Dheevatsa Mudigere - researchr alias

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Viewing Publication 1 - 24 from 24

2023

TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training JobsWeiyang Wang, Moein Khazraee, Zhizhen Zhong, Manya Ghobadi, Zhihao Jia, Dheevatsa Mudigere, Ying Zhang 0022, Anthony Kewitsch. NSDI 2023: 739-767 [doi]

2022

Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation ModelsAssaf Eisenman, Kiran Kumar Matam, Steven Ingram, Dheevatsa Mudigere, Raghuraman Krishnamoorthi, Krishnakumar Nair, Misha Smelyanskiy, Murali Annavaram. NSDI 2022: 929-943 [doi]

Software-hardware co-design for fast and scalable training of deep learning recommendation modelsDheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, Andrew Tulloch, Srinivas Sridharan 0002, 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 0020, 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, Dimitry Melts, Krishna Dhulipala, K. R. Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao. isca 2022: 993-1011 [doi]

Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and ParallelizationColin Unger, Zhihao Jia, Wei Wu 0016, Sina Lin, Mandeep Baines, Carlos Efrain Quintero Narvaez, Vinay Ramakrishnaiah, Nirmal Prajapati, Patrick S. McCormick, Jamaludin Mohd-Yusof, Xi Luo, Dheevatsa Mudigere, JongSoo Park, Misha Smelyanskiy, Alex Aiken. osdi 2022: 267-284 [doi]

EL-Rec: Efficient Large-Scale Recommendation Model Training via Tensor-Train Embedding TableZheng Wang, Yuke Wang, Boyuan Feng, Dheevatsa Mudigere, Bharath Muthiah, Yufei Ding. sc 2022: 1-14 [doi]

2021

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation SystemsAntonio A. Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou. isit 2021: 2786-2791 [doi]

SEERL: Sample Efficient Ensemble Reinforcement LearningRohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul. atal 2021: 1100-1108 [doi]

2020

The Architectural Implications of Facebook's DNN-Based Personalized RecommendationUdit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks 0001, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang 0001. hpca 2020: 488-501 [doi]

Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample StrategyMajid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takác. aistats 2020: 2634-2644 [doi]

Building Recommender Systems with PyTorchDheevatsa Mudigere, Maxim Naumov, Joe Spisak, Geeta Chauhan, Narine Kokhlikyan, Amanpreet Singh, Vedanuj Goswami. kdd 2020: 3525-3526 [doi]

Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transportSaeed Rashidi, Pallavi Shurpali, Srinivas Sridharan 0002, Naader Hassani, Dheevatsa Mudigere, Krishnakumar Nair, Misha Smelyanski, Tushar Krishna. hoti 2020: 33-42 [doi]

ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract)Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul. AAAI 2020: 13905-13906 [doi]

Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation SystemsHao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang. kdd 2020: 165-175 [doi]

2018

2017

Distributed Hessian-Free Optimization for Deep Neural NetworkXi He, Dheevatsa Mudigere, Mikhail Smelyanskiy, Martin Takác. AAAI 2017: [doi]

On Large-Batch Training for Deep Learning: Generalization Gap and Sharp MinimaNitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang. iclr 2017: [doi]

2015

2011

Nature inspired optimization techniques for the design optimization of laminated composite structures using failure criteriaG. Narayana Naik, S. N. Omkar, Dheevatsa Mudigere, S. Gopalakrishnan. eswa, 38(3):2489-2499, 2011. [doi]

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