Publications
For a compete list, PDFs, and citation counts please see Google scholar.
-2023-
HAAC: A Hardware-Software Co-Design to Accelerate Garbled Circuits
Jianqiao Mo, Jayanth Gopinath, Brandon Reagen
ISCA 2023
Characterizing and optimizing end-to-end systems for private inference
Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
ASPLOS 2023
Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar, Homer Gamil, Benjamin Heyman, Mohammed Nabeel, Ahmad Al Badawi, Yuriy Polyakov, Kellie Canida, Massoud Pedram, Michail Maniatakos, David Bruce Cousins, Franz Franchetti, Matthew French, Andrew Schmidt, Brandon Reagen
ISPASS 2023
Exploring the Efficiency of Data-Oblivious Programs
Lauren Biernacki, Biniyam Mengist Tiruye, Meron Zerihun Demissie, Fitsum Assamnew Andargie, Brandon Reagen, Todd Austin
ISPASS 2023
Quantifying the Overheads of Modular Multiplication
Deepraj Soni, Mohammed Nabeel Thari Moopan, Negar Neda, Ramesh Karri, Michail Maniatakos, Brandon Reagen
ISLPED 2023
Generating High-Performance Number Theoretic Transform Implementations for Vector Architectures
Naifeng Zhang, Austin Ebel, Negar Neda, Benedict Reynwar, Andrew Schmidt, Brandon Reagen, Franz Franchetti
HPEC 2023
Design Space Exploration of Modular Multipliers for ASIC FHE accelerators
Deepraj Soni, Mohammed Nabeel, Homer Gamil, Oleg Mazonka, Brandon Reagen, Ramesh Karri, Michail Maniatakos
ISQED 2023
Towards Fast and Scalable Private Inference
Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen
Computing Frontiers 2023
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi, Matthew French, Andrew Schmidt, Ajey Jacob, Benedict Reynwar, Kellie Canida, Akhilesh Jaiswal, Clynn Mathew, Homer Gamil, Negar Neda, Deepraj Soni, Michail Maniatakos, Brandon Reagen, Naifeng Zhang, Franz Franchetti, Patrick Brinich, Jeremy Johnson, Patrick Broderick, Mike Franusich, Bo Zhang, Zeming Chen, Massoud Pedram
GOMACTech 2023
NTTSuite: Number Theoretic Transform Benchmarks for Accelerating Encrypted Computation
Juran Ding, Yuanzhe Liu, Lingbin Sun, Brandon Reagen
Online, 2023
-2022-
Selective Network Linearization for Efficient Private Inference
Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde
ICML 2022
Sphynx: A Deep Neural Network Design for Private Inference
Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde
IEEE S&P 2022
Towards Full-Stack Acceleration for Fully Homomorphic Encryption
Naifeng Zhang, Homer Gamil, Patrick Brinich, Benedict Reynwar, Ahmad Al Badawi, Negar Neda, Deepraj Soni, Kellie Canida, Yuriy Polyakov, Patrick Broderick, Michail Maniatakos, Andrew G Schmidt, Mike Franusich, Jeremy Johnson, Brandon Reagen, David Bruce Cousins, Franz Franchetti
HPEC 2022
Impala: Low-Latency, Communication-Efficient Private Deep Learning Inference
Woo-Seok Choi, Brandon Reagen, Gu-Yeon Wei, David Brooks
ArXiv 2022
Verifiable Access Control for Augmented Reality Localization and Mapping
Shaowei Zhu, Hyo Jin Kim, Maurizio Monge, G Edward Suh, Armin Alaghi, Brandon Reagen, Vincent Lee
ArXiv 2022
Homomorphically Encrypted Computation using Stochastic Encodings
Hsuan Hsiao, Vincent Lee, Brandon Reagen, Armin Alaghi
NOPE 2022
-2021-
Circa: Stochastic relus for private deep learning
Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg
NeurIPS 2021
Cryptonite: Revealing the pitfalls of end-to-end private inference at scale
Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
ArXiv 2021
VIP-Bench: A Benchmark Suite for Evaluating Privacy-Enhanced Computation Frameworks
Lauren Biernacki, Meron Zerihun Demissie, Kidus Birkayehu Workneh, Galane Basha Namomsa, Plato Gebremedhin, Fitsum Assamnew Andargie, Brandon Reagen, Todd Austin
SEED 2021
Karthik Garimella, Nandan Kumar Jha, Brandon Reagen
PPML 2021
DeepReDuce: Relu reduction for fast private inference
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
ICML 2021
Computer memory module processing device with cache storage
Liu Ke, Xuan Zhang, Udit Gupta, WU Carole-Jean, Mark David Hempstead, Brandon Reagen, Hsien-hsin Sean Lee
U.S. Parent 2021
Porcupine: A synthesizing compiler for vectorized homomorphic encryption
Meghan Cowan, Deeksha Dangwal, Armin Alaghi, Caroline Trippel, Vincent T Lee, Brandon Reagen
PLDI 2021
Cheetah: Optimizing and accelerating homomorphic encryption for private inference
Brandon Reagen, Woo-Seok Choi, Yeongil Ko, Vincent T Lee, Hsien-Hsin S Lee, Gu-Yeon Wei, David Brooks
HPCA 2021 (TopPicks Honorable Mention)
Mitigating Reverse Engineering Attacks on Local Feature Descriptors
Deeksha Dangwal, Vincent T Lee, Hyo Jin Kim, Tianwei Shen, Meghan Cowan, Rajvi Shah, Caroline Trippel, Brandon Reagen, Timothy Sherwood, Vasileios Balntas, Armin Alaghi, Eddy Ilg
BMVC 2021
-2020-
Cryptonas: Private inference on a relu budget
Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg
NeurIPS 2020
SoK: Opportunities for Software-Hardware-Security Codesign for Next Generation Secure Computing
Deeksha Dangwal, Meghan Cowan, Armin Alaghi, Vincent T Lee, Brandon Reagen, Caronline Trippel
HASP 2020
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
ISCA 2020
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
ISCA 2020
The Architectural Implications of Facebook's DNN-based Personalized Recommendation
Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Bill Jia, Hsien-Hsin S Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
HPCA 2020
-2019-
MASR: A Modular Accelerator for Sparse RNNs
Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe,
Alexander Rush, Gu-Yeon Wei, David Brooks
PACT 2019 (Best paper nomination)
Lillian Pentecost, Marco Donato, Brandon Reagen, Udit Gupta, Siming Ma, Gu-Yeon Wei, David Brooks
MICRO 2019
Demystifying Bayesian Inference Workloads
Yu Emma Wang, Yuhao Zhu, Glenn G Ko, Brandon Reagen, Gu-Yeon Wei, David Brooks
ISPASS 2019
Machine learning at facebook: Understanding inference at the edge
Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim Hazelwood, Eldad Isaac, Yangqing Jia, Bill Jia, Tommer Leyvand, Hao Lu, Yang Lu, Lin Qiao, Brandon Reagen, Joe Spisak, Fei Sun, Andrew Tulloch, Peter Vajda, Xiaodong Wang, Yanghan Wang, Bram Wasti, Yiming Wu, Ran Xian, Sungjoo Yoo, Peizhao Zhang
HPCA 2019
-2018-
Weightless: Lossy Weight Encoding For Deep Neural Network Compression
Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander Rush, Gu-Yeon Wei, David Brooks
ICML 2018
Ares: A Framework for Quantifying the Resilience of Deep Neural Networks
Brandon Reagen, Udit Gupta, Lillian Pentecost, Paul Whatmough, Sae Kyu Lee, Gu-Yeon Wei, David Brooks
DAC 2018 ( Best Paper Nomination! )
On-Chip Deep Neural Network Storage with Multi-Level eNVM
Marco Donato, Brandon Reagen, Lillian Pentecost, Udit Gupta, Gu-Yeon Wei, David Brooks
DAC 2018
Assisting High-Level Synthesis Improve SpMV Benchmark Through Dynamic Dependence Analysis
Rafael Garibotti, Brandon Reagen, Yakun Sophia Shao, Gu-Yeon Wei, David Brooks
TCAS II 2018
-2017-
Deep Learning for Computer Architects
Brandon Reagen, Robert Adolf, Paul Whatmough, Gu-Yeon Wei, David
Synthesis Lecture 2017
A Fully-Integrated Battery-Powered System-on-Chip in 40-nm CMOS for Closed-Loop Control of Insect-Scale Pico-Aerial Vehicle
Xuan Zhang, Mario Lok, Tao Tong, Sae Kyu Lee, Brandon Reagen, Simon Chaput, Pierre-Emile J Duhamel, Robert J Wood, David Brooks, Gu-Yeon Wei
JSSC 2017
A Case for Efficient Accelerator Design Space Exploration via Bayesian Optimization
Brandon Reagen, Jose-Miguel Hernández-Lobato, Robert Adolf, Michael Gelbart, Paul Whatmough, Gu-Yeon Wei, David Brooks
ISLPED 2017
Using Dynamic Dependence Analysis to Improve the quality of High-Level Synthesis Designs
Rafael Garibotti, Brandon Reagen, Sophia Shao, Gu-Yeon Wei, David Brooks
ISCAS 2017
The Design and Evolution of Deep Learning Workloads
Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David Brooks
IEEE MICRO 2017
-2016-
Fathom: Reference Workloads for Modern Deep Learning Methods
Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David Brooks
IISWC 2016
Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators
Brandon Reagen, Paul Whatmough, Robert Adolf, Saketh Rama, Hyungkwong Lee, Sae Kyu Lee, Jose-Miguel Hernández-Lobato, Gu-Yeon Wei, David Brooks
ISCA 2016
-2015-
A Multi-Chip System Optimized for Insect-Scale Flapping-Wing Robots
Xuan Zhang, Mario Lok, Tao Tong, Simon Chaput, Sae Kyu Lee, Brandon Reagen, Hyungkwong Lee, David Brooks, Gu-Yeon Wei
VLSI 2015
The Aladdin Approach to Accelerator Design and Modeling
Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David Brooks
IEEE MICRO, Top Picks 2015
-2014-
MachSuite: Benchmarks for Accelerator Design and Customized Architectures
Brandon Reagen, Robert Adolf, Sophia Shao, Gu-Yeon Wei, David Brooks
IISWC 2014
Aladdin: A Pre-RTL, Power-Performance Accelerator Simulator Enabling Large Design Space Exploration of Customized Architectures
Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David Brooks
ISCA 2014
-2013-
Quantifying Acceleration: Power/Performance Trade-offs of Application Kernels in Hardware
Brandon Reagen, Sophia Shao, Gu-Yeon Wei, David Brooks
ISLPED 2013
-2012-
Joined Harvard as a PhD student.