GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient
Aggregation in Distributed CNN Training

GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training

8 November 2018

Timo C. Wunderlich

Papers citing "GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training"

12 / 12 papers shown

Title
RS-DGC: Exploring Neighborhood Statistics for Dynamic Gradient Compression on Remote Sensing Image Interpretation Weiying Xie Zixuan Wang Jitao Ma Daixun Li Yunsong Li 38 0 0 29 Dec 2023
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression Xiaoyun Li Ping Li FedML 39 4 0 25 Nov 2022
Embedding Compression for Text Classification Using Dictionary Screening Jing Zhou Xinru Jing Mu Liu Hansheng Wang 29 0 0 23 Nov 2022
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training Chia-Yu Chen Jiamin Ni Songtao Lu Xiaodong Cui Pin-Yu Chen ... Naigang Wang Swagath Venkataramani Vijayalakshmi Srinivasan Wei Zhang K. Gopalakrishnan 29 0 0 21 Apr 2021
On the Utility of Gradient Compression in Distributed Training Systems Saurabh Agarwal Hongyi Wang Shivaram Venkataraman Dimitris Papailiopoulos 41 46 0 28 Feb 2021
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 25 110 0 10 Aug 2020
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi FedML 11 54 0 04 Aug 2020
Communication-Efficient Gradient Coding for Straggler Mitigation in Distributed Learning S. Kadhe O. O. Koyluoglu Kannan Ramchandran 32 11 0 14 May 2020
Communication optimization strategies for distributed deep neural network training: A survey Shuo Ouyang Dezun Dong Yemao Xu Liquan Xiao 30 12 0 06 Mar 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 29 327 0 22 Feb 2020
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning XINYAN DAI Xiao Yan Kaiwen Zhou Han Yang K. K. Ng James Cheng Yu Fan FedML 27 47 0 12 Nov 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 19 317 0 31 May 2019