Dheevatsa Mudigere

Research Scientist

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.


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