Publications
For a compete list, PDFs, and citation counts please see Google scholar.
-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.