Nicholas J. Fraser

According to our database, Nicholas J. Fraser authored at least 28 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Synthesis of LUT Networks for Random-Looking Dense Functions with Don't Cares - Towards Efficient FPGA Implementation of DNN.

Yukio Miyasaka, Alan Mishchenko, John Wawrzynek, Nicholas J. Fraser

Proceedings of the 32nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2024

2023

Fault-Tolerant Neural Network Accelerators With Selective TMR.

Timoteo García Bertoa, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, John McAllister

IEEE Des. Test, April, 2023

2021

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

Michaela Blott, Nicholas J. Fraser, Giulio Gambardella, Lisa Halder, Johannes Kath, Zachary Neveu, Yaman Umuroglu, Alina Vasilciuc, Miriam Leeser, Linda Doyle

IEEE Trans. Computers, 2021

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

Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu

Frontiers Artif. Intell., 2021

Trainable Preprocessing for Reduced Precision Neural Networks.

Gábor Csordás, Kristof Denolf, Nicholas J. Fraser, Alessandro Pappalardo, Kees A. Vissers

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Kernel Normalised Least Mean Squares with Delayed Model Adaptation.

Nicholas J. Fraser, Philip H. W. Leong

ACM Trans. Reconfigurable Technol. Syst., 2020

FAT: Training Neural Networks for Reliable Inference Under Hardware Faults.

Ussama Zahid, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, Kees A. Vissers

Proceedings of the IEEE International Test Conference, 2020

Memory-Efficient Dataflow Inference for Deep CNNs on FPGA.

Lucian Petrica, Tobias Alonso, Mairin Kroes, Nicholas J. Fraser, Sorin Cotofana, Michaela Blott

Proceedings of the International Conference on Field-Programmable Technology, 2020

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

Yaman Umuroglu, Yash Akhauri, Nicholas James Fraser, Michaela Blott

Proceedings of the 30th International Conference on Field-Programmable Logic and Applications, 2020

Evaluation of Optimized CNNs on FPGA and non-FPGA based Accelerators using a Novel Benchmarking Approach.

Michaela Blott, Johannes Kath, Lisa Halder, Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Miriam Leeser, Linda Doyle

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

High-Throughput DNN Inference with LogicNets.

Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser, Michaela Blott

Proceedings of the 28th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2020

2018

FINN-<i>R</i>: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks.

Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser, Kees A. Vissers

ACM Trans. Reconfigurable Technol. Syst., 2018

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

Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu

CoRR, 2018

Customizing Low-Precision Deep Neural Networks for FPGAs.

Julian Faraone, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, Philip H. W. Leong, David Boland

Proceedings of the 28th International Conference on Field Programmable Logic and Applications, 2018

Inference of quantized neural networks on heterogeneous all-programmable devices.

Thomas B. Preußer, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott

Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks.

Julian Faraone, Nicholas J. Fraser, Michaela Blott, Philip H. W. Leong

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

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

Jiang Su, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Gianluca Durelli, David B. Thomas, Philip Heng Wai Leong, Peter Y. K. Cheung

Proceedings of the Applied Reconfigurable Computing. Architectures, Tools, and Applications, 2018

2017

FPGA Implementations of Kernel Normalised Least Mean Squares Processors.

Nicholas J. Fraser, JunKyu Lee, Duncan J. M. Moss, Julian Faraone, Stephen Tridgell, Craig T. Jin, Philip Heng Wai Leong

ACM Trans. Reconfigurable Technol. Syst., 2017

Compressing Low Precision Deep Neural Networks Using Sparsity-Induced Regularization in Ternary Networks.

Julian Faraone, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong

Proceedings of the Neural Information Processing - 24th International Conference, 2017

Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic.

Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser

Proceedings of the 2017 IEEE International Conference on Computer Design, 2017

Scaling Binarized Neural Networks on Reconfigurable Logic.

Nicholas J. Fraser, Yaman Umuroglu, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers

Proceedings of the 8th Workshop and 6th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and Design Tools and Architectures for Multicore Embedded Computing Platforms, 2017

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

Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers

Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2017

2016

A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology.

Yeyong Pang, Shaojun Wang, Yu Peng, Xiyuan Peng, Nicholas J. Fraser, Philip Heng Wai Leong

ACM Trans. Reconfigurable Technol. Syst., 2016

2015

Distributed kernel learning using Kernel Recursive Least Squares.

Nicholas J. Fraser, Duncan J. M. Moss, Nicolas Epain, Philip Heng Wai Leong

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Braiding: A scheme for resolving hazards in kernel adaptive filters.

Stephen Tridgell, Duncan J. M. Moss, Nicholas J. Fraser, Philip Heng Wai Leong

Proceedings of the 2015 International Conference on Field Programmable Technology, 2015

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

Nicholas J. Fraser, Duncan J. M. Moss, JunKyu Lee, Stephen Tridgell, Craig T. Jin, Philip Heng Wai Leong

Proceedings of the 25th International Conference on Field Programmable Logic and Applications, 2015

2014

An FPGA-based spectral anomaly detection system.

Duncan J. M. Moss, Zhe Zhang, Nicholas J. Fraser, Philip Heng Wai Leong

Proceedings of the 2014 International Conference on Field-Programmable Technology, 2014

2013

A low latency kernel recursive least squares processor using FPGA technology.

Yeyong Pang, Shaojun Wang, Yu Peng, Nicholas J. Fraser, Philip Heng Wai Leong

Proceedings of the 2013 International Conference on Field-Programmable Technology, 2013