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Udit Gupta
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2020 – today
- 2024
- [c36]Maximilian Lam
, Jeff Johnson
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. ASPLOS (1) 2024: 197-214 - [c35]Hyung Joon Byun
3D IC Architecture Evaluation and Optimization with Digital Compute-in-Memory Designs. ISLPED 2024: 1-6 - [c34]Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh:
Information Flow Control in Machine Learning through Modular Model Architecture. USENIX Security Symposium 2024 - [i26]Farbin Fayza, Satyavolu Papa Rao, Darius Bunandar, Udit Gupta, Ajay Joshi:
Photonics for Sustainable Computing. CoRR abs/2401.05121 (2024) - [i25]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:
Carbon Connect: An Ecosystem for Sustainable Computing. CoRR abs/2405.13858 (2024) - 2023
- [j5]Udit Gupta
Architectural CO2 Footprint Tool: Designing Sustainable Computer Systems With an Architectural Carbon Modeling Tool. IEEE Micro 43(4): 107-117 (2023) - [c33]Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters. ASPLOS (2) 2023: 118-132 - [c32]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation. ASPLOS (3) 2023: 449-465 - [c31]Jaylen Wang
Peeling Back the Carbon Curtain: Carbon Optimization Challenges in Cloud Computing. HotCarbon 2023: 8:1-8:7 - [c30]Mariam Elgamal
Carbon-Efficient Design Optimization for Computing Systems. HotCarbon 2023: 16:1-16:7 - [i24]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:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. CoRR abs/2301.10904 (2023) - [i23]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation. CoRR abs/2302.10872 (2023) - [i22]Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, Carole-Jean Wu:
GreenScale: Carbon-Aware Systems for Edge Computing. CoRR abs/2304.00404 (2023) - [i21]Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu:
Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems. CoRR abs/2305.01831 (2023) - [i20]Trishita Tiwari, Suchin Gururangan, Chuan Guo, Weizhe Hua, Sanjay Kariyappa, Udit Gupta, Wenjie Xiong, Kiwan Maeng, Hsien-Hsin S. Lee, G. Edward Suh:
Information Flow Control in Machine Learning through Modular Model Architecture. CoRR abs/2306.03235 (2023) - [i19]Udit Gupta:
GPT-InvestAR: Enhancing Stock Investment Strategies through Annual Report Analysis with Large Language Models. CoRR abs/2309.03079 (2023) - 2022
- [j4]Udit Gupta
Chasing Carbon: The Elusive Environmental Footprint of Computing. IEEE Micro 42(4): 37-47 (2022) - [c29]Liu Ke, Udit Gupta, Mark Hempstead
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. HPCA 2022: 141-154 - [c28]Udit Gupta
ACT: designing sustainable computer systems with an architectural carbon modeling tool. ISCA 2022: 784-799 - [c27]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 Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. MLSys 2022 - [i18]Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu:
A Holistic Approach for Designing Carbon Aware Datacenters. CoRR abs/2201.10036 (2022) - [i17]Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin S. Lee, Xuan Zhang:
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation. CoRR abs/2203.07424 (2022) - 2021
- [j3]Udit Gupta
Learning Chemistry of Complex Reaction Systems via a Python First-Principles Reaction Rule Stencil (pReSt) Generator. J. Chem. Inf. Model. 61(7): 3431-3441 (2021) - [c26]Mark Wilkening, Udit Gupta
RecSSD: near data processing for solid state drive based recommendation inference. ASPLOS 2021: 717-729 - [c25]Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Chasing Carbon: The Elusive Environmental Footprint of Computing. HPCA 2021: 854-867 - [c24]Udit Gupta
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. MICRO 2021: 870-884 - [c23]Elba Garza, Gururaj Saileshwar, Udit Gupta, Tianyi Liu, Abdulrahman Mahmoud, Saugata Ghose, Joel S. Emer:
Mentoring Opportunities in Computer Architecture: Analyzing the Past to Develop the Future. WCAE 2021: 1-9 - [i16]Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei:
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference. CoRR abs/2102.00075 (2021) - [i15]Udit Gupta, Samuel Hsia, Jeff Jun Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks:
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. CoRR abs/2105.08820 (2021) - [i14]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 Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR abs/2111.00364 (2021) - 2020
- [j2]Udit Gupta
Reaction Network Viewer (ReNView): An open-source framework for reaction path visualization of chemical reaction systems. SoftwareX 11: 100442 (2020) - [c22]David Brooks, Martin M. Frank, Tayfun Gokmen, Udit Gupta, Xiaobo Sharon Hu
Emerging Neural Workloads and Their Impact on Hardware. DATE 2020: 1462-1471 - [c21]Udit Gupta
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. HPCA 2020: 488-501 - [c20]Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks:
Cross-Stack Workload Characterization of Deep Recommendation Systems. IISWC 2020: 157-168 - [c19]Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. ISCA 2020: 790-803 - [c18]Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu:
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference. ISCA 2020: 982-995 - [c17]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:
MLPerf Training Benchmark. MLSys 2020 - [i13]Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu:
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference. CoRR abs/2001.02772 (2020) - [i12]Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks:
Cross-Stack Workload Characterization of Deep Recommendation Systems. CoRR abs/2010.05037 (2020) - [i11]Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Chasing Carbon: The Elusive Environmental Footprint of Computing. CoRR abs/2011.02839 (2020)
2010 – 2019
- 2019
- [c16]Udit Gupta
MASR: A Modular Accelerator for Sparse RNNs. PACT 2019: 1-14 - [c15]Udit Gupta
Fast and Accurate Learning of Knowledge Graph Embeddings at Scale. HiPC 2019: 173-182 - [c14]Lillian Pentecost
MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation. MICRO 2019: 769-781 - [c13]Lillian Pentecost
CHAMPVis: Comparative Hierarchical Analysis of Microarchitectural Performance. ProTools@SC 2019: 55-61 - [c12]Paul N. Whatmough, Sae Kyu Lee, Marco Donato, Hsea-Ching Hsueh, Sam Likun Xi, Udit Gupta
A 16nm 25mm2 SoC with a 54.5x Flexibility-Efficiency Range from Dual-Core Arm Cortex-A53 to eFPGA and Cache-Coherent Accelerators. VLSI Circuits 2019: 34- - [i10]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:
Deep Learning Recommendation Model for Personalization and Recommendation Systems. CoRR abs/1906.00091 (2019) - [i9]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:
The Architectural Implications of Facebook's DNN-based Personalized Recommendation. CoRR abs/1906.03109 (2019) - [i8]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:
MLPerf Training Benchmark. CoRR abs/1910.01500 (2019) - [i7]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:
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. CoRR abs/1912.12953 (2019) - 2018
- [c11]Brandon Reagen, Udit Gupta, Lillian Pentecost
Ares: a framework for quantifying the resilience of deep neural networks. DAC 2018: 17:1-17:6 - [c10]Marco Donato, Brandon Reagen, Lillian Pentecost
On-chip deep neural network storage with multi-level eNVM. DAC 2018: 169:1-169:6 - [c9]Yuan Zhou, Udit Gupta, Steve Dai, Ritchie Zhao, Nitish Kumar Srivastava, Hanchen Jin, Joseph Featherston, Yi-Hsiang Lai, Gai Liu, Gustavo Angarita Velasquez, Wenping Wang
Rosetta: A Realistic High-Level Synthesis Benchmark Suite for Software Programmable FPGAs. FPGA 2018: 269-278 - [c8]Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander M. Rush
Weightless: Lossy weight encoding for deep neural network compression. ICLR (Workshop) 2018 - [c7]Brandon Reagen, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander M. Rush
Weightless: Lossy weight encoding for deep neural network compression. ICML 2018: 4321-4330 - 2017
- [c6]Rahul Pawar, Aaron Albin, Udit Gupta, Hrishikesh Rao, Caroline Carberry, Amarelle Hamo, Rebecca M. Jones, Catherine Lord, Mark A. Clements:
Automatic analysis of LENA recordings for language assessment in children aged five to fourteen years with application to individuals with autism. BHI 2017: 245-248 - [c5]Steve Dai, Ritchie Zhao, Gai Liu, Shreesha Srinath, Udit Gupta, Christopher Batten, Zhiru Zhang:
Dynamic Hazard Resolution for Pipelining Irregular Loops in High-Level Synthesis. FPGA 2017: 189-194 - [i6]Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David M. Brooks:
Weightless: Lossy Weight Encoding For Deep Neural Network Compression. CoRR abs/1711.04686 (2017) - 2016
- [j1]Udit Gupta
Time scale decomposition in complex reaction systems: A graph theoretic analysis. Comput. Chem. Eng. 95: 170-181 (2016) - [c4]Ayon Chakraborty, Udit Gupta, Samir R. Das:
Benchmarking resource usage for spectrum sensing on commodity mobile devices. HotWireless@MobiCom 2016: 7-11 - 2015
- [c3]Mingxing Tan, Steve Dai, Udit Gupta, Zhiru Zhang
Mapping-Aware Constrained Scheduling for LUT-Based FPGAs. FPGA 2015: 190-199 - [c2]Udit Gupta, Elliot Moore II, Alexander Lerch
On the perceptual relevance of objective source separation measures for singing voice separation. WASPAA 2015: 1-5 - [i5]Udit Gupta:
Survey on security issues in file management in cloud computing environment. CoRR abs/1505.00729 (2015) - [i4]Udit Gupta:
Application of Multi factor authentication in Internet of Things domain. CoRR abs/1506.03753 (2015) - [i3]Udit Gupta:
Monitoring in IOT enabled devices. CoRR abs/1507.03780 (2015) - [i2]Udit Gupta:
Secure management of logs in internet of things. CoRR abs/1507.05085 (2015) - [i1]Udit Gupta:
Comparison between security majors in virtual machine and linux containers. CoRR abs/1507.07816 (2015) - 2010
- [c1]Aida Austin, Elliot Moore II, Udit Gupta, Parag Chordia:
Characterization of movie genre based on music score. ICASSP 2010: 421-424
Coauthor Index
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last updated on 2024-10-23 20:27 CEST by the dblp team
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