Paul N. Whatmough

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 88

Top Venues

CoRR

IEEE J. Solid State Circuits

ISLPED

MLSys

Publications

Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhu, Paul N. Whatmough, Yuhao Zhu
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator. CoRR (2024)
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
Sparse High Rank Adapters. CoRR (2024)
Mart van Baalen, Andrey Kuzmin, Markus Nagel, Peter Couperus, Cédric Bastoul, Eric Mahurin, Tijmen Blankevoort, Paul N. Whatmough
GPTVQ: The Blessing of Dimensionality for LLM Quantization. CoRR (2024)
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
Rapid Switching and Multi-Adapter Fusion via Sparse High Rank Adapters. CoRR (2024)
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhou, Paul N. Whatmough, Yuhao Zhu
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator. ISPASS (2024)
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
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) (2023)
Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu
Fast and Accurate: Video Enhancement Using Sparse Depth. WACV (2023)
Teyuh Chou, Fernando García-Redondo, Paul N. Whatmough, Zhengya Zhang
AR-PIM: An Adaptive-Range Processing-in-Memory Architecture. ISLPED (2023)
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
A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. ISSCC (2023)
Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama
Efficient Edge Inference by Selective Query. ICLR (2023)
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 (2023)
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Sabrina M. Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. MICRO (2022)
Sae Kyu Lee, Paul N. Whatmough, Marco Donato, Glenn G. Ko, David Brooks, Gu-Yeon Wei
SMIV: A 16-nm 25-mm² SoC for IoT With Arm Cortex-A53, eFPGA, and Coherent Accelerators. IEEE J. Solid State Circuits 57 (2) (2022)
Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. DATE (2022)
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units. NeurIPS (2022)
Zhi Gang Liu, Paul N. Whatmough, Yuhao Zhu, Matthew Mattina
S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration. HPCA (2022)
Yiming Gan, Paul N. Whatmough, Jingwen Leng, Bo Yu, Shaoshan Liu, Yuhao Zhu
Braum: Analyzing and Protecting Autonomous Machine Software Stack. ISSRE (2022)
Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough
UDC: Unified DNAS for Compressible TinyML Models. CoRR (2022)
Abhishek Tyagi, Yiming Gan, Shaoshan Liu, Bo Yu, Paul N. Whatmough, Yuhao Zhu
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators. CoRR (2022)
Kartikeya Bhardwaj, James Ward, Caleb Tung, Dibakar Gope, Lingchuan Meng, Igor Fedorov, Alex Chalfin, Paul N. Whatmough, Danny Loh
Restructurable Activation Networks. CoRR (2022)
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
ML-HW Co-Design of Noise-Robust TinyML Models and Always-On Analog Compute-in-Memory Edge Accelerator. IEEE Micro 42 (6) (2022)
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
Strong data processing inequality in neural networks with noisy neurons and its implications. ISIT (2021)
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
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator. CoRR (2021)
Durmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
Debiasing Model Updates for Improving Personalized Federated Training. ICML (2021)
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Sabrina Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots. CoRR (2021)
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
EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. MICRO (2021)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. MLSys (2021)
Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices. CoRR (2021)
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
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)
Urmish Thakker, Paul N. Whatmough, Zhi Gang Liu, Matthew Mattina, Jesse G. Beu
Doping: A technique for Extreme Compression of LSTM Models using Sparse Structured Additive Matrices. MLSys (2021)
Zhi Gang Liu, Paul N. Whatmough, Yuhao Zhu, Matthew Mattina
S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration. CoRR (2021)
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, Paul N. Whatmough
Information contraction in noisy binary neural networks and its implications. CoRR (2021)
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
Federated Learning Based on Dynamic Regularization. CoRR (2021)
Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama
Federated Learning Based on Dynamic Regularization. ICLR (2021)
Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu
A LiDAR-Guided Framework for Video Enhancement. CoRR (2021)
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
Hot Chips Symposium - August 22-24, 2021. HCS (2021)
Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh
Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. CoRR (2021)
Jian Meng, Shreyas Kolala Venkataramanaiah, Chuteng Zhou, Patrick Hansen, Paul N. Whatmough, Jae-sun Seo
FixyFPGA: Efficient FPGA Accelerator for Deep Neural Networks with High Element-Wise Sparsity and without External Memory Access. FPL (2021)
Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers. CoRR (2020)
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) (2020)
Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids. INTERSPEECH (2020)
Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference. IEEE Comput. Archit. Lett. 19 (1) (2020)
Urmish Thakker, Paul N. Whatmough, Matthew Mattina, Jesse G. Beu
Compressing Language Models using Doped Kronecker Products. CoRR (2020)
Yu Feng, Boyuan Tian, Tiancheng Xu, Paul N. Whatmough, Yuhao Zhu
Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation. MICRO (2020)
Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference. CoRR (2020)
Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe, Rob A. Rutenbar, Gu-Yeon Wei, David Brooks
A Scalable Bayesian Inference Accelerator for Unsupervised Learning. Hot Chips Symposium (2020)
Glenn G. Ko, Yuji Chai, Marco Donato, Paul N. Whatmough, Thierry Tambe, Rob A. Rutenbar, David Brooks, Gu-Yeon Wei
Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm. VLSI Circuits (2020)
Javier Fernández-Marqués, Paul N. Whatmough, Andrew Mundy, Matthew Mattina
Searching for Winograd-aware Quantized Networks. CoRR (2020)
Javier Fernández-Marqués, Paul N. Whatmough, Andrew Mundy, Matthew Mattina
Searching for Winograd-aware Quantized Networks. MLSys (2020)
Yu Feng, Boyuan Tian, Tiancheng Xu, Paul N. Whatmough, Yuhao Zhu
Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation. CoRR (2020)
Chuteng Zhou, Prad Kadambi, Matthew Mattina, Paul N. Whatmough
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation. CoRR (2020)
Ananda Samajdar, Jan Moritz Joseph, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna
A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim. ISPASS (2020)
Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough
TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids. CoRR (2020)
Zhi Gang Liu, Paul N. Whatmough, Matthew Mattina
Sparse Systolic Tensor Array for Efficient CNN Hardware Acceleration. CoRR (2020)
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 (2020)
Patrick Hansen, Alexey Vilkin, Yury Krustalev, James Imber, Dumidu Talagala, David Hanwell, Matthew Mattina, Paul N. Whatmough
ISP4ML: The Role of Image Signal Processing in Efficient Deep Learning Vision Systems. ICPR (2020)
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul N. Whatmough, Aleksandra Faust, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi
The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines. IEEE Comput. Archit. Lett. 19 (1) (2020)
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) (2020)
Patrick Hansen, Alexey Vilkin, Yury Khrustalev, James Imber, David Hanwell, Matthew Mattina, Paul N. Whatmough
ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems. CoRR (2019)
Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers. NeurIPS (2019)
Zacharias Hadjilambrou, Shidhartha Das, Paul N. Whatmough, David M. Bull, Yiannakis Sazeides
GeST: An Automatic Framework For Generating CPU Stress-Tests. ISPASS (2019)
Haitong Li, Mudit Bhargava, Paul N. Whatmough, H.-S. Philip Wong
On-Chip Memory Technology Design Space Explorations for Mobile Deep Neural Network Accelerators. DAC (2019)
Yu Feng, Paul N. Whatmough, Yuhao Zhu
ASV: Accelerated Stereo Vision System. MICRO (2019)
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
SoC with a 54.5x Flexibility-Efficiency Range from Dual-Core Arm Cortex-A53 to eFPGA and Cache-Coherent Accelerators. VLSI Circuits (2019)
Jae-Sun Seo, Yu Cao, Xin Li, Paul N. Whatmough
Guest Editors' Introduction: Hardware and Algorithms for Energy-Constrained On-Chip Machine Learning (Part 2). ACM J. Emerg. Technol. Comput. Syst. 15 (4) (2019)
Yu Feng, Paul N. Whatmough, Yuhao Zhu
ASV: Accelerated Stereo Vision System. CoRR (2019)
Sae Kyu Lee, Paul N. Whatmough, David Brooks, Gu-Yeon Wei
A 16-nm Always-On DNN Processor With Adaptive Clocking and Multi-Cycle Banked SRAMs. IEEE J. Solid State Circuits 54 (7) (2019)
Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers. CoRR (2019)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning. MLSys (2019)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas K. Venkataramanaiah, Jae-sun Seo, Matthew Mattina
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning. CoRR (2019)
Jae-sun Seo, Yu Cao, Xin Li, Paul N. Whatmough
Guest Editors' Introduction to the Special Section on Hardware and Algorithms for Energy-Constrained On-chip Machine Learning. ACM J. Emerg. Technol. Comput. Syst. 15 (2) (2019)
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 (2019)
Ananda Samajdar, Yuhao Zhu, Paul N. Whatmough, Matthew Mattina, Tushar Krishna
SCALE-Sim: Systolic CNN Accelerator. CoRR (2018)
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning. CoRR (2018)
Yuhao Zhu, Anand Samajdar, Matthew Mattina, Paul N. Whatmough
Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision. ISCA (2018)
Paul N. Whatmough, Sae Kyu Lee, David M. Brooks, Gu-Yeon Wei
DNN Engine: A 28-nm Timing-Error Tolerant Sparse Deep Neural Network Processor for IoT Applications. IEEE J. Solid State Circuits 53 (9) (2018)
Brandon Reagen, Udit Gupta, Lillian Pentecost, Paul N. Whatmough, Sae Kyu Lee, Niamh Mulholland, David M. Brooks, Gu-Yeon Wei
Ares: a framework for quantifying the resilience of deep neural networks. DAC (2018)
Yuhao Zhu, Anand Samajdar, Matthew Mattina, Paul N. Whatmough
Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision. CoRR (2018)
Sae Kyu Lee, Paul N. Whatmough, Niamh Mulholland, Patrick Hansen, David Brooks, Gu-Yeon Wei
A Wide Dynamic Range Sparse FC-DNN Processor with Multi-Cycle Banked SRAM Read and Adaptive Clocking in 16nm FinFET. ESSCIRC (2018)
Yuhao Zhu, Matthew Mattina, Paul N. Whatmough
Mobile Machine Learning Hardware at ARM: A Systems-on-Chip (SoC) Perspective. CoRR (2018)
Paul N. Whatmough, Shidhartha Das, Zacharias Hadjilambrou, David M. Bull
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 52 (6) (2017)
Sreela Kodali, Patrick Hansen, Niamh Mulholland, Paul N. Whatmough, David M. Brooks, Gu-Yeon Wei
Applications of Deep Neural Networks for Ultra Low Power IoT. ICCD (2017)
Paul N. Whatmough, Sae Kyu Lee, Gu-Yeon Wei, David M. Brooks
Sub-uJ deep neural networks for embedded applications. ACSSC (2017)
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)
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)
Jedrzej Kufel, Peter R. Wilson, Stephen Hill, Bashir M. Al-Hashimi, Paul N. Whatmough
Sequence-Aware Watermark Design for Soft IP Embedded Processors. IEEE Trans. Very Large Scale Integr. Syst. 24 (1) (2016)
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)
Reza Ghanaatian, Paul N. Whatmough, Jeremy Constantin, Adam Teman, Andreas Burg
A low-power correlator for wakeup receivers with algorithm pruning through early termination. ISCAS (2016)
Paul N. Whatmough, Shidhartha Das, Zacharias Hadjilambrou, David M. Bull
14.6 An all-digital power-delivery monitor for analysis of a 28nm dual-core ARM Cortex-A57 cluster. ISSCC (2015)
Shidhartha Das, Paul N. Whatmough, David M. Bull
Modeling and characterization of the system-level Power Delivery Network for a dual-core ARM Cortex-A57 cluster in 28nm CMOS. ISLPED (2015)
Paul N. Whatmough, Shidhartha Das, David M. Bull
Analysis of adaptive clocking technique for resonant supply voltage noise mitigation. ISLPED (2015)
Paul N. Whatmough, George Smart, Shidhartha Das, Yiannis Andreopoulos, David M. Bull
A 0.6V all-digital body-coupled wakeup transceiver for IoT applications. VLSIC (2015)
Jedrzej Kufel, Peter R. Wilson, Stephen Hill, Bashir M. Al-Hashimi, Paul N. Whatmough, James Myers
Clock-modulation based watermark for protection of embedded processors. DATE (2014)
Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
Precision-Energy-Throughput Scaling of Generic Matrix Multiplication and Convolution Kernels via Linear Projections. IEEE Trans. Circuits Syst. Video Technol. 24 (11) (2014)
Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
Precision-Energy-Throughput Scaling Of Generic Matrix Multiplication and Convolution Kernels Via Linear Projections. CoRR (2014)
Paul N. Whatmough, Shidhartha Das, David M. Bull
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 49 (1) (2014)
Paul N. Whatmough, Shidhartha Das, David M. Bull
A low-power 1GHz razor FIR accelerator with time-borrow tracking pipeline and approximate error correction in 65nm CMOS. ISSCC (2013)
Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
Precision-energy-throughput scaling of generic matrix multiplication and discrete convolution kernels via linear projections. ESTIMedia (2013)
Paul N. Whatmough, Shidhartha Das, David M. Bull, Izzat Darwazeh
Circuit-Level Timing Error Tolerance for Low-Power DSP Filters and Transforms. IEEE Trans. Very Large Scale Integr. Syst. 21 (6) (2013)
Paul N. Whatmough, Shidhartha Das, David M. Bull, Izzat Darwazeh
Selective time borrowing for DSP pipelines with hybrid voltage control loop. ASP-DAC (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Paul N. Whatmough