Nicholas J. Fraser

发表

A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology

Philip Heng Wai Leong, Yu Peng, Xiyuan Peng, 2016, ACM Trans. Reconfigurable Technol. Syst..

Braiding: A scheme for resolving hazards in kernel adaptive filters

Philip Heng Wai Leong, Nicholas J. Fraser, Stephen Tridgell, 2015, 2015 International Conference on Field Programmable Technology (FPT).

FPGA Implementations of Kernel Normalised Least Mean Squares Processors

Craig T. Jin, Philip Heng Wai Leong, Nicholas J. Fraser, 2017, TRETS.

LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications

Yash Akhauri, Michaela Blott, Yaman Umuroglu, 2020, 2020 30th International Conference on Field-Programmable Logic and Applications (FPL).

Scaling Binarized Neural Networks on Reconfigurable Logic

Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers, 2017, PARMA-DITAM '17.

Accuracy to Throughput Trade-Offs for Reduced Precision Neural Networks on Reconfigurable Logic

David B. Thomas, Philip Heng Wai Leong, Gianluca Durelli, 2018, ARC.

Customizing Low-Precision Deep Neural Networks for FPGAs

David Boland, Michaela Blott, Giulio Gambardella, 2018, 2018 28th International Conference on Field Programmable Logic and Applications (FPL).

SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks

Philip Heng Wai Leong, Michaela Blott, Nicholas J. Fraser, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic

Miriam Leeser, Kenneth O'Brien, Thomas B. Preußer, 2017, 2017 IEEE International Conference on Computer Design (ICCD).

Inference of quantized neural networks on heterogeneous all-programmable devices

Thomas B. Preußer, Michaela Blott, Giulio Gambardella, 2018, 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Evaluation of Optimized CNNs on Heterogeneous Accelerators Using a Novel Benchmarking Approach

Linda Doyle, Miriam Leeser, Michaela Blott, 2020, IEEE Transactions on Computers.

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers, 2016, FPGA.

Distributed kernel learning using Kernel Recursive Least Squares

Philip Heng Wai Leong, Nicholas J. Fraser, Nicolas Epain, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks

Kenneth O'Brien, Thomas B. Preußer, Michaela Blott, 2018 .

FAT: Training Neural Networks for Reliable Inference Under Hardware Faults

Michaela Blott, Giulio Gambardella, Kees Vissers, 2020, 2020 IEEE International Test Conference (ITC).

Kernel Normalised Least Mean Squares with Delayed Model Adaptation

Philip H. W. Leong, Nicholas J. Fraser, P. Leong, 2020, ACM Trans. Reconfigurable Technol. Syst..

An FPGA-based spectral anomaly detection system

Zhe Zhang, Philip Heng Wai Leong, Nicholas J. Fraser, 2014, 2014 International Conference on Field-Programmable Technology (FPT).

A low latency kernel recursive least squares processor using FPGA technology

Philip Heng Wai Leong, Yu Peng, Shaojun Wang, 2013, 2013 International Conference on Field-Programmable Technology (FPT).

A fully pipelined kernel normalised least mean squares processor for accelerated parameter optimisation

Craig T. Jin, Philip Heng Wai Leong, Nicholas J. Fraser, 2015, 2015 25th International Conference on Field Programmable Logic and Applications (FPL).

High-Throughput DNN Inference with LogicNets

Yash Akhauri, Michaela Blott, Yaman Umuroglu, 2020, 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Javier Duarte, Yaman Umuroglu, Nicholas J. Fraser, 2021, Frontiers in Artificial Intelligence.

Trainable Preprocessing for Reduced Precision Neural Networks

Kristof Denolf, Kees A. Vissers, Nicholas J. Fraser, 2021, 2021 29th European Signal Processing Conference (EUSIPCO).

FINN-R

Kenneth O'Brien, Thomas B. Preußer, Michaela Blott, 2018, ACM Trans. Reconfigurable Technol. Syst..

Accelerated Radiation Test on Quantized Neural Networks trained with Fault Aware Training

Nicholas J. Fraser, G. Furano, Michaela Blott, 2022, 2022 IEEE Aerospace Conference (AERO).

Fault-Tolerant Neural Network Accelerators With Selective TMR

Nicholas J. Fraser, Timoteo García Bertoa, Michaela Blott, 2023, IEEE Design & Test.

Memory-Efficient Dataflow Inference for Deep CNNs on FPGA pdf

Sorin Cotofana, Michaela Blott, Lucian Petrica, 2020, 2020 International Conference on Field-Programmable Technology (ICFPT).

Quantizing Convolutional Neural Networks for Low-Power High-Throughput Inference Engines pdf

Michael Wu, Nicholas J. Fraser, Manasa Bollavaram, 2018, ArXiv.