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

18 October 2020

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

7 / 7 papers shown

Title
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 51 5 0 08 Jan 2025
GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs Vipul Gupta Xin Chen Ruoyun Huang Fanlong Meng Jianjun Chen Yujun Yan GNN 41 0 0 22 Jul 2024
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 25 32 0 17 Oct 2022
BagPipe: Accelerating Deep Recommendation Model Training Saurabh Agarwal Chengpo Yan Ziyi Zhang Shivaram Venkataraman 37 18 0 24 Feb 2022
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT Yashas Malur Saidutta Afshin Abdi Faramarz Fekri AI4CE 38 4 0 24 Jan 2022
Training Large-Scale News Recommenders with Pretrained Language Models in the Loop Shitao Xiao Zheng Liu Yingxia Shao Tao Di Xing Xie VLM AIFin 127 41 0 18 Feb 2021
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 312 2,896 0 15 Sep 2016