A Frequency-aware Software Cache for Large Recommendation System Embeddings

The netflix recommender system: Algorithms, business value, and innovation

Carlos A Gomez-Uribe and Neil Hunt. 2015 · 2015

Earlier work this paper cites.

Two decades of recommender systems at Amazon. com

Original

Brent Smith and Greg Linden. 2017 · 2017

Earlier work this paper cites.

Deep learning recommendation model for personalization and recommendation systems

Original

Maxim Naumov, Dheevatsa Mudigere, Hao-Jun Michael Shi, Jianyu Huang, Narayanan Sundaraman, Jongsoo Park, Xiaodong Wang, Udit Gupta, Carole-Jean Wu, Alisson G Azzolini, et al · 2019

Earlier work this paper cites.

Accelerating recommendation system training by leveraging popular choices

Original

Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, and Prashant J Nair. 2021 · 2021

Earlier work this paper cites.

Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training

Original

Zhengda Bian, Hongxin Liu, Boxiang Wang, Haichen Huang, Yongbin Li, Chuanrui Wang, Fan Cui, and Yang You. 2021 · 2021

Cited alongside, same era.

Mixed dimension embeddings with application to memory-efficient recommendation systems. In 2021 IEEE International Symposium on Information Theory (ISIT) . IEEE, 2786–2791

Antonio A Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, and James Zou. 2021 · 2021

Cited alongside, same era.

Persia: a hybrid system scaling deep learning based recommenders up to 100 trillion parameters

Original

Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, et al · 2021

Cited alongside, same era.

Het: Scaling out huge embedding model training via cache-enabled distributed framework

Original

Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, and Bin Cui. 2021 · 2021

Later among the works it cites.

Heterogeneous Acceleration Pipeline for Recommendation System Training

Original

Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, and Prashant J Nair. 2022 · 2022

Closest in time.

Software-hardware co-design for fast and scalable training of deep learning recommendation models. In Proceedings of the 49th Annual International Symposium on Computer Architecture . 993–1011

Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, et al · 2022

Closest in time.