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Paul N Whatmough
Paul N Whatmough
Arm ML Research, Harvard University
Verified email at arm.com - Homepage
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Cited by
Year
Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators
B Reagen, PN Whatmough, R Adolf, S Rama, H Lee, SK Lee, ...
International Symposium on Computer Architecture (ISCA), Proceedings of the …, 2016
6172016
Scale-Sim: Systolic CNN Accelerator Simulator
A Samajdar, Y Zhu, PN Whatmough, M Mattina, T Krishna
arXiv preprint arXiv:1811.02883, 2018
2542018
Ares: A framework for quantifying the resilience of deep neural networks
B Reagen, U Gupta, L Pentecost, PN Whatmough, SK Lee, N Mulholland, ...
2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), 1-6, 2018
2252018
A 28nm SoC with a 1.2 GHz 568nJ/prediction Sparse Deep-Neural-Network Engine with >0.1 Timing Error Rate Tolerance for IoT Applications
PN Whatmough, SK Lee, H Lee, S Rama, D Brooks, GY Wei
Solid-State Circuits Conference (ISSCC), 2017 IEEE International, 242-243, 2017
1792017
Federated learning based on dynamic regularization
DAE Acar, Y Zhao, RM Navarro, M Mattina, PN Whatmough, V Saligrama
arXiv preprint arXiv:2111.04263, 2021
1712021
VLSI Architecture for a Reconfigurable Spectrally Efficient FDM Baseband Transmitter
PN Whatmough, MR Perrett, S Isam, I Darwazeh
IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) 59 (5 …, 2012
1062012
VLSI Architecture for a Reconfigurable Spectrally Efficient FDM Baseband Transmitter
PN Whatmough, MR Perrett, S Isam, I Darwazeh
Circuits and Systems (ISCAS), 2011 IEEE International Symposium on, 1688-1691, 2011
1062011
MicroNets: Neural Network Architectures for Deploying tinyML Applications on Commodity Microcontrollers
C Banbury, C Zhou, I Fedorov, R Matas, U Thakker, D Gope, ...
Proceedings of Machine Learning and Systems 3, 2021
1052021
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
I Fedorov, RP Adams, M Mattina, P Whatmough
Advances in Neural Information Processing Systems (NeurIPS), 4978-4990, 2019
982019
DNN ENGINE: A 28-nm Timing-Error Tolerant Sparse Deep Neural Network Processor for IoT Applications
PN Whatmough, SK Lee, D Brooks, GY Wei
IEEE Journal of Solid-State Circuits (JSSC) 53 (9), 2722-2731, 2018
792018
Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision
Y Zhu, A Samajdar, M Mattina, P Whatmough
45th Annual International Symposium on Computer Architecture (ISCA), 547-560, 2018
782018
Circuit-Level Timing Error Tolerance for Low-Power DSP Filters and Transforms
PN Whatmough, S Das, DM Bull, I Darwazeh
IEEE Transactions on Very Large Scale Integration (VLSI) Systems 21 (6), 989-999, 2013
722013
A case for efficient accelerator design space exploration via bayesian optimization
B Reagen, JM Hernández-Lobato, R Adolf, M Gelbart, P Whatmough, ...
2017 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2017
702017
A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim
A Samajdar, JM Joseph, Y Zhu, P Whatmough, M Mattina, T Krishna
IEEE International Symposium on Performance Analysis of Systems and Software …, 2020
612020
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
PN Whatmough, C Zhou, P Hansen, SK Venkataramanaiah, J Seo, ...
The 2nd Conference on Systems and Machine Learning (SysML) 2019, Palo Alto …, 2019
532019
TinyLSTMs: Efficient neural speech enhancement for hearing aids
I Fedorov, M Stamenovic, C Jensen, LC Yang, A Mandell, Y Gan, ...
arXiv preprint arXiv:2005.11138, 2020
502020
A Low-Power 1GHz Razor FIR Accelerator with Time-Borrow Tracking Pipeline and Approximate Error Correction in 65nm CMOS
PN Whatmough, S Das, DM Bull
IEEE Journal of Solid-State Circuits (JSSC) 49 (1), 84-94, 2014
492014
A Low-Power 1GHz Razor FIR Accelerator with Time-Borrow Tracking Pipeline and Approximate Error Correction in 65nm CMOS
PN Whatmough, S Das, DM Bull
International Solid-State Circuits Conference (ISSCC), Digest of Technical …, 2013
492013
Deep learning for computer architects
B Reagen, R Adolf, PN Whatmough, GY Wei, D Brooks
Synthesis Lectures on Computer Architecture 12 (4), 1-123, 2017
432017
On-Chip Memory Technology Design Space Explorations for Mobile Deep Neural Network Accelerators
H Li, M Bhargava, PN Whatmough, HSP Wong
56th Annual Design Automation Conference (DAC) 2019, 131, 2019
412019
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