BagPipe: Accelerating Deep Recommendation Model Training

BagPipe: Accelerating Deep Recommendation Model Training

24 February 2022

Saurabh Agarwal

Shivaram Venkataraman

Papers citing "BagPipe: Accelerating Deep Recommendation Model Training"

6 / 6 papers shown

Title
MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage Yongjun He R. Waleffe Zhichao Han Johnu George Binhang Yuan ... Yinan Shan Yang Zhao Debojyoti Dutta Theodoros Rekatsinas Ce Zhang AIFin 33 0 0 02 Apr 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 39 0 0 01 Apr 2025
Stochastic Communication Avoidance for Recommendation Systems Lutfi Eren Erdogan Vijay Anand Raghava Kanakagiri Kurt Keutzer Zhen Dong 64 1 0 03 Nov 2024
Heterogeneous Acceleration Pipeline for Recommendation System Training Muhammad Adnan Yassaman Ebrahimzadeh Maboud Divyat Mahajan Prashant J. Nair 21 18 0 11 Apr 2022
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 168 564 0 27 Jul 2020
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing Liu Ke Udit Gupta Carole-Jean Wu B. Cho Mark Hempstead ... Dheevatsa Mudigere Maxim Naumov Martin D. Schatz M. Smelyanskiy Xiaodong Wang 41 212 0 30 Dec 2019