An energy efficient cache design using spin torque transfer (STT) RAM. - Mitchelle Rasquinha; Dhruv Choudhary; Subho Chatterjee; Saibal Mukhopadhyay; Sudhakar Yalamanchili (ISLPED, 2010)

Regulating Locality vs. Parallelism Tradeoffs in Multiple Memory Controller Environments. - Syed Minhaj Hassan; Dhruv Choudhary; Mitchelle Rasquinha; Sudhakar Yalamanchili (PACT, 2011)

On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data. - Dhruv Choudhary; Arun Kejariwal; Francois Orsini (CoRR, 2017)

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. - Mao Ye 006; Dhruv Choudhary; Jiecao Yu; Ellie Wen; Zeliang Chen; Jiyan Yang; Jongsoo Park; Qiang Liu 001; Arun Kejariwal (CoRR, 2020)

Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. - Vipul Gupta; Dhruv Choudhary; Ping Tak Peter Tang; Xiaohan Wei; Xing Wang; Yuzhen Huang; Arun Kejariwal; Kannan Ramchandran; Michael W. Mahoney (CoRR, 2020)

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. - Xiaocong Du; Bhargav Bhushanam; Jiecao Yu; Dhruv Choudhary; Tianxiang Gao; Sherman Wong; Louis Feng; Jongsoo Park; Yu Cao 001; Arun Kejariwal (ICMLA, 2021)

Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. - Vipul Gupta; Dhruv Choudhary; Ping Tak Peter Tang; Xiaohan Wei; Xing Wang; Yuzhen Huang; Arun Kejariwal; Kannan Ramchandran; Michael W. Mahoney (KDD, 2021)

Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. - Yuzhen Huang; Xiaohan Wei; Xing Wang; Jiyan Yang; Bor-Yiing Su; Shivam Bharuka; Dhruv Choudhary; Zewei Jiang; Hai Zheng; Jack Langman (KDD, 2021)

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. - Zhaoxia Deng; Jongsoo Park; Ping Tak Peter Tang; Haixin Liu; Jie Yang; Hector Yuen; Jianyu Huang; Daya Shanker Khudia; Xiaohan Wei; Ellie Wen; Dhruv Choudhary; Raghuraman Krishnamoorthi; et al. (IEEE Micro, 2021)

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. - Yan Li 074; Dhruv Choudhary; Xiaohan Wei; Baichuan Yuan; Bhargav Bhushanam; Tuo Zhao; Guanghui Lan (ICLR, 2022)

AutoShard: Automated Embedding Table Sharding for Recommender Systems. - Daochen Zha; Louis Feng; Bhargav Bhushanam; Dhruv Choudhary; Jade Nie; Yuandong Tian; Jay Chae; Yinbin Ma; Arun Kejariwal; Xia Hu 001 (KDD, 2022)

Harmless Transfer Learning for Item Embeddings. - Chengyue Gong; Xiaocong Du; Dhruv Choudhary; Bhargav Bhushanam; Qiang Liu 001; Arun Kejariwal (NAACL-HLT (Findings), 2022)

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. - Mao Ye 006; Ruichen Jiang; Haoxiang Wang 003; Dhruv Choudhary; Xiaocong Du; Bhargav Bhushanam; Aryan Mokhtari; Arun Kejariwal; Qiang Liu 001 (UAI, 2022)

Positive Unlabeled Contrastive Learning. - Anish Acharya; Sujay Sanghavi; Li Jing 001; Bhargav Bhushanam; Dhruv Choudhary; Michael G. Rabbat; Inderjit S. Dhillon (CoRR, 2022)

RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. - Mark Zhao; Dhruv Choudhary; Devashish Tyagi; Ajay Somani; Max Kaplan; Sung-Han Lin; Sarunya Pumma; Jongsoo Park; Aarti Basant; Niket Agarwal; Carole-Jean Wu; Christos Kozyrakis (MLSys, 2023)

FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models. - Geet Sethi; Pallab Bhattacharya; Dhruv Choudhary; Carole-Jean Wu; Christos Kozyrakis (CoRR, 2023)

Microscaling Data Formats for Deep Learning. - Bita Darvish Rouhani; Ritchie Zhao; Ankit More; Mathew Hall; Alireza Khodamoradi; Summer Deng; Dhruv Choudhary; Marius Cornea; Eric Dellinger; Kristof Denolf; Dusan Stosic; Venmugil Elango; et al. (CoRR, 2023)

Layer Compression of Deep Networks with Straight Flows. - Chengyue Gong; Xiaocong Du; Bhargav Bhushanam; Lemeng Wu; Xingchao Liu; Dhruv Choudhary; Arun Kejariwal; Qiang Liu 001 (AAAI, 2024)

The Llama 3 Herd of Models. - Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Ahmad Al-Dahle; Aiesha Letman; Akhil Mathur; Alan Schelten; Amy Yang; Angela Fan; Anirudh Goyal; Anthony Hartshorn; et al. (CoRR, 2024)

Movie Gen: A Cast of Media Foundation Models. - Adam Polyak; Amit Zohar; Andrew Brown; Andros Tjandra; Animesh Sinha; Ann Lee 001; Apoorv Vyas; Bowen Shi; Chih-Yao Ma; Ching-Yao Chuang; David Yan; Dhruv Choudhary; et al. (CoRR, 2024)

SpinQuant: LLM Quantization with Learned Rotations. - Zechun Liu; Changsheng Zhao 002; Igor Fedorov; Bilge Soran; Dhruv Choudhary; Raghuraman Krishnamoorthi; Vikas Chandra; Yuandong Tian; Tijmen Blankevoort (ICLR, 2025)

Accelerating Transformer Inference and Training with 2:4 Activation Sparsity. - Daniel Haziza; Timothy Chou; Dhruv Choudhary; Luca Wehrstedt; Francisco Massa; Jiecao Yu; Geonhwa Jeong; Supriya Rao; Patrick Labatut; Jesse Cai (CoRR, 2025)