Maxim Naumov

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.

Interests

Deep learning, parallel algorithms, numerical methods, high performance computing

Google Scholar Profile

Latest Publications

Bandana: Using Non-Volatile Memory for Storing Deep Learning Models

Assaf Eisenman, Maxim Naumov, Darryl Gardner, Misha Smelyanskiy, Sergey Pupyrev, Kim Hazelwood, Asaf Cidon, Sachin Katti

SysML - April 2, 2019

On the Dimensionality of Embeddings for Sparse Features and Data

Maxim Naumov

ArXiv - January 7, 2019

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

On Periodic Functions as Regularizers for Quantization of Neural Networks

Maxim Naumov, Utku Diril, Jongsoo Park, Benjamin Ray, Jedrzej Jablonski, Andrew Tulloch