Scaling Deep Learning on GPU and Knights Landing clusters

Scaling Deep Learning on GPU and Knights Landing clusters

9 August 2017

Yang You

Papers citing "Scaling Deep Learning on GPU and Knights Landing clusters"

11 / 11 papers shown

Title
Towards Efficient Communications in Federated Learning: A Contemporary Survey Zihao Zhao Yuzhu Mao Yang Liu Linqi Song Ouyang Ye Xinlei Chen Wenbo Ding FedML 66 60 0 02 Aug 2022
Reducing Data Motion to Accelerate the Training of Deep Neural Networks Sicong Zhuang Cristiano Malossi Marc Casas 27 0 0 05 Apr 2020
Communication Contention Aware Scheduling of Multiple Deep Learning Training Jobs Qiang-qiang Wang S. Shi Canhui Wang Xiaowen Chu 24 13 0 24 Feb 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach Pengchao Han Shiqiang Wang K. Leung FedML 35 175 0 14 Jan 2020
A Survey on Distributed Machine Learning Joost Verbraeken Matthijs Wolting Jonathan Katzy Jeroen Kloppenburg Tim Verbelen Jan S. Rellermeyer OOD 42 692 0 20 Dec 2019
MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning S. Shi Xiaowen Chu Bo Li FedML 28 25 0 18 Dec 2019
Layer-wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees S. Shi Zhenheng Tang Qiang-qiang Wang Kaiyong Zhao Xiaowen Chu 19 22 0 20 Nov 2019
AI Enabling Technologies: A Survey V. Gadepally Justin A. Goodwin J. Kepner Albert Reuther Hayley Reynolds S. Samsi Jonathan Su David Martinez 27 24 0 08 May 2019
GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware A. Samajdar Parth Mannan K. Garg T. Krishna 32 20 0 03 Aug 2018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis Tal Ben-Nun Torsten Hoefler GNN 33 704 0 26 Feb 2018
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 310 2,896 0 15 Sep 2016