Paul N. Whatmough

121 papers A* 16A 9B 6C 4Misc 1Journal 66Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dissecting Quantization Error: A Concentration-Alignment Perspective. CoRR Marco Federici, Boris van Breugel, Paul N. Whatmough, Markus Nagel
2026	J	`jnl`	Efficient Reasoning on the Edge. CoRR Yelysei Bondarenko, Thomas Hehn, Rob Hesselink, Romain Lepert, Fabio Valerio Massoli, Evgeny Mironov, Leyla Mirvakhabova, Tribhuvanesh Orekondy, Spyridon Stasis, Andrey Kuzmin, Anna Kuzina, Markus Nagel, Ankita Nayak, Corrado Rainone, Ork de Rooij, Paul N. Whatmough, Arash Behboodi, Babak Ehteshami Bejnordi
2026	J	`jnl`	Leech Lattice Vector Quantization for Efficient LLM Compression. CoRR Tycho F. A. van der Ouderaa, Mart van Baalen, Paul N. Whatmough, Markus Nagel
2025	J	`jnl`	Dirichlet-Prior Shaping: Guiding Expert Specialization in Upcycled MoEs. CoRR Leyla Mirvakhabova, Babak Ehteshami Bejnordi, Gaurav Kumar, Hanxue Liang, Wanru Zhao, Paul N. Whatmough
2025	—	`conf`	Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking. MLSys Marco Federici, Davide Belli, Mart van Baalen, Amir Jalalirad, Andrii Skliar, Bence Major, Markus Nagel, Paul N. Whatmough
2025	J	`jnl`	FPTQuant: Function-Preserving Transforms for LLM Quantization. CoRR Boris van Breugel, Yelysei Bondarenko, Paul N. Whatmough, Markus Nagel
2025	J	`jnl`	HadaNorm: Diffusion Transformer Quantization through Mean-Centered Transformations. CoRR Marco Federici, Riccardo Del Chiaro, Boris van Breugel, Paul N. Whatmough, Markus Nagel
2025	J	`jnl`	KaVa: Latent Reasoning via Compressed KV-Cache Distillation. CoRR Anna Kuzina, Maciej Pioro, Paul N. Whatmough, Babak Ehteshami Bejnordi
2025	J	`jnl`	Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference. Trans. Mach. Learn. Res. Andrii Skliar, Ties van Rozendaal, Romain Lepert, Todor Boinovski, Mart van Baalen, Markus Nagel, Paul N. Whatmough, Babak Ehteshami Bejnordi
2025	J	`jnl`	ObjectAlign: Neuro-Symbolic Object Consistency Verification and Correction. CoRR Mustafa Munir, Harsh Goel, Xiwen Wei, Minkyu Choi, Sahil Shah, Kartikeya Bhardwaj, Paul N. Whatmough, Sandeep Chinchali, Radu Marculescu
2025	J	`jnl`	PipeFlow: Pipelined Processing and Motion-Aware Frame Selection for Long-Form Video Editing. CoRR Mustafa Munir, Md Mostafijur Rahman, Kartikeya Bhardwaj, Paul N. Whatmough, Radu Marculescu
2025	J	`jnl`	STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization. CoRR Marco Federici, Riccardo Del Chiaro, Boris van Breugel, Paul N. Whatmough, Markus Nagel
2024	B	`conf`	Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator. ISPASS Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhou, Paul N. Whatmough, Yuhao Zhu
2024	J	`jnl`	Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator. CoRR Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhu, Paul N. Whatmough, Yuhao Zhu
2024	J	`jnl`	Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking. CoRR Marco Federici, Davide Belli, Mart van Baalen, Amir Jalalirad, Andrii Skliar, Bence Major, Markus Nagel, Paul N. Whatmough
2024	J	`jnl`	GPTVQ: The Blessing of Dimensionality for LLM Quantization. CoRR Mart van Baalen, Andrey Kuzmin, Markus Nagel, Peter Couperus, Cédric Bastoul, Eric Mahurin, Tijmen Blankevoort, Paul N. Whatmough
2024	J	`jnl`	Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference. CoRR Andrii Skliar, Ties van Rozendaal, Romain Lepert, Todor Boinovski, Mart van Baalen, Markus Nagel, Paul N. Whatmough, Babak Ehteshami Bejnordi
2024	J	`jnl`	Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters. CoRR Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Viswanath Ganapathy, Rafael Esteves, Shreya Kadambi, Shubhankar Borse, Paul N. Whatmough, Risheek Garrepalli, Mart van Baalen, Harris Teague, Markus Nagel
2024	A*	`conf`	Sparse High Rank Adapters. NeurIPS Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Viswanath Ganapathy, Shreya Kadambi, Rafael Esteves, Shubhankar Borse, Paul N. Whatmough, Risheek Garrepalli, Mart van Baalen, Harris Teague, Markus Nagel
2024	J	`jnl`	Sparse High Rank Adapters. CoRR Kartikeya Bhardwaj, Nilesh Prasad Pandey, Sweta Priyadarshi, Viswanath Ganapathy, Rafael Esteves, Shreya Kadambi, Shubhankar Borse, Paul N. Whatmough, Risheek Garrepalli, Mart van Baalen, Harris Teague, Markus Nagel
2023	—	`conf`	A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. ISSCC Thierry Tambe, Jeff Zhang, Coleman Hooper, Tianyu Jia, Paul N. Whatmough, Joseph Zuckerman, Maico Cassel dos Santos, Erik Jens Loscalzo, Davide Giri, Kenneth L. Shepard, Luca P. Carloni, Alexander M. Rush, David Brooks, Gu-Yeon Wei
2023	J	`jnl`	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 Thierry Tambe, En-Yu Yang, Glenn G. Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N. Whatmough, Alexander M. Rush, David Brooks, Gu-Yeon Wei
2023	A	`conf`	AR-PIM: An Adaptive-Range Processing-in-Memory Architecture. ISLPED Teyuh Chou, Fernando García-Redondo, Paul N. Whatmough, Zhengya Zhang
2023	A*	`conf`	Efficient Edge Inference by Selective Query. ICLR Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama
2023	A	`conf`	Fast and Accurate: Video Enhancement Using Sparse Depth. WACV Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu
2023	J	`jnl`	PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices. CoRR Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough
2022	A*	`conf`	Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. MICRO Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Sabrina M. Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
2022	A	`conf`	Braum: Analyzing and Protecting Autonomous Machine Software Stack. ISSRE Yiming Gan, Paul N. Whatmough, Jingwen Leng, Bo Yu, Shaoshan Liu, Yuhao Zhu
2022	J	`jnl`	ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator. IEEE Micro Chuteng Zhou, Fernando García-Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough
2022	J	`jnl`	Restructurable Activation Networks. CoRR Kartikeya Bhardwaj, James Ward, Caleb Tung, Dibakar Gope, Lingchuan Meng, Igor Fedorov, Alex Chalfin, Paul N. Whatmough, Danny Loh
2022	A*	`conf`	S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration. HPCA Zhi Gang Liu, Paul N. Whatmough, Yuhao Zhu, Matthew Mattina
2022	J	`jnl`	SMIV: A 16-nm 25-mm² SoC for IoT With Arm Cortex-A53, eFPGA, and Coherent Accelerators. IEEE J. Solid State Circuits Sae Kyu Lee, Paul N. Whatmough, Marco Donato, Glenn G. Ko, David Brooks, Gu-Yeon Wei
2022	A	`conf`	Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. DATE Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh
2022	J	`jnl`	Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators. CoRR Abhishek Tyagi, Yiming Gan, Shaoshan Liu, Bo Yu, Paul N. Whatmough, Yuhao Zhu
2022	A*	`conf`	UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units. NeurIPS Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2022	J	`jnl`	UDC: Unified DNAS for Compressible TinyML Models. CoRR Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
2021	—	`conf`	9.8 A 25mm ISSCC Thierry Tambe, En-Yu Yang, Glenn G. Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N. Whatmough, Alexander M. Rush, David Brooks, Gu-Yeon Wei
2021	J	`jnl`	A LiDAR-Guided Framework for Video Enhancement. CoRR Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu
2021	J	`jnl`	AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator. CoRR Chuteng Zhou, Fernando García-Redondo, Julian Büchel, Irem Boybat, Xavier Timoneda Comas, S. R. Nandakumar, Shidhartha Das, Abu Sebastian, Manuel Le Gallo, Paul N. Whatmough
2021	A*	`conf`	Debiasing Model Updates for Improving Personalized Federated Training. ICML Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
2021	—	`conf`	Doping: A technique for Extreme Compression of LSTM Models using Sparse Structured Additive Matrices. MLSys Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
2021	J	`jnl`	Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices. CoRR Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
2021	A*	`conf`	EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. MICRO Thierry Tambe, Coleman Hooper, Lillian Pentecost, Tianyu Jia, En-Yu Yang, Marco Donato, Victor Sanh, Paul N. Whatmough, Alexander M. Rush, David Brooks, Gu-Yeon Wei
2021	A*	`conf`	Federated Learning Based on Dynamic Regularization. ICLR Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
2021	J	`jnl`	Federated Learning Based on Dynamic Regularization. CoRR Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
2021	B	`conf`	FixyFPGA: Efficient FPGA Accelerator for Deep Neural Networks with High Element-Wise Sparsity and without External Memory Access. FPL Jian Meng, Shreyas Kolala Venkataramanaiah, Chuteng Zhou, Patrick Hansen, Paul N. Whatmough, Jae-sun Seo
2021	J	`jnl`	Information contraction in noisy binary neural networks and its implications. CoRR Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
2021	J	`jnl`	Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots. CoRR Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Sabrina M. Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
2021	—	`conf`	MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. MLSys Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2021	J	`jnl`	S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration. CoRR Zhi Gang Liu, Paul N. Whatmough, Yuhao Zhu, Matthew Mattina
2021	—	`conf`	SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33 HCS Thierry Tambe, En-Yu Yang, Glenn G. Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N. Whatmough, Alexander M. Rush, David Brooks, Gu-Yeon Wei
2021	B	`conf`	Strong data processing inequality in neural networks with noisy neurons and its implications. ISIT Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
2021	J	`jnl`	Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. CoRR Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh
2020	—	`conf`	A 3mm VLSI Circuits Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe, Rob A. Rutenbar, David Brooks, Gu-Yeon Wei
2020	—	`conf`	A Scalable Bayesian Inference Accelerator for Unsupervised Learning. Hot Chips Symposium Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe, Rob A. Rutenbar, Gu-Yeon Wei, David Brooks
2020	B	`conf`	A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim. ISPASS Ananda Samajdar, Jan Moritz Joseph, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna
2020	J	`jnl`	CHIPKIT: An Agile, Reusable Open-Source Framework for Rapid Test Chip Development. IEEE Micro Paul N. Whatmough, Marco Donato, Glenn G. Ko, Sae Kyu Lee, David Brooks, Gu-Yeon Wei
2020	J	`jnl`	CHIPKIT: An agile, reusable open-source framework for rapid test chip development. CoRR Paul N. Whatmough, Marco Donato, Glenn G. Ko, David Brooks, Gu-Yeon Wei
2020	J	`jnl`	Compressing Language Models using Doped Kronecker Products. CoRR Urmish Thakker, Paul N. Whatmough, Matthew Mattina, Jesse G. Beu
2020	B	`conf`	ISP4ML: The Role of Image Signal Processing in Efficient Deep Learning Vision Systems. ICPR Patrick Hansen, Alexey Vilkin, Yury Krustalev, James Imber, Dumidu S. Talagala, David Hanwell, Matthew Mattina, Paul N. Whatmough
2020	A*	`conf`	Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation. MICRO Yu Feng, Boyuan Tian, Tiancheng Xu, Paul N. Whatmough, Yuhao Zhu
2020	J	`jnl`	Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation. CoRR Yu Feng, Boyuan Tian, Tiancheng Xu, Paul N. Whatmough, Yuhao Zhu
2020	J	`jnl`	MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. CoRR Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
2020	J	`jnl`	Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation. CoRR Chuteng Zhou, Prad Kadambi, Matthew Mattina, Paul N. Whatmough
2020	J	`jnl`	SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads. ACM Trans. Archit. Code Optim. Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul N. Whatmough, Gu-Yeon Wei, David Brooks
2020	—	`conf`	Searching for Winograd-aware Quantized Networks. MLSys Javier Fernández-Marqués, Paul N. Whatmough, Andrew Mundy, Matthew Mattina
2020	J	`jnl`	Searching for Winograd-aware Quantized Networks. CoRR Javier Fernández-Marqués, Paul N. Whatmough, Andrew Mundy, Matthew Mattina
2020	J	`jnl`	Sparse Systolic Tensor Array for Efficient CNN Hardware Acceleration. CoRR Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
2020	J	`jnl`	Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference. IEEE Comput. Archit. Lett. Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
2020	J	`jnl`	Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference. CoRR Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
2020	J	`jnl`	The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines. IEEE Comput. Archit. Lett. Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
2020	A	`conf`	TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids. INTERSPEECH Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
2020	J	`jnl`	TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids. CoRR Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
2019	J	`jnl`	A 16-nm Always-On DNN Processor With Adaptive Clocking and Multi-Cycle Banked SRAMs. IEEE J. Solid State Circuits Sae Kyu Lee, Paul N. Whatmough, David Brooks, Gu-Yeon Wei
2019	—	`conf`	A 16nm 25mm VLSI Circuits Paul N. Whatmough, Sae Kyu Lee, Marco Donato, Hsea-Ching Hsueh, Sam Likun Xi, Udit Gupta, Lillian Pentecost, Glenn G. Ko, David M. Brooks, Gu-Yeon Wei
2019	A*	`conf`	ASV: Accelerated Stereo Vision System. MICRO Yu Feng, Paul N. Whatmough, Yuhao Zhu
2019	J	`jnl`	ASV: Accelerated Stereo Vision System. CoRR Yu Feng, Paul N. Whatmough, Yuhao Zhu
2019	J	`jnl`	FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning. CoRR Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
2019	—	`conf`	FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning. SysML Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
2019	B	`conf`	GeST: An Automatic Framework For Generating CPU Stress-Tests. ISPASS Zacharias Hadjilambrou, Shidhartha Das, Paul N. Whatmough, David M. Bull, Yiannakis Sazeides
2019	J	`jnl`	Guest Editors' Introduction to the Special Section on Hardware and Algorithms for Energy-Constrained On-chip Machine Learning. ACM J. Emerg. Technol. Comput. Syst. Jae-sun Seo, Yu Cao, Xin Li, Paul N. Whatmough
2019	J	`jnl`	Guest Editors' Introduction: Hardware and Algorithms for Energy-Constrained On-Chip Machine Learning (Part 2). ACM J. Emerg. Technol. Comput. Syst. Jae-sun Seo, Yu Cao, Xin Li, Paul N. Whatmough
2019	J	`jnl`	ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems. CoRR Patrick Hansen, Alexey Vilkin, Yury Khrustalev, James Imber, David Hanwell, Matthew Mattina, Paul N. Whatmough
2019	A*	`conf`	On-Chip Memory Technology Design Space Explorations for Mobile Deep Neural Network Accelerators. DAC Haitong Li, Mudit Bhargava, Paul N. Whatmough, H.-S. Philip Wong
2019	J	`jnl`	SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads. CoRR Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul N. Whatmough, Gu-Yeon Wei, David Brooks
2019	A*	`conf`	SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers. NeurIPS Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
2019	J	`jnl`	SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers. CoRR Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
2018	—	`conf`	A Wide Dynamic Range Sparse FC-DNN Processor with Multi-Cycle Banked SRAM Read and Adaptive Clocking in 16nm FinFET. ESSCIRC Sae Kyu Lee, Paul N. Whatmough, Niamh Mulholland, Patrick Hansen, David Brooks, Gu-Yeon Wei
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`	DNN Engine: A 28-nm Timing-Error Tolerant Sparse Deep Neural Network Processor for IoT Applications. IEEE J. Solid State Circuits Paul N. Whatmough, Sae Kyu Lee, David M. Brooks, Gu-Yeon Wei
2018	J	`jnl`	Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning. CoRR Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina
2018	A*	`conf`	Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision. ISCA Yuhao Zhu, Anand Samajdar, Matthew Mattina, Paul N. Whatmough
2018	J	`jnl`	Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision. CoRR Yuhao Zhu, Anand Samajdar, Matthew Mattina, Paul N. Whatmough
2018	J	`jnl`	Mobile Machine Learning Hardware at ARM: A Systems-on-Chip (SoC) Perspective. CoRR Yuhao Zhu, Matthew Mattina, Paul N. Whatmough
2018	J	`jnl`	SCALE-Sim: Systolic CNN Accelerator. CoRR Ananda Samajdar, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna
2017	—	`conf`	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 Paul N. Whatmough, Sae Kyu Lee, Hyunkwang Lee, Saketh Rama, 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	C	`conf`	Applications of Deep Neural Networks for Ultra Low Power IoT. ICCD Sreela Kodali, Patrick Hansen, Niamh Mulholland, Paul N. Whatmough, David M. Brooks, Gu-Yeon Wei
2017	—	`book`	Deep Learning for Computer Architects Brandon Reagen, Robert Adolf, Paul N. Whatmough, Gu-Yeon Wei, David M. Brooks
2017	J	`jnl`	Power Integrity Analysis of a 28 nm Dual-Core ARM Cortex-A57 Cluster Using an All-Digital Power Delivery Monitor. IEEE J. Solid State Circuits Paul N. Whatmough, Shidhartha Das, Zacharias Hadjilambrou, David M. Bull
2017	Misc	`conf`	Sub-uJ deep neural networks for embedded applications. ACSSC Paul N. Whatmough, Sae Kyu Lee, Gu-Yeon Wei, David M. Brooks
2016	C	`conf`	A low-power correlator for wakeup receivers with algorithm pruning through early termination. ISCAS Reza Ghanaatian, Paul N. Whatmough, Jeremy Constantin, Adam Teman, Andreas Burg
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
2016	J	`jnl`	Sequence-Aware Watermark Design for Soft IP Embedded Processors. IEEE Trans. Very Large Scale Integr. Syst. Jedrzej Kufel, Peter R. Wilson, Stephen Hill, Bashir M. Al-Hashimi, Paul N. Whatmough
2015	—	`conf`	14.6 An all-digital power-delivery monitor for analysis of a 28nm dual-core ARM Cortex-A57 cluster. ISSCC Paul N. Whatmough, Shidhartha Das, Zacharias Hadjilambrou, David M. Bull
2015	—	`conf`	A 0.6V all-digital body-coupled wakeup transceiver for IoT applications. VLSIC Paul N. Whatmough, George Smart, Shidhartha Das, Yiannis Andreopoulos, David M. Bull
2015	A	`conf`	Analysis of adaptive clocking technique for resonant supply voltage noise mitigation. ISLPED Paul N. Whatmough, Shidhartha Das, David M. Bull
2015	A	`conf`	Modeling and characterization of the system-level Power Delivery Network for a dual-core ARM Cortex-A57 cluster in 28nm CMOS. ISLPED Shidhartha Das, Paul N. Whatmough, David M. Bull
2014	J	`jnl`	A Low-Power 1-GHz Razor FIR Accelerator With Time-Borrow Tracking Pipeline and Approximate Error Correction in 65-nm CMOS. IEEE J. Solid State Circuits Paul N. Whatmough, Shidhartha Das, David M. Bull
2014	A	`conf`	Clock-modulation based watermark for protection of embedded processors. DATE Jedrzej Kufel, Peter R. Wilson, Stephen Hill, Bashir M. Al-Hashimi, Paul N. Whatmough, James Myers
2014	J	`jnl`	Precision-Energy-Throughput Scaling Of Generic Matrix Multiplication and Convolution Kernels Via Linear Projections. CoRR Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
2014	J	`jnl`	Precision-Energy-Throughput Scaling of Generic Matrix Multiplication and Convolution Kernels via Linear Projections. IEEE Trans. Circuits Syst. Video Technol. Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
2013	—	`conf`	A low-power 1GHz razor FIR accelerator with time-borrow tracking pipeline and approximate error correction in 65nm CMOS. ISSCC Paul N. Whatmough, Shidhartha Das, David M. Bull
2013	J	`jnl`	Circuit-Level Timing Error Tolerance for Low-Power DSP Filters and Transforms. IEEE Trans. Very Large Scale Integr. Syst. Paul N. Whatmough, Shidhartha Das, David M. Bull, Izzat Darwazeh
2013	—	`conf`	Precision-energy-throughput scaling of generic matrix multiplication and discrete convolution kernels via linear projections. ESTIMedia Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
2012	—	`conf`	Selective time borrowing for DSP pipelines with hybrid voltage control loop. ASP-DAC Paul N. Whatmough, Shidhartha Das, David M. Bull, Izzat Darwazeh
2012	J	`jnl`	VLSI Architecture for a Reconfigurable Spectrally Efficient FDM Baseband Transmitter. IEEE Trans. Circuits Syst. I Regul. Pap. Paul N. Whatmough, Marcus R. Perrett, Safa Isam, Izzat Darwazeh
2011	A*	`conf`	Error-resilient low-power DSP via path-delay shaping. DAC Paul N. Whatmough, Shidhartha Das, David M. Bull, Izzat Darwazeh
2011	C	`conf`	VLSI architecture for a reconfigurable Spectrally Efficient FDM baseband transmitter. ISCAS Paul N. Whatmough, Marcus R. Perrett, Safa Isam, Izzat Darwazeh
2010	C	`conf`	A robust FIR filter with in situ error detection. ISCAS Paul N. Whatmough, Izzat Darwazeh, David M. Bull, Shidhartha Das, Danny Kershaw
2009	J	`jnl`	System-Efficiency Analysis of Power Amplifier Supply-Tracking Regimes in Mobile Transmitters. IEEE Trans. Circuits Syst. I Regul. Pap. Brian J. Minnis, Paul A. Moore, Paul N. Whatmough, Peter G. Blanken, Mark P. van der Heijden