Brandon Reagen

106 papers A* 20A 5B 6C 1Journal 58Unranked 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
NerVE: Nonlinear Eigenspectrum Dynamics in LLM Feed-Forward Networks.
CoRR
Nandan Kumar Jha, Brandon Reagen
2026 A* conf
zkPHIRE: A Programmable Accelerator for ZKPs over HIgh-degRee, Expressive Gates.
HPCA
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Siddharth Garg, Brandon Reagen
2025 J jnl
A Random Matrix Theory Perspective on the Learning Dynamics of Multi-head Latent Attention.
CoRR
Nandan Kumar Jha, Brandon Reagen
2025 — conf
A Spatial Array for Spectrally Agile Wireless Processing.
IEEECONF
Ali Rasteh, Andrew Hennessee, Ishaan Shivhare, Siddharth Garg, Sundeep Rangan, Brandon Reagen
2025 J jnl
A Spatial Array for Spectrally Agile Wireless Processing.
CoRR
Ali Rasteh, Andrew Hennessee, Ishaan Shivhare, Siddharth Garg, Sundeep Rangan, Brandon Reagen
2025 J jnl
ABLE: Optimizing Mixed Arithmetic and Boolean Garbled Circuit.
IACR Cryptol. ePrint Arch.
Jianqiao Cambridge Mo, Brandon Reagen
2025 — conf
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors.
WAHC@CCS
Karthik Garimella, Austin Ebel, Brandon Reagen
2025 J jnl
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors.
CoRR
Karthik Garimella, Austin Ebel, Brandon Reagen
2025 J jnl
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors.
IACR Cryptol. ePrint Arch.
Karthik Garimella, Austin Ebel, Brandon Reagen
2025 J jnl
Entropy-Guided Attention for Private LLMs.
CoRR
Nandan Kumar Jha, Brandon Reagen
2025 J jnl
HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption.
CoRR
Karthik Garimella, Austin Ebel, Gabrielle De Micheli, Brandon Reagen
2025 — conf
MTU: The Multifunction Tree Unit for Accelerating Zero-Knowledge Proofs.
HASP@MICRO
Jianqiao Mo, Alhad Daftardar, Joey Ah-kiow, Kaiyue Guo, Benedikt Bünz, Siddharth Garg, Brandon Reagen
2025 J jnl
MTU: The Multifunction Tree Unit in zkSpeed for Accelerating HyperPlonk.
CoRR
Jianqiao Mo, Alhad Daftardar, Joey Ah-kiow, Kaiyue Guo, Benedikt Bünz, Siddharth Garg, Brandon Reagen
2025 A* conf
Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs.
ISCA
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Ramesh Karri, Siddharth Garg, Brandon Reagen
2025 J jnl
Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs.
CoRR
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Ramesh Karri, Siddharth Garg, Brandon Reagen
2025 J jnl
Need for zkSpeed: Accelerating HyperPlonk for Zero-Knowledge Proofs.
IACR Cryptol. ePrint Arch.
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Ramesh Karri, Siddharth Garg, Brandon Reagen
2025 A conf
Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference (Invited Paper).
ICCAD
Karthik Garimella, Negar Neda, Austin Ebel, Nandan Kumar Jha, Brandon Reagen
2025 J jnl
Network and Compiler Optimizations for Efficient Linear Algebra Kernels in Private Transformer Inference.
CoRR
Karthik Garimella, Negar Neda, Austin Ebel, Nandan Kumar Jha, Brandon Reagen
2025 — conf
Orion: A Fully Homomorphic Encryption Framework for Deep Learning.
ASPLOS (2)
Austin Ebel, Karthik Garimella, Brandon Reagen
2025 J jnl
Spectral Scaling Laws in Language Models: How Effectively Do Feed-Forward Networks Use Their Latent Space?
CoRR
Nandan Kumar Jha, Brandon Reagen
2025 A* conf
Spectral Scaling Laws in Language Models: emphHow Effectively Do Feed-Forward Networks Use Their Latent Space?
EMNLP
Nandan Kumar Jha, Brandon Reagen
2025 J jnl
zkPHIRE: A Programmable Accelerator for ZKPs over HIgh-degRee, Expressive Gates.
CoRR
Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz, Siddharth Garg, Brandon Reagen
2024 J jnl
AERO: Softmax-Only LLMs for Efficient Private Inference.
CoRR
Nandan Kumar Jha, Brandon Reagen
2024 B conf
CiFlow: Dataflow Analysis and Optimization of Key Switching for Homomorphic Encryption.
ISPASS
Negar Neda, Austin Ebel, Benedict Reynwar, Brandon Reagen
2024 J jnl
DeepReShape: Redesigning Neural Networks for Efficient Private Inference.
Trans. Mach. Learn. Res.
Nandan Kumar Jha, Brandon Reagen
2024 J jnl
NTTSuite: Number Theoretic Transform Benchmarks for Accelerating Encrypted Computation.
CoRR
Juran Ding, Yuanzhe Liu, Lingbin Sun, Brandon Reagen
2024 J jnl
Osiris: A Systolic Approach to Accelerating Fully Homomorphic Encryption.
CoRR
Austin Ebel, Brandon Reagen
2024 J jnl
PriViT: Vision Transformers for Private Inference.
Trans. Mach. Learn. Res.
Naren Dhyani, Jianqiao Cambridge Mo, Patrick Yubeaton, Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde
2024 J jnl
ReLU's Revival: On the Entropic Overload in Normalization-Free Large Language Models.
CoRR
Nandan Kumar Jha, Brandon Reagen
2024 B conf
SZKP: A Scalable Accelerator Architecture for Zero-Knowledge Proofs.
PACT
Alhad Daftardar, Brandon Reagen, Siddharth Garg
2024 J jnl
SZKP: A Scalable Accelerator Architecture for Zero-Knowledge Proofs.
CoRR
Alhad Daftardar, Brandon Reagen, Siddharth Garg
2024 J jnl
TruncFormer: Private LLM Inference Using Only Truncations.
CoRR
Patrick Yubeaton, Jianqiao Mo, Karthik Garimella, Nandan Kumar Jha, Brandon Reagen, Chinmay Hegde, Siddharth Garg
2023 — conf
Characterizing and Optimizing End-to-End Systems for Private Inference.
ASPLOS (3)
Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
2023 J jnl
CiFlow: Dataflow Analysis and Optimization of Key Switching for Homomorphic Encryption.
CoRR
Negar Neda, Austin Ebel, Benedict Reynwar, Brandon Reagen
2023 J jnl
DeepReShape: Redesigning Neural Networks for Efficient Private Inference.
CoRR
Nandan Kumar Jha, Brandon Reagen
2023 — conf
Design Space Exploration of Modular Multipliers for ASIC FHE accelerators.
ISQED
Deepraj Soni, Mohammed Nabeel, Homer Gamil, Oleg Mazonka, Brandon Reagen, Ramesh Karri, Michail Maniatakos
2023 B conf
Exploring the Efficiency of Data-Oblivious Programs.
ISPASS
Lauren Biernacki, Biniyam Mengist Tiruye, Meron Zerihun Demissie, Fitsum Assamnew Andargie, Brandon Reagen, Todd M. Austin
2023 — conf
Generating High-Performance Number Theoretic Transform Implementations for Vector Architectures.
HPEC
Naifeng Zhang, Austin Ebel, Negar Neda, Patrick Brinich, Benedict Reynwar, Andrew G. Schmidt, Mike Franusich, Jeremy Johnson, Brandon Reagen, Franz Franchetti
2023 A* conf
HAAC: A Hardware-Software Co-Design to Accelerate Garbled Circuits.
ISCA
Jianqiao Mo, Jayanth Gopinath, Brandon Reagen
2023 J jnl
Orion: A Fully Homomorphic Encryption Compiler for Private Deep Neural Network Inference.
CoRR
Austin Ebel, Karthik Garimella, Brandon Reagen
2023 J jnl
PriViT: Vision Transformers for Fast Private Inference.
CoRR
Naren Dhyani, Jianqiao Mo, Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde
2023 J jnl
Privacy Preserving In-memory Computing Engine.
CoRR
Haoran Geng, Jianqiao Mo, Dayane Reis, Jonathan Takeshita, Taeho Jung, Brandon Reagen, Michael T. Niemier, Xiaobo Sharon Hu
2023 A conf
Quantifying the Overheads of Modular Multiplication.
ISLPED
Deepraj Soni, Mohammed Nabeel, Negar Neda, Ramesh Karri, Michail Maniatakos, Brandon Reagen
2023 B conf
RPU: The Ring Processing Unit.
ISPASS
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 G. Schmidt, Brandon Reagen
2023 J jnl
RPU: The Ring Processing Unit.
CoRR
Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar, Homer Gamil, Benjamin Heyman, Mohammed Thari Nabeel, Ahmad Al Badawi, Yuriy Polyakov, Kellie Canida, Massoud Pedram, Michail Maniatakos, David Bruce Cousins, Franz Franchetti, Matthew French, Andrew G. Schmidt, Brandon Reagen
2023 J jnl
RPU: The Ring Processing Unit.
IACR Cryptol. ePrint Arch.
Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar, Homer Gamil, Benjamin Heyman, Mohammed Thari Nabeel, Ahmad Al Badawi, Yuriy Polyakov, Kellie Canida, Massoud Pedram, Michail Maniatakos, David Bruce Cousins, Franz Franchetti, Matthew French, Andrew G. Schmidt, Brandon Reagen
2023 J jnl
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation.
CoRR
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi, Matthew French, Andrew G. Schmidt, Ajey P. Jacob, Benedict Reynwar, Kellie Canida, Akhilesh R. 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 Cheng, Massoud Pedram
2023 J jnl
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation.
IACR Cryptol. ePrint Arch.
David Bruce Cousins, Yuriy Polyakov, Ahmad Al Badawi, Matthew French, Andrew G. Schmidt, Ajey P. Jacob, Benedict Reynwar, Kellie Canida, Akhilesh R. 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 Cheng, Massoud Pedram
2023 — conf
Towards Fast and Scalable Private Inference.
CF
Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen
2023 J jnl
Towards Fast and Scalable Private Inference.
CoRR
Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen
2022 J jnl
Characterizing and Optimizing End-to-End Systems for Private Inference.
CoRR
Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen
2022 J jnl
HAAC: A Hardware-Software Co-Design to Accelerate Garbled Circuits.
CoRR
Jianqiao Mo, Jayanth Gopinath, Brandon Reagen
2022 J jnl
Homomorphically Encrypted Computation using Stochastic Encodings.
CoRR
Hsuan Hsiao, Vincent T. Lee, Brandon Reagen, Armin Alaghi
2022 J jnl
Impala: Low-Latency, Communication-Efficient Private Deep Learning Inference.
CoRR
Wooseok Choi, Brandon Reagen, Gu-Yeon Wei, David Brooks
2022 A* conf
Selective Network Linearization for Efficient Private Inference.
ICML
Minsu Cho, Ameya Joshi, Brandon Reagen, Siddharth Garg, Chinmay Hegde
2022 J jnl
Selective Network Linearization for Efficient Private Inference.
CoRR
Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde
2022 J jnl
Sphynx: A Deep Neural Network Design for Private Inference.
IEEE Secur. Priv.
Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde
2022 J jnl
Verifiable Access Control for Augmented Reality Localization and Mapping.
CoRR
Shaowei Zhu, Hyo Jin Kim, Maurizio Monge, G. Edward Suh, Armin Alaghi, Brandon Reagen, Vincent T. Lee
2021 J jnl
Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors.
CoRR
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
2021 A* conf
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference.
HPCA
Brandon Reagen, Wooseok Choi, Yeongil Ko, Vincent T. Lee, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks
2021 A* conf
Circa: Stochastic ReLUs for Private Deep Learning.
NeurIPS
Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg
2021 J jnl
Circa: Stochastic ReLUs for Private Deep Learning.
CoRR
Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg
2021 J jnl
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale.
CoRR
Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
2021 A* conf
DeepReDuce: ReLU Reduction for Fast Private Inference.
ICML
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
2021 J jnl
DeepReDuce: ReLU Reduction for Fast Private Inference.
CoRR
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
2021 A conf
Mitigating Reverse Engineering Attacks on Local Feature Descriptors.
BMVC
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
2021 J jnl
Porcupine: A Synthesizing Compiler for Vectorized Homomorphic Encryption.
CoRR
Meghan Cowan, Deeksha Dangwal, Armin Alaghi, Caroline Trippel, Vincent T. Lee, Brandon Reagen
2021 A* conf
Porcupine: a synthesizing compiler for vectorized homomorphic encryption.
PLDI
Meghan Cowan, Deeksha Dangwal, Armin Alaghi, Caroline Trippel, Vincent T. Lee, Brandon Reagen
2021 J jnl
Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning.
CoRR
Karthik Garimella, Nandan Kumar Jha, Brandon Reagen
2021 J jnl
SoK: Opportunities for Software-Hardware-Security Codesign for Next Generation Secure Computing.
CoRR
Deeksha Dangwal, Meghan Cowan, Armin Alaghi, Vincent T. Lee, Brandon Reagen, Caroline Trippel
2021 J jnl
Sphynx: ReLU-Efficient Network Design for Private Inference.
CoRR
Minsu Cho, Zahra Ghodsi, Brandon Reagen, Siddharth Garg, Chinmay Hegde
2021 — conf
VIP-Bench: A Benchmark Suite for Evaluating Privacy-Enhanced Computation Frameworks.
SEED
Lauren Biernacki, Meron Zerihun Demissie, Kidus Birkayehu Workneh, Galane Basha Namomsa, Plato Gebremedhin, Fitsum Assamnew Andargie, Brandon Reagen, Todd M. Austin
2020 J jnl
Cheetah: Optimizations and Methods for PrivacyPreserving Inference via Homomorphic Encryption.
CoRR
Brandon Reagen, Wooseok Choi, Yeongil Ko, Vincent T. Lee, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks
2020 A* conf
CryptoNAS: Private Inference on a ReLU Budget.
NeurIPS
Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg
2020 J jnl
CryptoNAS: Private Inference on a ReLU Budget.
CoRR
Zahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg
2020 A* conf
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference.
ISCA
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2020 J jnl
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference.
CoRR
Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu
2020 A* conf
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.
ISCA
Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David 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, Brandon Reagen, Carole-Jean Wu, Mark Hempstead, Xuan Zhang
2020 — conf
SoK: Opportunities for Software-Hardware-Security Codesign for Next Generation Secure Computing.
HASP@MICRO
Deeksha Dangwal, Meghan Cowan, Armin Alaghi, Vincent T. Lee, Brandon Reagen, Caroline Trippel
2020 A* conf
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation.
HPCA
Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
2019 B conf
Demystifying Bayesian Inference Workloads.
ISPASS
Yu Emma Wang, Yuhao Zhu, Glenn G. Ko, Brandon Reagen, Gu-Yeon Wei, David Brooks
2019 B conf
MASR: A Modular Accelerator for Sparse RNNs.
PACT
Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2019 A* conf
Machine Learning at Facebook: Understanding Inference at the Edge.
HPCA
Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim M. 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
2019 A* conf
MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation.
MICRO
Lillian Pentecost, Marco Donato, Brandon Reagen, Udit Gupta, Siming Ma, Gu-Yeon Wei, David Brooks
2019 J jnl
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing.
CoRR
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
2019 J jnl
The Architectural Implications of Facebook's DNN-based Personalized Recommendation.
CoRR
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
2018 A* conf
Ares: a framework for quantifying the resilience of deep neural networks.
DAC
Brandon Reagen, Udit Gupta, Lillian Pentecost, Paul N. Whatmough, Sae Kyu Lee, Niamh Mulholland, David M. Brooks, Gu-Yeon Wei
2018 J jnl
Assisting High-Level Synthesis Improve SpMV Benchmark Through Dynamic Dependence Analysis.
IEEE Trans. Circuits Syst. II Express Briefs
Rafael Garibotti, Brandon Reagen, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks
2018 A* conf
On-chip deep neural network storage with multi-level eNVM.
DAC
Marco Donato, Brandon Reagen, Lillian Pentecost, Udit Gupta, David Brooks, Gu-Yeon Wei
2018 — conf
Weightless: Lossy weight encoding for deep neural network compression.
ICLR (Workshop)
Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2018 A* conf
Weightless: Lossy weight encoding for deep neural network compression.
ICML
Brandon Reagen, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks
2017 J jnl
A Fully Integrated Battery-Powered System-on-Chip in 40-nm CMOS for Closed-Loop Control of Insect-Scale Pico-Aerial Vehicle.
IEEE J. Solid State Circuits
Xuan Zhang, Mario Lok, Tao Tong, Sae Kyu Lee, Brandon Reagen, Simon Chaput, Pierre-Emile J. Duhamel, Robert J. Wood, David M. Brooks, Gu-Yeon Wei
2017 A conf
A case for efficient accelerator design space exploration via Bayesian optimization.
ISLPED
Brandon Reagen, José Miguel Hernández-Lobato, Robert Adolf, Michael A. Gelbart, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks
2017 J jnl
Cognitive Computing Safety: The New Horizon for Reliability / The Design and Evolution of Deep Learning Workloads.
IEEE Micro
Yuhao Zhu, Vijay Janapa Reddi, Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks
2017 — book
Deep Learning for Computer Architects
Brandon Reagen, Robert Adolf, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks
2017 — conf
Methods and infrastructure in the era of accelerator-centric architectures.
MWSCAS
Brandon Reagen, Yakun Sophia Shao, Sam Likun Xi, Gu-Yeon Wei, David Brooks
2017 C conf
Using dynamic dependence analysis to improve the quality of high-level synthesis designs.
ISCAS
Rafael Garibotti, Brandon Reagen, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks
2017 J jnl
Weightless: Lossy Weight Encoding For Deep Neural Network Compression.
CoRR
Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David M. Brooks
2016 J jnl
Fathom: Reference Workloads for Modern Deep Learning Methods.
CoRR
Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks
2016 — conf
Fathom: reference workloads for modern deep learning methods.
IISWC
Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks
2016 A* conf
Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators.
ISCA
Brandon Reagen, Paul N. Whatmough, Robert Adolf, Saketh Rama, Hyunkwang Lee, Sae Kyu Lee, José Miguel Hernández-Lobato, Gu-Yeon Wei, David M. Brooks
2015 — conf
A multi-chip system optimized for insect-scale flapping-wing robots.
VLSIC
Xuan Zhang, Mario Lok, Tao Tong, Simon Chaput, Sae Kyu Lee, Brandon Reagen, Hyunkwang Lee, David M. Brooks, Gu-Yeon Wei
2015 J jnl
The Aladdin Approach to Accelerator Design and Modeling.
IEEE Micro
Yakun Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David M. Brooks
2014 A* conf
Aladdin: A pre-RTL, power-performance accelerator simulator enabling large design space exploration of customized architectures.
ISCA
Yakun Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David M. Brooks
2014 — conf
MachSuite: Benchmarks for accelerator design and customized architectures.
IISWC
Brandon Reagen, Robert Adolf, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks
2013 A conf
Quantifying acceleration: Power/performance trade-offs of application kernels in hardware.
ISLPED
Brandon Reagen, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks