I’m a research scientist on the AI System SW/HW Co-design team at Facebook Infra’s Technology Strategy group. My research focuses on systems design at large scale, parallel algorithms and high-performance computing. Formerly, I have held research positions at the Parallel Computing Lab in Intel Labs and GE global research. I’m a mechanical engineer by training and have a master’s degree in applied mathematics and computational science from the TU Munich.
Interests
Deep learning, systems design, parallel algorithms, high performance computing, numerical methods
Latest Publications
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
arXiv - September 3, 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 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
ISCA - May 22, 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 Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
HPCA - February 17, 2020