Training Recommender Systems at Scale: Communication-Efficient Model and
Data Parallelism

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Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism

18 October 2020

Dhruv Choudhary

Kannan Ramchandran

Michael W. Mahoney

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Papers citing "Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism"

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Title
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding Peihua Mai Youlong Ding Ziyan Lyu Minxin Du Yan Pang FedML 71 0 0 18 May 2025
SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models Jinho Yang Ji-Hoon Kim Joo-Young Kim 97 0 0 01 Apr 2025
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions Doaa Mahmud Hadeel Hajmohamed Shamma Almentheri Shamma Alqaydi Lameya Aldhaheri R. A. Khalil Nasir Saeed AI4TS 99 12 0 08 Jan 2025
DQRM: Deep Quantized Recommendation Models Yang Zhou Zhen Dong Ellick Chan Dhiraj Kalamkar Diana Marculescu Kurt Keutzer MQ 102 1 0 26 Oct 2024
GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs Vipul Gupta Xin Chen Ruoyun Huang Fanlong Meng Jianjun Chen Yujun Yan GNN 66 2 0 22 Jul 2024
Activations and Gradients Compression for Model-Parallel Training Mikhail Rudakov Aleksandr Beznosikov Yaroslav Kholodov Alexander Gasnikov 80 2 0 15 Jan 2024
Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training Ngoc-Hieu Nguyen Tuan Nguyen Tuan Nguyen Vu Tien Hoang Dung D. Le Kok-Seng Wong FedML 50 11 0 08 Jan 2024
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation Samuel Hsia Udit Gupta Bilge Acun Newsha Ardalani Pan Zhong Gu-Yeon Wei David Brooks Carole-Jean Wu 108 17 0 21 Feb 2023
A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models Yingcan Wei Matthias Langer F. Yu Minseok Lee Kingsley Liu Ji Shi Zehuan Wang BDL 54 18 0 17 Oct 2022
Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference Zehuan Wang Yingcan Wei Minseok Lee Matthias Langer F. Yu ... Daniel G. Abel Xu Guo Jianbing Dong Ji Shi Kunlun Li GNN LRM 48 33 0 17 Oct 2022
BagPipe: Accelerating Deep Recommendation Model Training Saurabh Agarwal Chengpo Yan Ziyi Zhang Shivaram Venkataraman 95 20 0 24 Feb 2022
Click-Through Rate Prediction in Online Advertising: A Literature Review Yanwu Yang Panyu Zhai CML 3DV 116 100 0 22 Feb 2022
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT Yashas Malur Saidutta Afshin Abdi Faramarz Fekri AI4CE 53 4 0 24 Jan 2022
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance Udit Gupta Samuel Hsia J. Zhang Mark Wilkening Javin Pombra Hsien-Hsin S. Lee Gu-Yeon Wei Carole-Jean Wu David Brooks 60 33 0 18 May 2021
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop Shitao Xiao Zheng Liu Yingxia Shao Tao Di Xing Xie VLM AIFin 186 42 0 18 Feb 2021