Global Built-In Self-Repair for 3D memories with redundancy sharing and parallel testing. - Xiaodong Wang 020; Dilip P. Vasudevan; Hsien-Hsin S. Lee (3DIC, 2011)

Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective. - Kim M. Hazelwood; Sarah Bird; David M. Brooks; Soumith Chintala; Utku Diril; Dmytro Dzhulgakov; Mohamed Fawzy; Bill Jia; Yangqing Jia; Aditya Kalro; James Law; Kevin Lee; et al. (HPCA, 2018)

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications. - Jongsoo Park; Maxim Naumov; Protonu Basu; Summer Deng; Aravind Kalaiah; Daya Shanker Khudia; James Law; Parth Malani; Andrey Malevich; Nadathur Satish; Juan Miguel Pino; Martin Schatz; et al. (CoRR, 2018)

Machine Learning at Facebook: Understanding Inference at the Edge. - Carole-Jean Wu; David Brooks 001; Kevin Chen; Douglas Chen; Sy Choudhury; Marat Dukhan; Kim M. Hazelwood; Eldad Isaac; Yangqing Jia; Bill Jia; Tommer Leyvand; Hao Lu; et al. (HPCA, 2019)

Deep Learning Recommendation Model for Personalization and Recommendation Systems. - Maxim Naumov; Dheevatsa Mudigere; Hao-Jun Michael Shi; Jianyu Huang; Narayanan Sundaraman; Jongsoo Park; Xiaodong Wang 020; Udit Gupta; Carole-Jean Wu; Alisson G. Azzolini; Dmytro Dzhulgakov; Andrey Mallevich; et al. (CoRR, 2019)

The Architectural Implications of Facebook's DNN-based Personalized Recommendation. - Udit Gupta; Xiaodong Wang 020; Maxim Naumov; Carole-Jean Wu; Brandon Reagen; David Brooks 001; Bradford Cottel; Kim M. Hazelwood; Bill Jia; Hsien-Hsin S. Lee; Andrey Malevich; Dheevatsa Mudigere; et al. (CoRR, 2019)

GEVO-ML: a proposal for optimizing ML code with evolutionary computation. - Jhe-Yu Liou; Xiaodong Wang 020; Stephanie Forrest; Carole-Jean Wu (GECCO Companion, 2020)

The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. - Udit Gupta; Carole-Jean Wu; Xiaodong Wang 020; Maxim Naumov; Brandon Reagen; David Brooks 001; Bradford Cottel; Kim M. Hazelwood; Mark Hempstead; Bill Jia; Hsien-Hsin S. Lee; Andrey Malevich; et al. (HPCA, 2020)

DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference. - Udit Gupta; Samuel Hsia; Vikram Saraph; Xiaodong Wang 020; Brandon Reagen; Gu-Yeon Wei; Hsien-Hsin S. Lee; David Brooks 001; Carole-Jean Wu (ISCA, 2020)

RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. - Liu Ke 001; Udit Gupta; Benjamin Youngjae Cho; David Brooks 001; Vikas Chandra; Utku Diril; Amin Firoozshahian; Kim M. Hazelwood; Bill Jia; Hsien-Hsin S. Lee; Meng Li 004; Bert Maher; et al. (ISCA, 2020)

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems. - Maxim Naumov; John Kim 001; Dheevatsa Mudigere; Srinivas Sridharan 002; Xiaodong Wang 020; Whitney Zhao; Serhat Yilmaz; Changkyu Kim; Hector Yuen; Mustafa Ozdal; Krishnakumar Nair; Isabel Gao; et al. (CoRR, 2020)

GEVO: GPU Code Optimization Using Evolutionary Computation. - Jhe-Yu Liou; Xiaodong Wang 020; Stephanie Forrest; Carole-Jean Wu (ACM Trans. Archit. Code Optim., 2020)

Understanding Training Efficiency of Deep Learning Recommendation Models at Scale. - Bilge Acun; Matthew Murphy; Xiaodong Wang 020; Jade Nie; Carole-Jean Wu; Kim M. Hazelwood (HPCA, 2021)

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Andrew Tulloch; Srinivas Sridharan 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; Leon Gao; et al. (CoRR, 2021)

Exploiting Parallelism Opportunities with Deep Learning Frameworks. - Yu Emma Wang; Carole-Jean Wu; Xiaodong Wang 020; Kim M. Hazelwood; David Brooks 001 (ACM Trans. Archit. Code Optim., 2021)

Software-hardware co-design for fast and scalable training of deep learning recommendation models. - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Zhihao Jia; Andrew Tulloch; Srinivas Sridharan 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; et al. (ISCA, 2022)

Scaling Llama 3 Training with Efficient Parallelism Strategies. - Weiwei Chu; Xinfeng Xie; Jiecao Yu; Jie Wang 022; Amar Phanishayee; Chunqiang Tang; Yuchen Hao; Jianyu Huang; Mustafa Ozdal; Jun Wang; Vedanuj Goswami; Naman Goyal 001; et al. (ISCA, 2025)