Maxim Naumov joined Facebook in January 2018. His interests include deep learning, parallel algorithms and numerical methods. In the past, he held different positions at Nvidia Research, Emerging Applications and Platform teams. He has also worked at Intel Corporation Microprocessor Technology and Computational Software Labs. Maxim received his PhD in computer science (with specialization in computational science and engineering) in 2009 and BS in computer science and mathematics in 2003 from Purdue University – West Lafayette. He was awarded the 2008-09 Intel Foundation PhD Fellowship during his graduate studies.
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
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
Jongsoo Park, Maxim Naumov, Protonu Basu, Summer Deng, Aravind Kalaiah, Daya Khudia, James Law, Parth Malani, Andrey Malevich, Satish Nadathur, Juan Pino, Martin Schatz, Alexander Sidorov, Viswanath Sivakumar, Andrew Tulloch, Xiaodong Wang, Yiming Wu, Hector Yuen, Utku Diril, Dmytro Dzhulgakov, Kim Hazelwood, Bill Jia, Yangqing Jia, Lin Qiao, Vijay Rao, Nadav Rotem, Sungjoo Yoo, Mikhail Smelyanskiy
ArXiv - November 24, 2018