Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Dheevatsa Mudigere

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


Apr 13, 2021
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, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Pallab Bhattacharya, Guoqiang Jerry Chen, Manoj Krishnan, Krishnakumar Nair, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao


  Access Paper or Ask Questions

Check-N-Run: A Checkpointing System for Training Recommendation Models


Oct 17, 2020
Assaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Murali Annavaram, Krishnakumar Nair, Misha Smelyanskiy


  Access Paper or Ask Questions

SEERL: Sample Efficient Ensemble Reinforcement Learning


Jan 15, 2020
Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul


  Access Paper or Ask Questions

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems


Sep 25, 2019
Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou


  Access Paper or Ask Questions

Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems


Sep 04, 2019
Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang

* 20 pages, 11 figures, 4 tables 

  Access Paper or Ask Questions

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


Jun 18, 2019
Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang

* 11 pages 

  Access Paper or Ask Questions

A Study of BFLOAT16 for Deep Learning Training


Jun 13, 2019
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey


  Access Paper or Ask Questions

Deep Learning Recommendation Model for Personalization and Recommendation Systems


May 31, 2019
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

* 10 pages, 6 figures 

  Access Paper or Ask Questions

Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy


Oct 26, 2018
Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takáč


  Access Paper or Ask Questions

A Progressive Batching L-BFGS Method for Machine Learning


May 30, 2018
Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang

* ICML 2018. 25 pages, 17 figures, 2 tables 

  Access Paper or Ask Questions

Mixed Precision Training of Convolutional Neural Networks using Integer Operations


Feb 23, 2018
Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesus Corbal, Nikita Shustrov, Roma Dubtsov, Evarist Fomenko, Vadim Pirogov

* Published as a conference paper at ICLR 2018 

  Access Paper or Ask Questions

On Scale-out Deep Learning Training for Cloud and HPC


Jan 24, 2018
Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey

* Accepted in SysML 2018 conference 

  Access Paper or Ask Questions

RAIL: Risk-Averse Imitation Learning


Nov 29, 2017
Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul

* Accepted for presentation in Deep Reinforcement Learning Symposium at NIPS 2017 

  Access Paper or Ask Questions

Ternary Residual Networks


Oct 31, 2017
Abhisek Kundu, Kunal Banerjee, Naveen Mellempudi, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey


  Access Paper or Ask Questions

Ternary Neural Networks with Fine-Grained Quantization


May 30, 2017
Naveen Mellempudi, Abhisek Kundu, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey


  Access Paper or Ask Questions

On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima


Feb 09, 2017
Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang

* Accepted as a conference paper at ICLR 2017 

  Access Paper or Ask Questions

Mixed Low-precision Deep Learning Inference using Dynamic Fixed Point


Feb 01, 2017
Naveen Mellempudi, Abhisek Kundu, Dipankar Das, Dheevatsa Mudigere, Bharat Kaul


  Access Paper or Ask Questions

Distributed Hessian-Free Optimization for Deep Neural Network


Jan 15, 2017
Xi He, Dheevatsa Mudigere, Mikhail Smelyanskiy, Martin Takáč


  Access Paper or Ask Questions

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent


Feb 22, 2016
Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidynathan, Srinivas Sridharan, Dhiraj Kalamkar, Bharat Kaul, Pradeep Dubey


  Access Paper or Ask Questions

Identification of Helicopter Dynamics based on Flight Data using Nature Inspired Techniques


Nov 12, 2014
S. N. Omkar, Dheevatsa Mudigere, J Senthilnath, M. Vijaya Kumar


  Access Paper or Ask Questions