Xiaodong Wang

According to our database, Xiaodong Wang authored at least 17 papers between 2011 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Scaling Llama 3 Training with Efficient Parallelism Strategies.

Weiwei Chu, Xinfeng Xie, Jiecao Yu, Jie Wang, Amar Phanishayee, Chunqiang Tang, Yuchen Hao, Jianyu Huang, Mustafa Ozdal, Jun Wang, Vedanuj Goswami, Naman Goyal, Abhishek Kadian, Andrew Gu, Chris Cai, Feng Tian, Xiaodong Wang, Min Si, Pavan Balaji, Ching-Hsiang Chu, Jongsoo Park

Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

2022

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, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

2021

Exploiting Parallelism Opportunities with Deep Learning Frameworks.

Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim M. Hazelwood, David Brooks

ACM Trans. Archit. Code Optim., 2021

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.

Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao

CoRR, 2021

Understanding Training Efficiency of Deep Learning Recommendation Models at Scale.

Bilge Acun, Matthew Murphy, Xiaodong Wang, Jade Nie, Carole-Jean Wu, Kim M. Hazelwood

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2021

2020

GEVO: GPU Code Optimization Using Evolutionary Computation.

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

ACM Trans. Archit. Code Optim., 2020

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems.

Maxim Naumov, John Kim, Dheevatsa Mudigere, Srinivas Sridharan, Xiaodong Wang, Whitney Zhao, Serhat Yilmaz, Changkyu Kim, Hector Yuen, Mustafa Ozdal, Krishnakumar Nair, Isabel Gao, Bor-Yiing Su, Jiyan Yang, Mikhail Smelyanskiy

CoRR, 2020

RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.

Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang, Brandon Reagen, Carole-Jean Wu, Mark Hempstead, Xuan Zhang

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference.

Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

The Architectural Implications of Facebook's DNN-Based Personalized Recommendation.

Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2020

GEVO-ML: a proposal for optimizing ML code with evolutionary computation.

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

The Architectural Implications of Facebook's DNN-based Personalized Recommendation.

Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang

CoRR, 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, Udit Gupta, Carole-Jean Wu, Alisson G. Azzolini, Dmytro Dzhulgakov, Andrey Mallevich, Ilia Cherniavskii, Yinghai Lu, Raghuraman Krishnamoorthi, Ansha Yu, Volodymyr Kondratenko, Stephanie Pereira, Xianjie Chen, Wenlin Chen, Vijay Rao, Bill Jia, Liang Xiong, Misha Smelyanskiy

CoRR, 2019

Machine Learning at Facebook: Understanding Inference at the Edge.

Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim M. Hazelwood, Eldad Isaac, Yangqing Jia, Bill Jia, Tommer Leyvand, Hao Lu, Yang Lu, Lin Qiao, Brandon Reagen, Joe Spisak, Fei Sun, Andrew Tulloch, Peter Vajda, Xiaodong Wang, Yanghan Wang, Bram Wasti, Yiming Wu, Ran Xian, Sungjoo Yoo, Peizhao Zhang

Proceedings of the 25th IEEE International Symposium on High Performance Computer Architecture, 2019

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, Alexander Sidorov, Viswanath Sivakumar, Andrew Tulloch, Xiaodong Wang, Yiming Wu, Hector Yuen, Utku Diril, Dmytro Dzhulgakov, Kim M. Hazelwood, Bill Jia, Yangqing Jia, Lin Qiao, Vijay Rao, Nadav Rotem, Sungjoo Yoo, Mikhail Smelyanskiy

CoRR, 2018

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, Jason Lu, Pieter Noordhuis, Misha Smelyanskiy, Liang Xiong, Xiaodong Wang

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2018

2011

Global Built-In Self-Repair for 3D memories with redundancy sharing and parallel testing.

Xiaodong Wang, Dilip P. Vasudevan, Hsien-Hsin S. Lee

Proceedings of the 2011 IEEE International 3D Systems Integration Conference (3DIC), Osaka, Japan, January 31, 2011