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About Me

I am a rising Assistant Professor in the Department of Electrical and Computer Engineering at Cornell Tech. My research interests lie at the intersection of computer architecture, systems, machine learning, and environmental sustainability The central theme to my research is co-designing solutions across the computing stack (applications, algorithms, systems and architecture, circuits and devices) to design and implement computer systems and hardware in new ways to improve the performance, efficiency, and environmental sustainability of emerging applications.

Systems for AI at-scale: My research optimizes the at-scale deployment of deep learning based personalized recommendation in order to enable next generation recommendation systems. Personalized recommendation is central to many Internet services we use on a daily basis including social media, search, video and movie streaming, and e-commerce platforms. My analysis and characterization of personalized recommendation services at-scale is the first to identify the unique challenges recommendation models pose to efficient data center deployment, opening exciting new computing systems and architecture research directions. Building on the characterization, my work accelerates recommendation systems through a diverse spectrum of solutions including  novel near memory processing systems, inference schedulers, and data center-scale specialized hardware. Through my close collaboration with industry, our software solutions for optimizing recommendation have been deployed in production data centers, yielding significant performance and efficiency improvements at-scale.

Sustainability and Computing: My research goes beyond improving performance and efficiency to investigate new techniques towards enabling environmentally sustainable computing. My research is the first to show that the carbon footprint of modern mobile devices and data-centers requires owes not only to operational energy consumption and but also (and in fact is dominated by) embodied carbon from hardware manufacturing (Chasing Carbon). Building sustainable computer systems for the future requires us to fundamentally rethink research and development across the computing stack. My research has conducted in-depth studies understanding the challenges and opportunities for sustainable AI, developed methods towards 24/7 carbon-aware data centers, and built architectural carbon aware modeling tools.

In the past my research has also investigated co-designing neural networks and specialized hardware for low-power and energy-efficient mobile AI including image classification and speech recognition.

My work has been recognized as an IEEE MICRO Top Picks (2021) and IEEE MICRO Top Picks Honorable Mention (2020), as well as received best paper nominations at the Parallel Architectures and Compilation Techniques (PACT 2019) and Design Automation Conference (DAC 2018). I completed my Ph.D. in Computer Science at Harvard University.

Recruiting!

I am actively looking for motivated, ambitious, and passtiontae graduate students, postdoctoral scholars, and undergraduate researchers!

If you are interested in working with me, please send me an email with your CV, your transcript, and brief summary of research areas that excite you.

If you are a PhD student interested in working with me, please apply to the Cornell ECE PhD program and mention me in your application. Cornell Tech and Cornell share the PhD application and end-to-end PhD program.

Education

Harvard University

PhD in Computer Science (2016-2022)
Masters of Science in Computer Science (2020)

Cornell University

Bachelor of Science, GPA 4.00 (2012-2016)
Major: Electrical and Computer Engineering
Minor: Computer Science

Publications

For a complete and up to date list of publications please visit Google Scholar.

ACT: Designing Sustainable Computer Systems With An Architectural Carbon Modeling Tool
Udit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
International Symposium on Computer Architecture (ISCA 2022)
[PDF] [Slides] [Github]

A Holistic Approach for Designing Carbon Aware Datacenters
Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
To appear in International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2023)
[ArXiv]

Sustainable AI: Environmental Implications, Challenges and Opportunities
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, et. al.
Machine Learning and Systems (MLSys 2022)
[ArXiv]

Hercules: Heterogeneity-Aware Inference Serving for At-scale Personalized Recommendation
Liu Ke, Udit Gupta, Mark Hempstead, Carole-Jean Wu, Hsien-Hsin Sean Lee, Xuan Zhang
IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022)

RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance
Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
IEEE/ACM International Symposium on Microarchitecture (MICRO 2021)
[ArXiv] [Github] [MICRO 2021 Talk] [MICRO 2021 Lightning Talk] [PDF]
[Artifact] (available, functional, and reproducible)

RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, Gu-Yeon Wei
International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2021)
[ArXiv]

Chasing Carbon: The Elusive Environmental Footprint of Computing
Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu
IEEE International Symposium on High-Performance Computer Architecture (HPCA 2021)
Selected as IEEE MICRO's Top Picks
Featured by: Harvard Gazette, Tech @ Facebook, Bloomberg Green
[PDF] [Slides] [HPCA 2021 Long Talk] [HPCA 2021 Short Talk]

DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
International Symposium on Computer Architecture (ISCA 2020)
[PDF] [Slides] [ISCA 2020 Talk] [Github] [PeRSonAl Tutorial Talk]

RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Liu Ke, Udit Gupta, Carole-Jean Wu, Benjamin Youngjae Cho, Mark Hempstead, Brandon Reagen, Xuan Zhang, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang
International Symposium on Computer Architecture (ISCA 2020)
[PDF]

Architectural Implications of Facebook’s DNN-based Personalized Recommendation
Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
IEEE International Symposium on High-Performance Computer Architecture (HPCA 2020)
Selected as Honorable Mention for IEEE MICRO's Top Picks
Featured by: Facebook Research
[PDF] [Slides] [Github] [PeRSonAl Tutorial Talk]

MASR: A Modular Accelerator for Sparse RNNs
Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander Rush, Gu-Yeon Wei, David Brooks
Parallel Architectures and Compilation Techniques (PACT 2019)
Best Paper Nominee
[PDF], [Slides], [ArXiv]

Professional Experience

Facebook, Inc.

Facebook AI Research (FAIR) Visiting Research Scientist January 2021 - Present
Facebook AI Research (FAIR) Intern January 2020 - December 2020
AI Infrastructure Research Intern September 2018 - January 2020

Algo Logic Systems Inc.

Hardware Design and Verification Engineer May 2015 - August 2015

Teaching Experience

Harvard CS 290 Fall 2020
Harvard CS 141 Spring 2019
EdX MOOC: The Computing Inside Your Smart Phone Summer 2014
Cornell ECE 2300: Introduction to Digital Logic and Computer Organization Spring & Fall 2014, Spring 2015
Cornell CS 3420 / ECE 3140: Embedded Systems Spring 2016
Middle-school and high-school outreach
Rainstorm, Sustainable Computing Spring & Summer 2021
Splash, Computers Don't Byte! Fall 2014 and Spring 2015

Community Involvement

Panels and Young Professionals Activities Chair at MLSys 2022 2022
CLEAR at ISCA 2021 Co-Founder and Co-Organizer 2021
NOPE at ASPLOS 2021 Co-Organizer 2021
JOURNE at MLSys 2021 Co-Founder and Co-Organizer 2021
PeRSonAl at MLSys 2021 Co-Founder and Co-Organizer 2021
PeRSonAl at ISCA 2020 Co-Founder and Co-Organizer 2020
PeRSonAl at ASPLOS 2020 Co-Founder and Co-Organizer 2020
NOPE at ASPLOS 2019 Co-Organizer 2019
Computer Architecture Student Association (Co-chair) 2022 - Present
Computer Architecture Student Association (steering committee member) 2020 - 2022
3C (Cultural Competence in Computing) Fellow 2021 - 2022
Harvard SEAS Graduate Council Member 2020 - Present
Harvard SITN Lecture Director 2018 - 2019
Harvard SITN Blog Editor 2018 - 2019
Cornell IEEE President 2015 - 2016
Cornell IEEE Corporate Director 2013 - 2015

Honors and Awards

IEEE MICRO Top Picks 2021
IEEE MICRO Top Picks Honorable Mention 2020
Best Paper Nominee at Parallel Architecture and Compilation Techniques (PACT 2019) 2019
Best Paper Nominee at Design Automation Conference (DAC 2018) 2018
Harvard Smith Family Fellowship 2017
NSF GRFP Honorable Mention 2016
Richard A. Newton Young Fellow Scholarship 2015
Cornell Eta Kappa Nu (HKN) - Electrical Engineering Honor Society 2013 - 2016
Cornell ECE Early Research Career Scholarship 2013

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