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David Brooks 0001
David M. Brooks
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- affiliation: Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, USA
Other persons with the same name
- David Brooks — disambiguation page
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2020 – today
- 2024
- [j61]Yu-Shun Hsiao
, Zishen Wan
Silent Data Corruption in Robot Operating System: A Case for End-to-End System-Level Fault Analysis Using Autonomous UAVs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(4): 1037-1050 (2024) - [c166]Maximilian Lam
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. ASPLOS (1) 2024: 197-214 - [c165]Sai Qian Zhang, Thierry Tambe, Nestor Cuevas, Gu-Yeon Wei, David Brooks:
CAMEL: Co-Designing AI Models and eDRAMs for Efficient On-Device Learning. HPCA 2024: 861-875 - [c164]Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush:
Guess & Sketch: Language Model Guided Transpilation. ICLR 2024 - [c163]Alexander Hankin, Abdulrahman Mahmoud, Mark Hempstead, David Brooks, Gu-Yeon Wei:
VelociTI: An Architecture-level Performance Modeling Framework for Trapped Ion Quantum Computers. IISWC 2024: 156-168 - [c162]Martin Cochet, Karthik Swaminathan, Erik Jens Loscalzo, Joseph Zuckerman, Maico Cassel dos Santos, Davide Giri, Alper Buyuktosunoglu, Tianyu Jia, David Brooks, Gu-Yeon Wei, Kenneth L. Shepard, Luca P. Carloni, Pradip Bose:
BlitzCoin: Fully Decentralized Hardware Power Management for Accelerator-Rich SoCs. ISCA 2024: 801-817 - [c161]Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. ISCA 2024: 818-833 - [c160]Sai Qian Zhang
JointNF: Enhancing DNN Performance through Adaptive N: M Pruning across both Weight and Activation. ISLPED 2024: 1-6 - [c159]Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation. ISPASS 2024: 257-267 - [c158]Maico Cassel dos Santos, Tianyu Jia, Joseph Zuckerman, Martin Cochet, Davide Giri, Erik Jens Loscalzo, Karthik Swaminathan, Thierry Tambe, Jeff Jun Zhang, Alper Buyuktosunoglu, Kuan-Lin Chiu, Giuseppe Di Guglielmo, Paolo Mantovani, Luca Piccolboni, Gabriele Tombesi, David Trilla, John-David Wellman, En-Yu Yang, Aporva Amarnath, Ying Jing, Bakshree Mishra, Joshua Park, Vignesh Suresh, Sarita V. Adve, Pradip Bose, David Brooks, Luca P. Carloni, Kenneth L. Shepard, Gu-Yeon Wei:
14.5 A 12nm Linux-SMP-Capable RISC-V SoC with 14 Accelerator Types, Distributed Hardware Power Management and Flexible NoC-Based Data Orchestration. ISSCC 2024: 262-264 - [c157]Erik Jens Loscalzo, Martin Cochet, Joseph Zuckerman, Samira Zalias, Michael Lekas, Stephen Cahill, Tianyu Jia, Karthik Swaminathan, Maico Cassel dos Santos, Davide Giri, Hesam Sadeghi, Joseph Meyer, Noah Sturcken, David Brooks, Gu-Yeon Wei, Luca P. Carloni, Pradip Bose, Kenneth L. Shepard:
A 400-ns-Settling- Time Hybrid Dynamic Voltage Frequency Scaling Architecture and Its Application in a 22-Core Network-on-Chip SoC in 12-nm FinFET Technology. VLSI Technology and Circuits 2024: 1-2 - [i49]Hyeri Roh, Jinsu Yeo, Yeongil Ko, Gu-Yeon Wei, David Brooks, Wooseok Choi:
Flash: A Hybrid Private Inference Protocol for Deep CNNs with High Accuracy and Low Latency on CPU. CoRR abs/2401.16732 (2024) - [i48]Iulian Brumar, Rodrigo Rocha, Alex Bernat, Devashree Tripathy, David Brooks, Gu-Yeon Wei:
Guac: Energy-Aware and SSA-Based Generation of Coarse-Grained Merged Accelerators from LLVM-IR. CoRR abs/2402.13513 (2024) - [i47]Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Is Flash Attention Stable? CoRR abs/2405.02803 (2024) - [i46]Benjamin C. Lee, David Brooks, Arthur van Benthem, Udit Gupta, Gage Hills, Vincent Liu, Benjamin Pierce, Christopher Stewart, Emma Strubell, Gu-Yeon Wei, Adam Wierman, Yuan Yao, Minlan Yu:
Carbon Connect: An Ecosystem for Sustainable Computing. CoRR abs/2405.13858 (2024) - 2023
- [j60]Gabriele Tombesi
SoCProbe: Compositional Post-Silicon Validation of Heterogeneous NoC-Based SoCs. IEEE Des. Test 40(6): 64-75 (2023) - [j59]Jeffrey S. Vetter
Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials. Int. J. High Perform. Comput. Appl. 37(3-4): 351-379 (2023) - [j58]Thierry Tambe
A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. IEEE J. Solid State Circuits 58(2): 569-581 (2023) - [j57]Udit Gupta
Architectural CO2 Footprint Tool: Designing Sustainable Computer Systems With an Architectural Carbon Modeling Tool. IEEE Micro 43(4): 107-117 (2023) - [j56]Iulian Brumar
Early DSE and Automatic Generation of Coarse-grained Merged Accelerators. ACM Trans. Embed. Comput. Syst. 22(2): 32:1-32:29 (2023) - [j55]Georgios Zacharopoulos
Trireme: Exploration of Hierarchical Multi-level Parallelism for Hardware Acceleration. ACM Trans. Embed. Comput. Syst. 22(3): 53:1-53:23 (2023) - [j54]Siming Ma
A Binary-Activation, Multi-Level Weight RNN and Training Algorithm for ADC-/DAC-Free and Noise-Resilient Processing-in-Memory Inference With eNVM. IEEE Trans. Emerg. Top. Comput. 11(2): 292-302 (2023) - [c156]Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Udit Gupta
Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters. ASPLOS (2) 2023: 118-132 - [c155]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-design to Enable Multi-path Recommendation. ASPLOS (3) 2023: 449-465 - [c154]Yu-Shun Hsiao, Zishen Wan, Tianyu Jia, Radhika Ghosal, Abdulrahman Mahmoud, Arijit Raychowdhury, David Brooks, Gu-Yeon Wei, Vijay Janapa Reddi:
MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles. DATE 2023: 1-6 - [c153]Mariam Elgamal
Carbon-Efficient Design Optimization for Computing Systems. HotCarbon 2023: 16:1-16:7 - [c152]Alexander Hankin, Abdulrahman Mahmoud, Mark Hempstead
VelociTI: An Architecture-level Performance Modeling Framework for Trapped Ion Quantum Computers. IISWC 2023: 206-210 - [c151]Alexander Hankin, Lillian Pentecost, Dongmoon Min, David Brooks, Gu-Yeon Wei:
Is the Future Cold or Tall? Design Space Exploration of Cryogenic and 3D Embedded Cache Memory. ISPASS 2023: 134-144 - [c150]Matthew Joseph Adiletta, Jesmin Jahan Tithi, Emmanouil-Ioannis Farsarakis
Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA. ISPASS 2023: 168-177 - [c149]Thierry Tambe
A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. ISSCC 2023: 342-343 - [c148]Yunho Jin, Chun-Feng Wu, David Brooks, Gu-Yeon Wei:
S3: Increasing GPU Utilization during Generative Inference for Higher Throughput. NeurIPS 2023 - [c147]Syed Talal Wasim, Kabila Haile Soboka, Abdulrahman Mahmoud, Salman H. Khan, David Brooks, Gu-Yeon Wei:
Hardware Resilience Properties of Text-Guided Image Classifiers. NeurIPS 2023 - [i45]Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh:
GPU-based Private Information Retrieval for On-Device Machine Learning Inference. CoRR abs/2301.10904 (2023) - [i44]Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough:
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices. CoRR abs/2301.10999 (2023) - [i43]Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation. CoRR abs/2302.10872 (2023) - [i42]Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, Carole-Jean Wu:
GreenScale: Carbon-Aware Systems for Edge Computing. CoRR abs/2304.00404 (2023) - [i41]Mariam Elgamal, Doug Carmean, Elnaz Ansari, Okay Zed, Ramesh Peri, Srilatha Manne, Udit Gupta, Gu-Yeon Wei, David Brooks, Gage Hills, Carole-Jean Wu:
Design Space Exploration and Optimization for Carbon-Efficient Extended Reality Systems. CoRR abs/2305.01831 (2023) - [i40]Sai Qian Zhang, Thierry Tambe, Nestor Cuevas, Gu-Yeon Wei, David Brooks:
CAMEL: Co-Designing AI Models and Embedded DRAMs for Efficient On-Device Learning. CoRR abs/2305.03148 (2023) - [i39]Yunho Jin, Chun-Feng Wu, David Brooks, Gu-Yeon Wei:
S3: Increasing GPU Utilization during Generative Inference for Higher Throughput. CoRR abs/2306.06000 (2023) - [i38]Yuji Chai, John Gkountouras, Glenn G. Ko, David Brooks, Gu-Yeon Wei:
INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation. CoRR abs/2306.08162 (2023) - [i37]Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush:
Guess & Sketch: Language Model Guided Transpilation. CoRR abs/2309.14396 (2023) - [i36]Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems. CoRR abs/2310.02784 (2023) - [i35]Jiali Xing, Bilge Acun, Aditya Sundarrajan, David Brooks, Manoj Chakkaravarthy, Nikky Avila, Carole-Jean Wu, Benjamin C. Lee:
Carbon Responder: Coordinating Demand Response for the Datacenter Fleet. CoRR abs/2311.08589 (2023) - [i34]Syed Talal Wasim, Kabila Haile Soboka
Hardware Resilience Properties of Text-Guided Image Classifiers. CoRR abs/2311.14062 (2023) - [i33]Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation. CoRR abs/2312.14385 (2023) - 2022
- [j53]Sae Kyu Lee
SMIV: A 16-nm 25-mm² SoC for IoT With Arm Cortex-A53, eFPGA, and Coherent Accelerators. IEEE J. Solid State Circuits 57(2): 639-650 (2022) - [j52]Udit Gupta
Chasing Carbon: The Elusive Environmental Footprint of Computing. IEEE Micro 42(4): 37-47 (2022) - [j51]Nicolas Bohm Agostini
Bridging Python to Silicon: The SODA Toolchain. IEEE Micro 42(5): 78-88 (2022) - [j50]Serena Curzel
End-to-End Synthesis of Dynamically Controlled Machine Learning Accelerators. IEEE Trans. Computers 71(12): 3074-3087 (2022) - [c146]Chun-Feng Wu
A joint management middleware to improve training performance of deep recommendation systems with SSDs. DAC 2022: 157-162 - [c145]Tianyu Jia, En-Yu Yang, Yu-Shun Hsiao, Jonathan J. Cruz, David Brooks, Gu-Yeon Wei, Vijay Janapa Reddi:
OMU: A Probabilistic 3D Occupancy Mapping Accelerator for Real-time OctoMap at the Edge. DATE 2022: 909-914 - [c144]Abdulrahman Mahmoud, Thierry Tambe
GoldenEye: A Platform for Evaluating Emerging Numerical Data Formats in DNN Accelerators. DSN 2022: 206-214 - [c143]Tianyu Jia, Paolo Mantovani, Maico Cassel dos Santos, Davide Giri, Joseph Zuckerman, Erik Jens Loscalzo, Martin Cochet, Karthik Swaminathan, Gabriele Tombesi, Jeff Jun Zhang, Nandhini Chandramoorthy, John-David Wellman, Kevin Tien, Luca P. Carloni, Kenneth L. Shepard, David Brooks, Gu-Yeon Wei, Pradip Bose:
A 12nm Agile-Designed SoC for Swarm-Based Perception with Heterogeneous IP Blocks, a Reconfigurable Memory Hierarchy, and an 800MHz Multi-Plane NoC. ESSCIRC 2022: 269-272 - [c142]Serena Curzel
From High-Level Frameworks to custom Silicon with SODA. HCS 2022: 1-13 - [c141]Yuji Chai, Glenn G. Ko, Wei-Te Mark Ting, Luke Bailey, David Brooks, Gu-Yeon Wei:
CoopMC: Algorithm-Architecture Co-Optimization for Markov Chain Monte Carlo Accelerators. HPCA 2022: 38-52 - [c140]Lillian Pentecost
NVMExplorer: A Framework for Cross-Stack Comparisons of Embedded Non-Volatile Memories. HPCA 2022: 938-956 - [c139]Maico Cassel dos Santos, Tianyu Jia, Martin Cochet, Karthik Swaminathan, Joseph Zuckerman, Paolo Mantovani, Davide Giri, Jeff Jun Zhang, Erik Jens Loscalzo, Gabriele Tombesi, Kevin Tien, Nandhini Chandramoorthy, John-David Wellman, David Brooks, Gu-Yeon Wei, Kenneth L. Shepard, Luca P. Carloni, Pradip Bose:
A Scalable Methodology for Agile Chip Development with Open-Source Hardware Components. ICCAD 2022: 20:1-20:9 - [c138]Cheng Tan, Thierry Tambe
ASAP: automatic synthesis of area-efficient and precision-aware CGRAs. ICS 2022: 4:1-4:13 - [c137]Udit Gupta
ACT: designing sustainable computer systems with an architectural carbon modeling tool. ISCA 2022: 784-799 - [c136]Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust
Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. MICRO 2022: 300-317 - [c135]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, Jinshi Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. MLSys 2022 - [i32]Georgios Zacharopoulos, Adel Ejjeh, Ying Jing, En-Yu Yang, Tianyu Jia, Iulian Brumar, Jeremy Intan, Muhammad Huzaifa, Sarita V. Adve, Vikram S. Adve, Gu-Yeon Wei, David Brooks:
Trireme: Exploring Hierarchical Multi-Level Parallelism for Domain Specific Hardware Acceleration. CoRR abs/2201.08603 (2022) - [i31]Bilge Acun, Benjamin Lee, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu:
A Holistic Approach for Designing Carbon Aware Datacenters. CoRR abs/2201.10036 (2022) - [i30]Maximilian Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks:
Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference. CoRR abs/2203.02833 (2022) - [i29]Tianyu Jia, En-Yu Yang, Yu-Shun Hsiao, Jonathan J. Cruz, David Brooks, Gu-Yeon Wei, Vijay Janapa Reddi:
OMU: A Probabilistic 3D Occupancy Mapping Accelerator for Real-time OctoMap at the Edge. CoRR abs/2205.03325 (2022) - [i28]Wooseok Choi, Brandon Reagen, Gu-Yeon Wei, David Brooks:
Impala: Low-Latency, Communication-Efficient Private Deep Learning Inference. CoRR abs/2205.06437 (2022) - [i27]Matthew Adiletta, David Brooks, Gu-Yeon Wei:
Architectural Implications of Embedding Dimension during GCN on CPU and GPU. CoRR abs/2212.00827 (2022) - 2021
- [j49]Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim M. Hazelwood, David Brooks:
Exploiting Parallelism Opportunities with Deep Learning Frameworks. ACM Trans. Archit. Code Optim. 18(1): 9:1-9:23 (2021) - [c134]Jeff Jun Zhang, Nicolas Bohm Agostini
Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis. ASAP 2021: 218-225 - [c133]En-Yu Yang, Tianyu Jia, David Brooks, Gu-Yeon Wei:
FlexACC: A Programmable Accelerator with Application-Specific ISA for Flexible Deep Neural Network Inference. ASAP 2021: 266-273 - [c132]Mark Wilkening, Udit Gupta
RecSSD: near data processing for solid state drive based recommendation inference. ASPLOS 2021: 717-729 - [c131]Thierry Tambe, En-Yu Yang, Glenn G. Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N. Whatmough, Alexander M. Rush
SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33rd Hot Chips Symposium - August 22-24, 2021. HCS 2021: 1-13 - [c130]Brandon Reagen, Wooseok Choi, Yeongil Ko, Vincent T. Lee, Hsien-Hsin S. Lee
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference. HPCA 2021: 26-39 - [c129]Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Chasing Carbon: The Elusive Environmental Footprint of Computing. HPCA 2021: 854-867 - [c128]Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher:
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix. ICML 2021: 5959-5968 - [c127]Mohammad Mehdi Sharifi
Application-driven Design Exploration for Dense Ferroelectric Embedded Non-volatile Memories. ISLPED 2021: 1-6 - [c126]Thierry Tambe
9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET. ISSCC 2021: 158-160 - [c125]Thierry Tambe
EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. MICRO 2021: 830-844 - [c124]Udit Gupta
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. MICRO 2021: 870-884 - [i26]Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei:
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference. CoRR abs/2102.00075 (2021) - [i25]Srivatsan Krishnan, Zishen Wan
Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots. CoRR abs/2102.02988 (2021) - [i24]Udit Gupta, Samuel Hsia, Jeff Jun Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks:
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance. CoRR abs/2105.08820 (2021) - [i23]Yu-Shun Hsiao, Zishen Wan
MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles. CoRR abs/2105.12882 (2021) - [i22]Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher:
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix. CoRR abs/2106.06089 (2021) - [i21]Mohammad Mehdi Sharifi, Lillian Pentecost, Ramin Rajaei, Arman Kazemi, Qiuwen Lou, Gu-Yeon Wei, David Brooks, Kai Ni, X. Sharon Hu, Michael T. Niemier, Marco Donato:
Application-driven Design Exploration for Dense Ferroelectric Embedded Non-volatile Memories. CoRR abs/2106.11757 (2021) - [i20]Lillian Pentecost, Alexander Hankin, Marco Donato, Mark Hempstead, Gu-Yeon Wei, David Brooks:
NVMExplorer: A Framework for Cross-Stack Comparisons of Embedded Non-Volatile Memories. CoRR abs/2109.01188 (2021) - [i19]Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Maximilian Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim M. Hazelwood:
Sustainable AI: Environmental Implications, Challenges and Opportunities. CoRR abs/2111.00364 (2021) - [i18]Iulian Brumar, Georgios Zacharopoulos, Yuan Yao, Saketh Rama, Gu-Yeon Wei, David Brooks:
Early DSE and Automatic Generation of Coarse Grained Merged Accelerators. CoRR abs/2111.09222 (2021) - 2020
- [j48]Srivatsan Krishnan
The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines. IEEE Comput. Archit. Lett. 19(1): 38-42 (2020) - [j47]Paul N. Whatmough, Marco Donato, Glenn G. Ko, Sae Kyu Lee, David Brooks, Gu-Yeon Wei:
CHIPKIT: An Agile, Reusable Open-Source Framework for Rapid Test Chip Development. IEEE Micro 40(4): 32-40 (2020) - [j46]Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul N. Whatmough, Gu-Yeon Wei, David Brooks:
SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads. ACM Trans. Archit. Code Optim. 17(4): 39:1-39:26 (2020) - [c123]Thierry Tambe
Algorithm-Hardware Co-Design of Adaptive Floating-Point Encodings for Resilient Deep Learning Inference. DAC 2020: 1-6 - [c122]Antonino Tumeo, Marco Minutoli
Invited: Software Defined Accelerators From Learning Tools Environment. DAC 2020: 1-6 - [c121]David Brooks, Martin M. Frank, Tayfun Gokmen, Udit Gupta, Xiaobo Sharon Hu
Emerging Neural Workloads and Their Impact on Hardware. DATE 2020: 1462-1471 - [c120]Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe
A Scalable Bayesian Inference Accelerator for Unsupervised Learning. Hot Chips Symposium 2020: 1-27 - [c119]Udit Gupta
The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. HPCA 2020: 488-501 - [c118]Marco Minutoli
SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators. ICCAD 2020: 98:1-98:7 - [c117]Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks:
Cross-Stack Workload Characterization of Deep Recommendation Systems. IISWC 2020: 157-168 - [c116]Liu Ke, Udit Gupta, Benjamin Youngjae Cho, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. ISCA 2020: 790-803 - [c115]Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu:
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference. ISCA 2020: 982-995 - [c114]Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, José Miguel Hernández-Lobato, Gu-Yeon Wei:
A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs. ISLPED 2020: 145-150 - [c113]Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. MLSys 2020 - [c112]Yu Wang, Gu-Yeon Wei, David Brooks:
A Systematic Methodology for Analysis of Deep Learning Hardware and Software Platforms. MLSys 2020 - [c111]Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe
A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm. VLSI Circuits 2020: 1-2 - [i17]Udit Gupta, Samuel Hsia, Vikram Saraph, Xiaodong Wang, Brandon Reagen, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks, Carole-Jean Wu:
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference. CoRR abs/2001.02772 (2020) - [i16]Paul N. Whatmough, Marco Donato, Glenn G. Ko, David Brooks, Gu-Yeon Wei:
CHIPKIT: An agile, reusable open-source framework for rapid test chip development. CoRR abs/2001.04504 (2020) - [i15]Brandon Reagen, Wooseok Choi, Yeongil Ko, Vincent T. Lee, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks:
Cheetah: Optimizations and Methods for PrivacyPreserving Inference via Homomorphic Encryption. CoRR abs/2006.00505 (2020) - [i14]Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu, Gu-Yeon Wei, David Brooks:
Cross-Stack Workload Characterization of Deep Recommendation Systems. CoRR abs/2010.05037 (2020) - [i13]Udit Gupta, Young Geun Kim, Sylvia Lee, Jordan Tse, Hsien-Hsin S. Lee, Gu-Yeon Wei, David Brooks, Carole-Jean Wu:
Chasing Carbon: The Elusive Environmental Footprint of Computing. CoRR abs/2011.02839 (2020) - [i12]Thierry Tambe, Coleman Hooper, Lillian Pentecost, En-Yu Yang, Marco Donato, Victor Sanh, Alexander M. Rush, David Brooks, Gu-Yeon Wei:
EdgeBERT: Optimizing On-Chip Inference for Multi-Task NLP. CoRR abs/2011.14203 (2020)
2010 – 2019
- 2019
- [j45]Kshitij Bhardwaj
Determining Optimal Coherency Interface for Many-Accelerator SoCs Using Bayesian Optimization. IEEE Comput. Archit. Lett. 18(2): 119-123 (2019) - [j44]Sae Kyu Lee
A 16-nm Always-On DNN Processor With Adaptive Clocking and Multi-Cycle Banked SRAMs. IEEE J. Solid State Circuits 54(7): 1982-1992 (2019) - [j43]Marco Donato, Lillian Pentecost
MEMTI: Optimizing On-Chip Nonvolatile Storage for Visual Multitask Inference at the Edge. IEEE Micro 39(6): 73-81 (2019) - [j42]Yu Wang, Victor Lee, Gu-Yeon Wei, David M. Brooks:
Predicting New Workload or CPU Performance by Analyzing Public Datasets. ACM Trans. Archit. Code Optim. 15(4): 53:1-53:21 (2019) - [c110]Udit Gupta
MASR: A Modular Accelerator for Sparse RNNs. PACT 2019: 1-14 - [c109]Glenn G. Ko, Yuji Chai, Rob A. Rutenbar
FlexGibbs: Reconfigurable Parallel Gibbs Sampling Accelerator for Structured Graphs. FCCM 2019: 334 - [c108]Glenn G. Ko, Yuji Chai, Rob A. Rutenbar
Accelerating Bayesian Inference on Structured Graphs Using Parallel Gibbs Sampling. FPL 2019: 159-165 - [c107]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:
Machine Learning at Facebook: Understanding Inference at the Edge. HPCA 2019: 331-344 - [c106]Brian Plancher
Application of Approximate Matrix Multiplication to Neural Networks and Distributed SLAM. HPEC 2019: 1-7 - [c105]Yu Emma Wang, Yuhao Zhu, Glenn G. Ko, Brandon Reagen, Gu-Yeon Wei, David Brooks:
Demystifying Bayesian Inference Workloads. ISPASS 2019: 177-189 - [c104]Lillian Pentecost
MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation. MICRO 2019: 769-781 - [c103]Lillian Pentecost
CHAMPVis: Comparative Hierarchical Analysis of Microarchitectural Performance. ProTools@SC 2019: 55-61 - [c102]Paul N. Whatmough, Sae Kyu Lee, Marco Donato, Hsea-Ching Hsueh, Sam Likun Xi, Udit Gupta
A 16nm 25mm2 SoC with a 54.5x Flexibility-Efficiency Range from Dual-Core Arm Cortex-A53 to eFPGA and Cache-Coherent Accelerators. VLSI Circuits 2019: 34- - [i11]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:
The Architectural Implications of Facebook's DNN-based Personalized Recommendation. CoRR abs/1906.03109 (2019) - [i10]Yu Wang, Gu-Yeon Wei, David Brooks:
Benchmarking TPU, GPU, and CPU Platforms for Deep Learning. CoRR abs/1907.10701 (2019) - [i9]Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim M. Hazelwood, David Brooks:
Exploiting Parallelism Opportunities with Deep Learning Frameworks. CoRR abs/1908.04705 (2019) - [i8]Thierry Tambe, En-Yu Yang, Zishen Wan
AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference. CoRR abs/1909.13271 (2019) - [i7]Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. CoRR abs/1910.01500 (2019) - [i6]Siming Ma, David Brooks, Gu-Yeon Wei:
A binary-activation, multi-level weight RNN and training algorithm for processing-in-memory inference with eNVM. CoRR abs/1912.00106 (2019) - [i5]Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul N. Whatmough, Gu-Yeon Wei, David Brooks:
SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads. CoRR abs/1912.04481 (2019) - [i4]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:
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing. CoRR abs/1912.12953 (2019) - 2018
- [j41]Paul N. Whatmough
DNN Engine: A 28-nm Timing-Error Tolerant Sparse Deep Neural Network Processor for IoT Applications. IEEE J. Solid State Circuits 53(9): 2722-2731 (2018) - [j40]Rafael Garibotti
Assisting High-Level Synthesis Improve SpMV Benchmark Through Dynamic Dependence Analysis. IEEE Trans. Circuits Syst. II Express Briefs 65-II(10): 1440-1444 (2018) - [j39]Simon Chaput
An Area-Efficient 8-Bit Single-Ended ADC With Extended Input Voltage Range. IEEE Trans. Circuits Syst. II Express Briefs 65-II(11): 1549-1553 (2018) - [c101]Brandon Reagen, Udit Gupta, Lillian Pentecost
Ares: a framework for quantifying the resilience of deep neural networks. DAC 2018: 17:1-17:6 - [c100]Marco Donato, Brandon Reagen, Lillian Pentecost
On-chip deep neural network storage with multi-level eNVM. DAC 2018: 169:1-169:6 - [c99]Sae Kyu Lee, Paul N. Whatmough, Niamh Mulholland
A Wide Dynamic Range Sparse FC-DNN Processor with Multi-Cycle Banked SRAM Read and Adaptive Clocking in 16nm FinFET. ESSCIRC 2018: 158-161 - [c98]Kim M. Hazelwood, Sarah Bird, David M. Brooks, Soumith Chintala, Utku Diril, Dmytro Dzhulgakov, Mohamed Fawzy, Bill Jia, Yangqing Jia, Aditya Kalro, James Law, Kevin Lee, Jason Lu, Pieter Noordhuis, Misha Smelyanskiy, Liang Xiong, Xiaodong Wang:
Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective. HPCA 2018: 620-629 - [c97]Brandon Reagen, Udit Gupta, Robert Adolf, Michael Mitzenmacher, Alexander M. Rush
Weightless: Lossy weight encoding for deep neural network compression. ICLR (Workshop) 2018 - [c96]Brandon Reagen, Udit Gupta, Bob Adolf, Michael Mitzenmacher, Alexander M. Rush
Weightless: Lossy weight encoding for deep neural network compression. ICML 2018: 4321-4330 - [c95]David M. Brooks:
Co-designed systems for deep learning hardware accelerators. VLSI-DAT 2018: 1 - [i3]Yuhao Zhu, Gu-Yeon Wei, David M. Brooks:
Cloud No Longer a Silver Bullet, Edge to the Rescue. CoRR abs/1802.05943 (2018) - 2017
- [b2]Brandon Reagen, Robert Adolf, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks:
Deep Learning for Computer Architects. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2017, ISBN 978-3-031-00628-9 - [j38]Simone Campanoni, Kevin Brownell, Svilen Kanev, Timothy M. Jones
Automatically accelerating non-numerical programs by architecture-compiler co-design. Commun. ACM 60(12): 88-97 (2017) - [j37]Xin Zhan, Reza Azimi, Svilen Kanev, David M. Brooks, Sherief Reda:
CARB: A C-State Power Management Arbiter for Latency-Critical Workloads. IEEE Comput. Archit. Lett. 16(1): 6-9 (2017) - [j36]Xuan Zhang
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 52(9): 2374-2387 (2017) - [j35]Yuhao Zhu, Vijay Janapa Reddi, Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks:
Cognitive Computing Safety: The New Horizon for Reliability / The Design and Evolution of Deep Learning Workloads. IEEE Micro 37(1): 15-21 (2017) - [j34]David Brooks, John Sartori:
Ultra-Low-Power Processors. IEEE Micro 37(6): 16-19 (2017) - [j33]David Brooks:
2017 International Symposium on Computer Architecture Influential Paper Award. IEEE Micro 37(6): 90-91 (2017) - [j32]Sae Kyu Lee
A 16-Core Voltage-Stacked System With Adaptive Clocking and an Integrated Switched-Capacitor DC-DC Converter. IEEE Trans. Very Large Scale Integr. Syst. 25(4): 1271-1284 (2017) - [c94]Paul N. Whatmough, Sae Kyu Lee, Gu-Yeon Wei, David M. Brooks:
Sub-uJ deep neural networks for embedded applications. ACSSC 2017: 1912-1915 - [c93]Svilen Kanev, Sam Likun Xi, Gu-Yeon Wei, David M. Brooks:
Mallacc: Accelerating Memory Allocation. ASPLOS 2017: 33-45 - [c92]An Zou, Jingwen Leng, Yazhou Zu, Tao Tong, Vijay Janapa Reddi, David M. Brooks, Gu-Yeon Wei, Xuan Zhang
Ivory: Early-Stage Design Space Exploration Tool for Integrated Voltage Regulators. DAC 2017: 1:1-1:6 - [c91]Sreela Kodali, Patrick Hansen, Niamh Mulholland
Applications of Deep Neural Networks for Ultra Low Power IoT. ICCD 2017: 589-592 - [c90]Ramon Bertran
Very Low Voltage (VLV) Design. ICCD 2017: 601-604 - [c89]Rafael Garibotti
Using dynamic dependence analysis to improve the quality of high-level synthesis designs. ISCAS 2017: 1-4 - [c88]Brandon Reagen, José Miguel Hernández-Lobato, Robert Adolf, Michael A. Gelbart, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks:
A case for efficient accelerator design space exploration via Bayesian optimization. ISLPED 2017: 1-6 - [c87]Paul N. Whatmough, Sae Kyu Lee, Hyunkwang Lee, Saketh Rama, David M. Brooks, Gu-Yeon Wei:
14.3 A 28nm SoC with a 1.2GHz 568nJ/prediction sparse deep-neural-network engine with >0.1 timing error rate tolerance for IoT applications. ISSCC 2017: 242-243 - [c86]Simon Chaput, David M. Brooks, Gu-Yeon Wei:
21.5 A 3-to-5V input 100Vpp output 57.7mW 0.42% THD+N highly integrated piezoelectric actuator driver. ISSCC 2017: 360-361 - [c85]Brandon Reagen, Yakun Sophia Shao, Sam Likun Xi, Gu-Yeon Wei, David Brooks:
Methods and infrastructure in the era of accelerator-centric architectures. MWSCAS 2017: 902-905 - [i2]Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David M. Brooks:
Weightless: Lossy Weight Encoding For Deep Neural Network Compression. CoRR abs/1711.04686 (2017) - 2016
- [j31]Tao Tong, Sae Kyu Lee, Xuan Zhang, David M. Brooks, Gu-Yeon Wei:
A Fully Integrated Reconfigurable Switched-Capacitor DC-DC Converter With Four Stacked Output Channels for Voltage Stacking Applications. IEEE J. Solid State Circuits 51(9): 2142-2152 (2016) - [j30]Svilen Kanev, Juan Pablo Darago, Kim M. Hazelwood, Parthasarathy Ranganathan, Tipp Moseley, Gu-Yeon Wei, David M. Brooks:
Profiling a Warehouse-Scale Computer. IEEE Micro 36(3): 54-59 (2016) - [c84]Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks:
Fathom: reference workloads for modern deep learning methods. IISWC 2016: 148-157 - [c83]Brandon Reagen, Paul N. Whatmough, Robert Adolf, Saketh Rama, Hyunkwang Lee, Sae Kyu Lee, José Miguel Hernández-Lobato, Gu-Yeon Wei, David M. Brooks:
Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators. ISCA 2016: 267-278 - [c82]Yakun Sophia Shao, Sam Likun Xi, Vijayalakshmi Srinivasan, Gu-Yeon Wei, David M. Brooks:
Co-designing accelerators and SoC interfaces using gem5-Aladdin. MICRO 2016: 48:1-48:12 - [i1]Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks:
Fathom: Reference Workloads for Modern Deep Learning Methods. CoRR abs/1608.06581 (2016) - 2015
- [b1]Yakun Sophia Shao, David M. Brooks:
Research Infrastructures for Hardware Accelerators. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2015, ISBN 978-3-031-00622-7 - [j29]Yakun Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David M. Brooks:
The Aladdin Approach to Accelerator Design and Modeling. IEEE Micro 35(3): 58-70 (2015) - [c81]Simone Campanoni, Glenn H. Holloway, Gu-Yeon Wei, David M. Brooks:
HELIX-UP: relaxing program semantics to unleash parallelization. CGO 2015: 235-245 - [c80]Mario Lok, Xuan Zhang
A power electronics unit to drive piezoelectric actuators for flying microrobots. CICC 2015: 1-4 - [c79]Sam Likun Xi, Hans M. Jacobson, Pradip Bose, Gu-Yeon Wei, David M. Brooks:
Quantifying sources of error in McPAT and potential impacts on architectural studies. HPCA 2015: 577-589 - [c78]Svilen Kanev, Juan Pablo Darago, Kim M. Hazelwood, Parthasarathy Ranganathan, Tipp Moseley, Gu-Yeon Wei, David M. Brooks:
Profiling a warehouse-scale computer. ISCA 2015: 158-169 - [c77]David M. Brooks:
Addressing the computing technology-capability gap: The coming Golden Age of design. NAS 2015: 233 - [c76]David M. Brooks:
Circuit and system design for robotic flying vehicles. VLSI-DAT 2015: 1 - [c75]Xuan Zhang
A multi-chip system optimized for insect-scale flapping-wing robots. VLSIC 2015: 152- - [c74]Sae Kyu Lee, Tao Tong, Xuan Zhang
A 16-core voltage-stacked system with an integrated switched-capacitor DC-DC converter. VLSIC 2015: 318- - 2014
- [j28]Xuan Zhang
Evaluating Adaptive Clocking for Supply-Noise Resilience in Battery-Powered Aerial Microrobotic System-on-Chip. IEEE Trans. Circuits Syst. I Regul. Pap. 61-I(8): 2309-2317 (2014) - [c73]Michael J. Lyons, Gu-Yeon Wei, David M. Brooks:
Multi-accelerator system development with the ShrinkFit acceleration framework. ICCD 2014: 75-82 - [c72]Svilen Kanev, Kim M. Hazelwood, Gu-Yeon Wei, David M. Brooks:
Tradeoffs between power management and tail latency in warehouse-scale applications. IISWC 2014: 31-40 - [c71]Brandon Reagen, Robert Adolf, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks:
MachSuite: Benchmarks for accelerator design and customized architectures. IISWC 2014: 110-119 - [c70]Yakun Sophia Shao, Brandon Reagen, Gu-Yeon Wei, David M. Brooks:
Aladdin: A pre-RTL, power-performance accelerator simulator enabling large design space exploration of customized architectures. ISCA 2014: 97-108 - [c69]Simone Campanoni, Kevin Brownell, Svilen Kanev, Timothy M. Jones
HELIX-RC: An architecture-compiler co-design for automatic parallelization of irregular programs. ISCA 2014: 217-228 - 2013
- [j27]Michael J. Lyons, Gu-Yeon Wei, David M. Brooks:
Shrink-Fit: A Framework for Flexible Accelerator Sizing. IEEE Comput. Archit. Lett. 12(1): 17-20 (2013) - [c68]Tao Tong, Xuan Zhang
A fully integrated battery-connected switched-capacitor 4: 1 voltage regulator with 70% peak efficiency using bottom-plate charge recycling. CICC 2013: 1-4 - [c67]Xuan Zhang
Supply-noise resilient adaptive clocking for battery-powered aerial microrobotic System-on-Chip in 40nm CMOS. CICC 2013: 1-4 - [c66]Xuan Zhang
Characterizing and evaluating voltage noise in multi-core near-threshold processors. ISLPED 2013: 82-87 - [c65]Yakun Sophia Shao, David M. Brooks:
Energy characterization and instruction-level energy model of Intel's Xeon Phi processor. ISLPED 2013: 389-394 - [c64]Brandon Reagen, Yakun Sophia Shao, Gu-Yeon Wei, David M. Brooks:
Quantifying acceleration: Power/performance trade-offs of application kernels in hardware. ISLPED 2013: 395-400 - [c63]Yakun Sophia Shao, David M. Brooks:
ISA-independent workload characterization and its implications for specialized architectures. ISPASS 2013: 245-255 - 2012
- [j26]Wonyoung Kim, David M. Brooks, Gu-Yeon Wei:
A Fully-Integrated 3-Level DC-DC Converter for Nanosecond-Scale DVFS. IEEE J. Solid State Circuits 47(1): 206-219 (2012) - [j25]Simone Campanoni, Timothy M. Jones
Helix: Making the Extraction of Thread-Level Parallelism Mainstream. IEEE Micro 32(4): 8-18 (2012) - [j24]Michael J. Lyons, Mark Hempstead, Gu-Yeon Wei, David M. Brooks:
The accelerator store: A shared memory framework for accelerator-based systems. ACM Trans. Archit. Code Optim. 8(4): 48:1-48:22 (2012) - [c62]Simone Campanoni, Timothy M. Jones
HELIX: automatic parallelization of irregular programs for chip multiprocessing. CGO 2012: 84-93 - [c61]Simone Campanoni, Timothy M. Jones
The HELIX project: overview and directions. DAC 2012: 277-282 - [c60]Svilen Kanev, Gu-Yeon Wei, David M. Brooks:
XIOSim: power-performance modeling of mobile x86 cores. ISLPED 2012: 267-272 - [c59]Sae Kyu Lee, David M. Brooks, Gu-Yeon Wei:
Evaluation of voltage stacking for near-threshold multicore computing. ISLPED 2012: 373-378 - 2011
- [j23]Mark Hempstead, David M. Brooks, Gu-Yeon Wei:
An Accelerator-Based Wireless Sensor Network Processor in 130 nm CMOS. IEEE J. Emerg. Sel. Topics Circuits Syst. 1(2): 193-202 (2011) - [j22]Vijay Janapa Reddi, Svilen Kanev, Wonyoung Kim, Simone Campanoni, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
Voltage Noise in Production Processors. IEEE Micro 31(1): 20-28 (2011) - [j21]David M. Brooks:
CPUs, GPUs, and Hybrid Computing. IEEE Micro 31(5): 4-6 (2011) - [j20]Vijay Janapa Reddi, David M. Brooks:
Resilient Architectures via Collaborative Design: Maximizing Commodity Processor Performance in the Presence of Variations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 30(10): 1429-1445 (2011) - [j19]Kevin Brownell, Ali Durlov Khan, Gu-Yeon Wei, David M. Brooks:
Automating Design of Voltage Interpolation to Address Process Variations. IEEE Trans. Very Large Scale Integr. Syst. 19(3): 383-396 (2011) - [c58]David M. Brooks:
The alarms project: A hardware/software approach to addressing parameter variations. ASP-DAC 2011: 291 - [c57]Peter Bailis, Vijay Janapa Reddi, Sanjay Gandhi, David M. Brooks, Margo I. Seltzer:
Dimetrodon: processor-level preventive thermal management via idle cycle injection. DAC 2011: 89-94 - [c56]Javier Lira, Carlos Molina, David M. Brooks, Antonio González
Implementing a hybrid SRAM / eDRAM NUCA architecture. HiPC 2011: 1-10 - [c55]Krishna K. Rangan, Michael D. Powell, Gu-Yeon Wei, David M. Brooks:
Achieving uniform performance and maximizing throughput in the presence of heterogeneity. HPCA 2011: 3-14 - [c54]Pierre-Emile Duhamel, Judson Porter, Benjamin M. Finio, Geoffrey L. Barrows, David M. Brooks, Gu-Yeon Wei, Robert J. Wood:
Hardware in the loop for optical flow sensing in a robotic bee. IROS 2011: 1099-1106 - [c53]Wonyoung Kim, David M. Brooks, Gu-Yeon Wei:
A fully-integrated 3-level DC/DC converter for nanosecond-scale DVS with fast shunt regulation. ISSCC 2011: 268-270 - 2010
- [j18]Michael J. Lyons, Mark Hempstead, Gu-Yeon Wei, David M. Brooks:
The Accelerator Store framework for high-performance, low-power accelerator-based systems. IEEE Comput. Archit. Lett. 9(2): 53-56 (2010) - [j17]Vijay Janapa Reddi, Meeta Sharma Gupta, Glenn H. Holloway, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
Predicting Voltage Droops Using Recurring Program and Microarchitectural Event Activity. IEEE Micro 30(1): 110 (2010) - [j16]Benton H. Calhoun, David M. Brooks:
Can Subthreshold and Near-Threshold Circuits Go Mainstream? IEEE Micro 30(4): 80-85 (2010) - [j15]Benjamin C. Lee, David M. Brooks:
Applied inference: Case studies in microarchitectural design. ACM Trans. Archit. Code Optim. 7(2): 8:1-8:37 (2010) - [j14]Vijay Janapa Reddi, Simone Campanoni, Meeta Sharma Gupta, Michael D. Smith, Gu-Yeon Wei, David M. Brooks, Kim M. Hazelwood:
Eliminating voltage emergencies via software-guided code transformations. ACM Trans. Archit. Code Optim. 7(2): 12:1-12:28 (2010) - [c52]Vijay Janapa Reddi, Svilen Kanev, Wonyoung Kim, Simone Campanoni, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
Voltage Smoothing: Characterizing and Mitigating Voltage Noise in Production Processors via Software-Guided Thread Scheduling. MICRO 2010: 77-88
2000 – 2009
- 2009
- [j13]Xiaoyao Liang, Gu-Yeon Wei, David M. Brooks:
Revival: A Variation-Tolerant Architecture Using Voltage Interpolation and Variable Latency. IEEE Micro 29(1): 127-138 (2009) - [j12]Lukasz Strozek, David M. Brooks:
Energy- and area-efficient architectures through application clustering and architectural heterogeneity. ACM Trans. Archit. Code Optim. 6(1): 4:1-4:31 (2009) - [c51]Mark Hempstead, Gu-Yeon Wei, David M. Brooks:
An accelerator-based wireless sensor network processor in 130nm CMOS. CASES 2009: 215-222 - [c50]Vijay Janapa Reddi, Simone Campanoni, Meeta Sharma Gupta, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
Software-assisted hardware reliability: abstracting circuit-level challenges to the software stack. DAC 2009: 788-793 - [c49]Meeta Sharma Gupta, Vijay Janapa Reddi, Glenn H. Holloway, Gu-Yeon Wei, David M. Brooks:
An event-guided approach to reducing voltage noise in processors. DATE 2009: 160-165 - [c48]Vijay Janapa Reddi, Meeta Sharma Gupta, Glenn H. Holloway, Gu-Yeon Wei, Michael D. Smith, David M. Brooks:
Voltage emergency prediction: Using signatures to reduce operating margins. HPCA 2009: 18-29 - [c47]Xiaoyao Liang, Benjamin C. Lee, Gu-Yeon Wei, David M. Brooks:
Design and test strategies for microarchitectural post-fabrication tuning. ICCD 2009: 84-90 - [c46]Kristen Lovin, Benjamin C. Lee, Xiaoyao Liang, David M. Brooks, Gu-Yeon Wei:
Empirical performance models for 3T1D memories. ICCD 2009: 398-403 - [c45]Krishna K. Rangan, Gu-Yeon Wei, David M. Brooks:
Thread motion: fine-grained power management for multi-core systems. ISCA 2009: 302-313 - [c44]Michael J. Lyons, David M. Brooks:
The design of a bloom filter hardware accelerator for ultra low power systems. ISLPED 2009: 371-376 - [c43]Kevin Brownell, Ali Durlov Khan, David M. Brooks, Gu-Yeon Wei:
Place and route considerations for voltage interpolated designs. ISQED 2009: 594-600 - [c42]Meeta Sharma Gupta, Jude A. Rivers, Pradip Bose, Gu-Yeon Wei, David M. Brooks:
Tribeca: design for PVT variations with local recovery and fine-grained adaptation. MICRO 2009: 435-446 - 2008
- [j11]Mark Hempstead, Michael J. Lyons, David M. Brooks, Gu-Yeon Wei:
Survey of Hardware Systems for Wireless Sensor Networks. J. Low Power Electron. 4(1): 11-20 (2008) - [j10]Sarita V. Adve, David M. Brooks, Craig B. Zilles:
Guest Editors' Introduction: Top Picks from the Computer Architecture Conferences of 2007. IEEE Micro 28(1): 8-11 (2008) - [j9]Xiaoyao Liang, Ramon Canal, Gu-Yeon Wei, David M. Brooks:
Replacing 6T SRAMs with 3T1D DRAMs in the L1 Data Cache to Combat Process Variability. IEEE Micro 28(1): 60-68 (2008) - [c41]Benjamin C. Lee, David M. Brooks:
Efficiency trends and limits from comprehensive microarchitectural adaptivity. ASPLOS 2008: 36-47 - [c40]Wonyoung Kim, Meeta Sharma Gupta, Gu-Yeon Wei, David M. Brooks:
System level analysis of fast, per-core DVFS using on-chip switching regulators. HPCA 2008: 123-134 - [c39]Benjamin C. Lee, David M. Brooks:
Roughness of microarchitectural design topologies and its implications for optimization. HPCA 2008: 240-251 - [c38]Meeta Sharma Gupta, Krishna K. Rangan, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
DeCoR: A Delayed Commit and Rollback mechanism for handling inductive noise in processors. HPCA 2008: 381-392 - [c37]Kevin Brownell, Gu-Yeon Wei, David M. Brooks:
Evaluation of voltage interpolation to address process variations. ICCAD 2008: 529-536 - [c36]Xiaoyao Liang, Gu-Yeon Wei, David M. Brooks:
ReVIVaL: A Variation-Tolerant Architecture Using Voltage Interpolation and Variable Latency. ISCA 2008: 191-202 - [c35]Mark Hempstead, Gu-Yeon Wei, David M. Brooks:
System design considerations for sensor network applications. ISCAS 2008: 2566-2569 - [c34]Gu-Yeon Wei, David M. Brooks, Ali Durlov Khan, Xiaoyao Liang:
Instruction-driven clock scheduling with glitch mitigation. ISLPED 2008: 357-362 - [c33]Xiaoyao Liang, David M. Brooks, Gu-Yeon Wei:
A Process-Variation-Tolerant Floating-Point Unit with Voltage Interpolation and Variable Latency. ISSCC 2008: 404-405 - [c32]Benjamin C. Lee, Jamison D. Collins, Hong Wang, David M. Brooks:
CPR: Composable performance regression for scalable multiprocessor models. MICRO 2008: 270-281 - 2007
- [j8]David M. Brooks, Robert P. Dick, Russ Joseph, Li Shang:
Power, Thermal, and Reliability Modeling in Nanometer-Scale Microprocessors. IEEE Micro 27(3): 49-62 (2007) - [j7]Benjamin C. Lee, David M. Brooks:
Spatial Sampling and Regression Strategies. IEEE Micro 27(3): 74-93 (2007) - [c31]Meeta Sharma Gupta, Jarod L. Oatley, Russ Joseph, Gu-Yeon Wei, David M. Brooks:
Understanding voltage variations in chip multiprocessors using a distributed power-delivery network. DATE 2007: 624-629 - [c30]Benjamin C. Lee, David M. Brooks:
Illustrative Design Space Studies with Microarchitectural Regression Models. HPCA 2007: 340-351 - [c29]Xiaoyao Liang, Kerem Turgay, David M. Brooks:
Architectural power models for SRAM and CAM structures based on hybrid analytical/empirical techniques. ICCAD 2007: 824-830 - [c28]Meeta Sharma Gupta, Krishna K. Rangan, Michael D. Smith, Gu-Yeon Wei, David M. Brooks:
Towards a software approach to mitigate voltage emergencies. ISLPED 2007: 123-128 - [c27]Xiaoyao Liang, Ramon Canal, Gu-Yeon Wei, David M. Brooks:
Process Variation Tolerant 3T1D-Based Cache Architectures. MICRO 2007: 15-26 - [c26]Benjamin C. Lee, David M. Brooks, Bronis R. de Supinski, Martin Schulz
Methods of inference and learning for performance modeling of parallel applications. PPoPP 2007: 249-258 - 2006
- [j6]Qiang Wu, Margaret Martonosi, Douglas W. Clark, Vijay Janapa Reddi, Dan Connors, Youfeng Wu, Jin Lee, David M. Brooks:
Dynamic-Compiler-Driven Control for Microprocessor Energy and Performance. IEEE Micro 26(1): 119-129 (2006) - [c25]Benjamin C. Lee, David M. Brooks:
Accurate and efficient regression modeling for microarchitectural performance and power prediction. ASPLOS 2006: 185-194 - [c24]Lukasz Strozek, David M. Brooks:
Efficient architectures through application clustering and architectural heterogeneity. CASES 2006: 190-200 - [c23]Mark Hempstead, Gu-Yeon Wei, David M. Brooks:
Architecture and circuit techniques for low-throughput, energy-constrained systems across technology generations. CASES 2006: 368-378 - [c22]Yingmin Li, Benjamin C. Lee, David M. Brooks, Zhigang Hu, Kevin Skadron
CMP design space exploration subject to physical constraints. HPCA 2006: 17-28 - [c21]Xiaoyao Liang, David M. Brooks:
Microarchitecture parameter selection to optimize system performance under process variation. ICCAD 2006: 429-436 - [c20]Wai-Chi Fang, Sharon Kedar, Susan Owen, Gu-Yeon Wei, David M. Brooks, Jonathan Lees
System-on-Chip Architecture Design for Intelligent Sensor Networks. IIH-MSP 2006: 579-582 - [c19]Xiaoyao Liang, David M. Brooks:
Mitigating the Impact of Process Variations on Processor Register Files and Execution Units. MICRO 2006: 504-514 - 2005
- [c18]Yingmin Li, David M. Brooks, Zhigang Hu, Kevin Skadron
Performance, Energy, and Thermal Considerations for SMT and CMP Architectures. HPCA 2005: 71-82 - [c17]Mark Hempstead, Nikhil Tripathi, Patrick Mauro, Gu-Yeon Wei, David M. Brooks:
An Ultra Low Power System Architecture for Sensor Network Applications. ISCA 2005: 208-219 - [c16]Yingmin Li, Mark Hempstead, Patrick Mauro, David M. Brooks, Zhigang Hu, Kevin Skadron
Power and thermal effects of SRAM vs. Latch-Mux design styles and clock gating choices. ISLPED 2005: 173-178 - [c15]Qiang Wu, Margaret Martonosi, Douglas W. Clark, Vijay Janapa Reddi, Dan Connors, Youfeng Wu, Jin Lee, David M. Brooks:
A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance. MICRO 2005: 271-282 - 2004
- [j5]David M. Brooks, Pradip Bose, Margaret Martonosi:
Power-performance simulation: design and validation strategies. SIGMETRICS Perform. Evaluation Rev. 31(4): 13-18 (2004) - [j4]Victor V. Zyuban, David M. Brooks, Viji Srinivasan, Michael Gschwind, Pradip Bose, Philip N. Strenski, Philip G. Emma:
Integrated Analysis of Power and Performance for Pipelined Microprocessors. IEEE Trans. Computers 53(8): 1004-1016 (2004) - [c14]Yau Chin, John Sheu, David M. Brooks:
Evaluating Techniques for Exploiting Instruction Slack. ICCD 2004: 375-378 - [c13]Yingmin Li, David M. Brooks, Zhigang Hu, Kevin Skadron
Understanding the energy efficiency of simultaneous multithreading. ISLPED 2004: 44-49 - [c12]Kim M. Hazelwood, David M. Brooks:
Eliminating voltage emergencies via microarchitectural voltage control feedback and dynamic optimization. ISLPED 2004: 326-331 - [c11]Mark Hempstead, Matt Welsh, David M. Brooks:
TinyBench: The Case For A Standardized Benchmark Suite for TinyOS Based Wireless Sensor Network Devices. LCN 2004: 585-586 - 2003
- [j3]David M. Brooks, Pradip Bose, Viji Srinivasan, Michael Gschwind, Philip G. Emma, Michael G. Rosenfield:
New methodology for early-stage, microarchitecture-level power-performance analysis of microprocessors. IBM J. Res. Dev. 47(5-6): 653-670 (2003) - [c10]Russ Joseph, David M. Brooks, Margaret Martonosi:
Control Techniques to Eliminate Voltage Emergencies in High Performance Processors. HPCA 2003: 79-90 - 2002
- [c9]Viji Srinivasan, David M. Brooks, Michael Gschwind, Pradip Bose, Victor V. Zyuban, Philip N. Strenski, Philip G. Emma:
Optimizing pipelines for power and performance. MICRO 2002: 333-344 - [c8]Pradip Bose, David M. Brooks, Alper Buyuktosunoglu, Peter W. Cook, K. Das, Philip G. Emma, Michael Gschwind, Hans M. Jacobson, Tejas Karkhanis, Prabhakar Kudva, Stanley Schuster, James E. Smith, Viji Srinivasan, Victor V. Zyuban, David H. Albonesi, Sandhya Dwarkadas:
Early-Stage Definition of LPX: A Low Power Issue-Execute Processor. PACS 2002: 1-17 - 2001
- [c7]Alper Buyuktosunoglu, David H. Albonesi, Stanley Schuster, David M. Brooks, Pradip Bose, Peter W. Cook:
A circuit level implementation of an adaptive issue queue for power-aware microprocessors. ACM Great Lakes Symposium on VLSI 2001: 73-78 - [c6]David M. Brooks, Margaret Martonosi:
Dynamic Thermal Management for High-Performance Microprocessors. HPCA 2001: 171-182 - 2000
- [j2]David M. Brooks, Pradip Bose, Stanley Schuster, Hans M. Jacobson, Prabhakar Kudva, Alper Buyuktosunoglu, John-David Wellman, Victor V. Zyuban, Manish Gupta, Peter W. Cook:
Power-Aware Microarchitecture: Design and Modeling Challenges for Next-Generation Microprocessors. IEEE Micro 20(6): 26-44 (2000) - [j1]David M. Brooks, Margaret Martonosi:
Value-based clock gating and operation packing: dynamic strategies for improving processor power and performance. ACM Trans. Comput. Syst. 18(2): 89-126 (2000) - [c5]David M. Brooks, Vivek Tiwari, Margaret Martonosi:
Wattch: a framework for architectural-level power analysis and optimizations. ISCA 2000: 83-94 - [c4]Alper Buyuktosunoglu, Stanley Schuster, David M. Brooks, Pradip Bose, Peter W. Cook, David H. Albonesi:
An Adaptive Issue Queue for Reduced Power at High Performance. PACS 2000: 25-39 - [c3]David M. Brooks, Margaret Martonosi, John-David Wellman, Pradip Bose:
Power-Performance Modeling and Tradeoff Analysis for a High End Microprocessor. PACS 2000: 126-136
1990 – 1999
- 1999
- [c2]David M. Brooks, Margaret Martonosi:
Implementing Application-Specific Cache-Coherence Protocols in Configurable Hardware. CANPC 1999: 181-195 - [c1]David M. Brooks, Margaret Martonosi:
Dynamically Exploiting Narrow Width Operands to Improve Processor Power and Performance. HPCA 1999: 13-22
Coauthor Index
Hsien-Hsin S. Lee
aka: Hsien-Hsin Sean Lee
aka: Hsien-Hsin Sean Lee
[j61] [c166] [c165] [c164] [c163] [c162] [c161] [c160] [c159] [c158] [c157] [i49] [i48] [i47] [i46] [j60] [j59] [j58] [j57] [j56] [j55] [j54] [c155] [c154] [c153] [c152] [c151] [c150] [c149] [c148] [c147] [i45] [i44] [i43] [i41] [i40] [i39] [i38] [i37] [i36] [i34] [i33] [j53] [j52] [j51] [j50] [c146] [c145] [c144] [c143] [c142] [c141] [c140] [c139] [c138] [c137] [c136] [i32] [i30] [i29] [i28] [i27] [c134] [c133] [c132] [c131] [c130] [c129] [c128] [c127] [c126] [c125] [c124] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [i18] [j48] [j47] [j46] [c123] [c122] [c120] [c118] [c117] [c115] [c114] [c113] [c112] [c111] [i17] [i16] [i15] [i14] [i13] [i12] [j45] [j44] [j43] [j42] [c110] [c109] [c108] [c105] [c104] [c103] [c102] [i10] [i8] [i7] [i6] [i5] [j41] [j40] [j39] [c101] [c100] [c99] [c97] [c96] [i3] [b2] [j38] [j36] [j35] [j32] [c94] [c93] [c92] [c91] [c90] [c89] [c88] [c87] [c86] [c85] [i2] [j31] [j30] [c84] [c83] [c82] [i1] [j29] [c81] [c80] [c79] [c78] [c75] [c74] [j28] [c73] [c72] [c71] [c70] [c69] [j27] [c68] [c67] [c66] [c64] [j26] [j25] [j24] [c62] [c61] [c60] [c59] [j23] [j22] [j19] [c55] [c54] [c53] [j18] [j17] [j14] [c52] [j13] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c43] [c42] [j11] [j9] [c40] [c38] [c37] [c36] [c35] [c34] [c33] [c31] [c28] [c27] [c23] [c20] [c17]
Jeff Zhang 0001
aka: Jeff Jun Zhang
aka: Jeff Jun Zhang
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