2016