Udit Gupta

61 papers A* 16A 4B 1Journal 29Unranked 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
COFFEE: A Carbon-Modeling and Optimization Framework for HZO-based FeFET eNVMs.
CoRR
Hongbang Wu, Xuesi Chen, Shubham Jadhav, Amit Lal, Lillian Pentecost, Udit Gupta
2025 J jnl
A view of the sustainable computing landscape.
Patterns
Benjamin C. Lee, David Brooks, Arthur van Benthem, Mariam Elgamal, Udit Gupta, Gage Hills, Vincent Liu, Linh Thi Xuan Phan, Benjamin Pierce, Christopher Stewart, Emma Strubell, Gu-Yeon Wei, Adam Wierman, Yuan Yao, Minlan Yu
2025 J jnl
Accelerating Diffusion Language Model Inference via Efficient KV Caching and Guided Diffusion.
CoRR
Zhanqiu Hu, Jian Meng, Yash Akhauri, Mohamed S. Abdelfattah, Jae-sun Seo, Zhiru Zhang, Udit Gupta
2025 A* conf
CORDOBA: Carbon-Efficient Optimization Framework for Computing Systems.
HPCA
Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu
2025 A conf
CarbonClarity: Understanding and Addressing Uncertainty in Embodied Carbon for Sustainable Computing.
ICCAD
Xuesi Chen, Leo Han, Anvita Bhagavathula, Udit Gupta
2025 J jnl
EcoServe: Designing Carbon-Aware AI Inference Systems.
CoRR
Yueying Li, Zhanqiu Hu, Esha Choukse, Rodrigo Fonseca, G. Edward Suh, Udit Gupta
2025 J jnl
Empowering Users to Make Sustainability-Forward Decisions for Computing Services.
Commun. ACM
Sydney Young, Udit Gupta, Josiah D. Hester
2025 A* conf
Fair-CO2: Fair Attribution for Cloud Carbon Emissions.
ISCA
Leo Han, Jash Kakadia, Benjamin C. Lee, Udit Gupta
2025 J jnl
GreenScale: Carbon Optimization for Edge Computing.
IEEE Internet Things J.
Yonglak Son, Udit Gupta, Andrew McCrabb, Young-geun Kim, Valeria Bertacco, David Brooks, Carole-Jean Wu
2025 A* conf
Hermes: Algorithm-System Co-design for Efficient Retrieval-Augmented Generation At-Scale.
ISCA
Michael Shen, Muhammad Umar, Kiwan Maeng, G. Edward Suh, Udit Gupta
2025 A conf
Silicon Foraging: Harvesting Excess Compute for Sustainable Edge Computing.
Conference on Designing Interactive Systems
Ilan Mandel, Udit Gupta
2025 J jnl
Slower is Greener: Acceptance of Eco-feedback Interventions on Carbon Heavy Internet Services.
ACM J. Comput. Sustain. Soc.
Hyeonwook Kim, Sydney Young, Xuesi Chen, Udit Gupta, Josiah D. Hester
2024 A conf
3D IC Architecture Evaluation and Optimization with Digital Compute-in-Memory Designs.
ISLPED
Hyung Joon Byun, Udit Gupta, Jae-sun Seo
2024 J jnl
Carbon Connect: An Ecosystem for Sustainable Computing.
CoRR
Benjamin C. Lee, David Brooks, Arthur van Benthem, Udit Gupta, Gage Hills, Vincent Liu, Benjamin Pierce, Christopher Stewart, Emma Strubell, Gu-Yeon Wei, Adam Wierman, Yuan Yao, Minlan Yu
2024 — conf
GPU-based Private Information Retrieval for On-Device Machine Learning Inference.
ASPLOS (1)
Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh
2024 A* conf
Information Flow Control in Machine Learning through Modular Model Architecture.
USENIX Security Symposium
Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2024 J jnl
Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference.
CoRR
Michael Shen, Muhammad Umar, Kiwan Maeng, G. Edward Suh, Udit Gupta
2023 J jnl
Architectural CO
IEEE Micro
Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2023 — conf
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters.
ASPLOS (2)
Bilge Acun, Benjamin C. Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta, Manoj Chakkaravarthy, David Brooks, Carole-Jean Wu
2023 — conf
Carbon-Efficient Design Optimization for Computing Systems.
HotCarbon
Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu
2023 J jnl
Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems.
CoRR
Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu
2023 J jnl
GPU-based Private Information Retrieval for On-Device Machine Learning Inference.
CoRR
Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh
2023 J jnl
GreenScale: Carbon-Aware Systems for Edge Computing.
CoRR
Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, Carole-Jean Wu
2023 J jnl
Information Flow Control in Machine Learning through Modular Model Architecture.
CoRR
Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh
2023 J jnl
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation.
CoRR
Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
2023 — conf
MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation.
ASPLOS (3)
Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
2023 — conf
Peeling Back the Carbon Curtain: Carbon Optimization Challenges in Cloud Computing.
HotCarbon
Jaylen Wang, Udit Gupta, Akshitha Sriraman
2022 J jnl
A Holistic Approach for Designing Carbon Aware Datacenters.
CoRR
Bilge Acun, Benjamin C. Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
2022 A* conf
ACT: designing sustainable computer systems with an architectural carbon modeling tool.
ISCA
Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2022 J jnl
Chasing Carbon: The Elusive Environmental Footprint of Computing.
IEEE Micro
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
2022 A* conf
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation.
HPCA
Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
2022 J jnl
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation.
CoRR
Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang
2022 — conf
Sustainable AI: Environmental Implications, Challenges and Opportunities.
MLSys
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin C. Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood
2021 A* conf
Chasing Carbon: The Elusive Environmental Footprint of Computing.
HPCA
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
2021 A* conf
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance.
MICRO
Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin Sean Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
2021 J jnl
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance.
CoRR
Udit Gupta, Samuel Hsia, Jeff Jun Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
2021 J jnl
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference.
CoRR
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei
2021 A* conf
RecSSD: near data processing for solid state drive based recommendation inference.
ASPLOS
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei
2021 J jnl
Sustainable AI: Environmental Implications, Challenges and Opportunities.
CoRR
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin C. Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood
2020 J jnl
Chasing Carbon: The Elusive Environmental Footprint of Computing.
CoRR
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
2020 — conf
Cross-Stack Workload Characterization of Deep Recommendation Systems.
IISWC
Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks
2020 J jnl
Cross-Stack Workload Characterization of Deep Recommendation Systems.
CoRR
Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks
2020 A* conf
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference.
ISCA
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2020 J jnl
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference.
CoRR
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2020 A conf
Emerging Neural Workloads and Their Impact on Hardware.
DATE
David Brooks, Martin M. Frank, Tayfun Gokmen, Udit Gupta, Xiaobo Sharon Hu, Shubham Jain, Ann Franchesca Laguna, Michael T. Niemier, Ian O'Connor, Anand Raghunathan, Ashish Ranjan, Dayane Reis, Jacob R. Stevens, Carole-Jean Wu, Xunzhao Yin
2020 — conf
MLPerf Training Benchmark.
MLSys
Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia
2020 A* conf
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.
ISCA
Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang, Brandon Reagen, Carole-Jean Wu, Mark Hempstead, Xuan Zhang
2020 A* conf
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation.
HPCA
Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
2019 — conf
A 16nm 25mm
VLSI Circuits
Paul N. Whatmough, Sae Kyu Lee, Marco Donato, Hsea-Ching Hsueh, Sam Likun Xi, Udit Gupta, Lillian Pentecost, Glenn G. Ko, David M. Brooks, Gu-Yeon Wei
2019 — conf
CHAMPVis: Comparative Hierarchical Analysis of Microarchitectural Performance.
ProTools@SC
Lillian Pentecost, Udit Gupta, Elisa Ngan, Johanna Beyer, Gu-Yeon Wei, David Brooks, Michael Behrisch
2019 J jnl
Deep Learning Recommendation Model for Personalization and Recommendation Systems.
CoRR
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
2019 B conf
MASR: A Modular Accelerator for Sparse RNNs.
PACT
Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2019 J jnl
MLPerf Training Benchmark.
CoRR
Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia
2019 A* conf
MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation.
MICRO
Lillian Pentecost, Marco Donato, Brandon Reagen, Udit Gupta, Siming Ma, Gu-Yeon Wei, David Brooks
2019 J jnl
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.
CoRR
Liu Ke, Udit Gupta, Carole-Jean Wu, Benjamin Youngjae Cho, Mark Hempstead, Brandon Reagen, Xuan Zhang, David M. Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang
2019 J jnl
The Architectural Implications of Facebook's DNN-based Personalized Recommendation.
CoRR
Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
2018 A* conf
Ares: a framework for quantifying the resilience of deep neural networks.
DAC
Brandon Reagen, Udit Gupta, Lillian Pentecost, Paul N. Whatmough, Sae Kyu Lee, Niamh Mulholland, David M. Brooks, Gu-Yeon Wei
2018 A* conf
On-chip deep neural network storage with multi-level eNVM.
DAC
Marco Donato, Brandon Reagen, Lillian Pentecost, Udit Gupta, David Brooks, Gu-Yeon Wei
2018 — conf
Weightless: Lossy weight encoding for deep neural network compression.
ICLR (Workshop)
Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2018 A* conf
Weightless: Lossy weight encoding for deep neural network compression.
ICML
Brandon Reagen, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2017 J jnl
Weightless: Lossy Weight Encoding For Deep Neural Network Compression.
CoRR
Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David M. Brooks