About Me
My research spans across computer architecture, systems, and machine learning to to co-design solutions across the computing stack. Generally, I am interested in discovering and demonstrating new ways to design systems and hardware to improve the performance, efficiency, and environmental sustainability of emerging applications.
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.
Our work demonstrates that recommendation not only accounts for a majority of all AI cycles in data centers but also poses unique challenges to efficient execution that limits new modeling capabilities.
Tackling these challenges we outline an in-depth analysis and characterization of the architectural implications of recommendation models across production data centers.
Building on the characterization, we accelerate recommendation systems with novel near memory processing systems, inference schedulers, and data center-scale specialized hardware for a wide set of neural recommendation models.
Some of these solutions have been deployed in production data centers, demonstrating performance improvements at-scale. To enable future work into datacenter scale recommendation inference, we have open-sourced the proposed infrastructure, DeepRecSys and host the Personalized Recommendation Systems and Algorithms (PeRSonAl) workshop.
Given the growing demands for AI, emerging applications, and computing overall, I am also passionate about investigated new techniques to enable environmentally sustainable computing.
We show that sustainable mobile and data-center scale computing requires reducing both operational energy consumption and embodied carbon from hardware manufacturing (Chasing Carbon).
From a computing perspective this means we must rethink research and development across the computing stack (applications, systems, hardware, and devices) in order to build sustainable computer systems of the future.
This has led us to conduct in-depth studies understanding the challenges and opportunities for sustainable AI , developing methods towards 24/7 carbon-aware data centers, and architectural carbon aware modeling tools.
We also hosted the Computing Landscapes for Environmental Accountability and Responsibility (CLEAR) workshop at ISCA 2021.
My past work has also included designing hardware accelerators for sparse RNNs, building and integrating a DNN accelerator into mobile SoC taped-out in 16nm, lossy compression techniques for DNNs, and quantifying the fault tolerance of DNNs.
I am an active co-chair of the Computer Architecture Student Association, where I hope to build a more diverse and inclusive student community in computer architecture.
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 am a PhD student studying Computer Science in the Harvard Architecture, Circuits and Compilers group at Harvard University working with Professor David Brooks and Professor Gu-Yeon Wei. I have also been fortunate to collaborate with Facebook AI Research's (FAIR) SysML team where I am advised by Dr. Carole-Jean Wu.
Education
Harvard University
PhD in Computer Science (2016-Present)
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
Under submission.
[ArXiv]
Sustainable AI: Environmental Implications, Challenges and Opportunities
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, et. al.
To appear in 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 |
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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