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ORCIDNicholas J. Fraser
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2020 – today
- 2024
[c20]Yukio Miyasaka, Alan Mishchenko, John Wawrzynek, Nicholas J. Fraser:
Synthesis of LUT Networks for Random-Looking Dense Functions with Don't Cares - Towards Efficient FPGA Implementation of DNN. FCCM 2024: 126-132- 2023
- [j7]Timoteo García Bertoa
, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, John McAllister:
Fault-Tolerant Neural Network Accelerators With Selective TMR. IEEE Des. Test 40(2): 67-74 (2023) - 2021
- [j6]Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu:
Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. Frontiers Artif. Intell. 4: 676564 (2021) - [j5]Michaela Blott, Nicholas J. Fraser, Giulio Gambardella, Lisa Halder, Johannes Kath, Zachary Neveu, Yaman Umuroglu, Alina Vasilciuc, Miriam Leeser, Linda Doyle:
Evaluation of Optimized CNNs on Heterogeneous Accelerators Using a Novel Benchmarking Approach. IEEE Trans. Computers 70(10): 1654-1669 (2021) - [c19]Gábor Csordás, Kristof Denolf, Nicholas J. Fraser, Alessandro Pappalardo, Kees A. Vissers:
Trainable Preprocessing for Reduced Precision Neural Networks. EUSIPCO 2021: 1546-1550 - [i12]Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu:
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference. CoRR abs/2102.11289 (2021) - 2020
- [j4]Nicholas J. Fraser, Philip H. W. Leong:
Kernel Normalised Least Mean Squares with Delayed Model Adaptation. ACM Trans. Reconfigurable Technol. Syst. 13(2): 7:1-7:30 (2020) - [c18]Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser, Michaela Blott:
High-Throughput DNN Inference with LogicNets. FCCM 2020: 238 - [c17]Michaela Blott, Johannes Kath, Lisa Halder, Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Miriam Leeser, Linda Doyle:
Evaluation of Optimized CNNs on FPGA and non-FPGA based Accelerators using a Novel Benchmarking Approach. FPGA 2020: 317 - [c16]Yaman Umuroglu, Yash Akhauri, Nicholas James Fraser, Michaela Blott:
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. FPL 2020: 291-297 - [c15]Lucian Petrica, Tobias Alonso, Mairin Kroes, Nicholas J. Fraser, Sorin Cotofana, Michaela Blott:
Memory-Efficient Dataflow Inference for Deep CNNs on FPGA. FPT 2020: 48-55 - [c14]Ussama Zahid, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, Kees A. Vissers:
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults. ITC 2020: 1-10 - [i11]Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser, Michaela Blott:
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. CoRR abs/2004.03021 (2020) - [i10]Ussama Zahid, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, Kees A. Vissers:
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults. CoRR abs/2011.05873 (2020) - [i9]Lucian Petrica, Tobias Alonso, Mairin Kroes, Nicholas J. Fraser, Sorin Cotofana, Michaela Blott:
Memory-Efficient Dataflow Inference for Deep CNNs on FPGA. CoRR abs/2011.07317 (2020)
2010 – 2019
- 2018
- [j3]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser, Kees A. Vissers:
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. ACM Trans. Reconfigurable Technol. Syst. 11(3): 16:1-16:23 (2018) - [c13]Jiang Su, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Gianluca Durelli, David B. Thomas, Philip Heng Wai Leong, Peter Y. K. Cheung:
Accuracy to Throughput Trade-Offs for Reduced Precision Neural Networks on Reconfigurable Logic. ARC 2018: 29-42 - [c12]Julian Faraone, Nicholas J. Fraser, Michaela Blott, Philip H. W. Leong:
SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks. CVPR 2018: 4300-4309 - [c11]Thomas B. Preußer, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott:
Inference of quantized neural networks on heterogeneous all-programmable devices. DATE 2018: 833-838 - [c10]Julian Faraone, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott, Philip H. W. Leong, David Boland:
Customizing Low-Precision Deep Neural Networks for FPGAs. FPL 2018: 97-100 - [i8]Thomas B. Preußer, Giulio Gambardella, Nicholas J. Fraser, Michaela Blott:
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices. CoRR abs/1806.08085 (2018) - [i7]Julian Faraone, Nicholas J. Fraser, Michaela Blott, Philip Heng Wai Leong:
SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks. CoRR abs/1807.00301 (2018) - [i6]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser:
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic. CoRR abs/1807.03123 (2018) - [i5]Jiang Su, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Gianluca Durelli, David B. Thomas, Philip Heng Wai Leong, Peter Y. K. Cheung:
Accuracy to Throughput Trade-offs for Reduced Precision Neural Networks on Reconfigurable Logic. CoRR abs/1807.10577 (2018) - [i4]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu:
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. CoRR abs/1809.04570 (2018) - 2017
- [j2]Nicholas J. Fraser, JunKyu Lee, Duncan J. M. Moss, Julian Faraone, Stephen Tridgell, Craig T. Jin, Philip Heng Wai Leong:
FPGA Implementations of Kernel Normalised Least Mean Squares Processors. ACM Trans. Reconfigurable Technol. Syst. 10(4): 26:1-26:20 (2017) - [c9]Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. FPGA 2017: 65-74 - [c8]Nicholas J. Fraser, Yaman Umuroglu, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
Scaling Binarized Neural Networks on Reconfigurable Logic. PARMA-DITAM@HiPEAC 2017: 25-30 - [c7]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser:
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic. ICCD 2017: 419-422 - [c6]Julian Faraone, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong:
Compressing Low Precision Deep Neural Networks Using Sparsity-Induced Regularization in Ternary Networks. ICONIP (2) 2017: 393-404 - [i3]Nicholas J. Fraser, Yaman Umuroglu, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
Scaling Binarized Neural Networks on Reconfigurable Logic. CoRR abs/1701.03400 (2017) - [i2]Julian Faraone, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong:
Compressing Low Precision Deep Neural Networks Using Sparsity-Induced Regularization in Ternary Networks. CoRR abs/1709.06262 (2017) - 2016
- [j1]Yeyong Pang, Shaojun Wang, Yu Peng, Xiyuan Peng, Nicholas J. Fraser, Philip Heng Wai Leong:
A Microcoded Kernel Recursive Least Squares Processor Using FPGA Technology. ACM Trans. Reconfigurable Technol. Syst. 10(1): 5:1-5:22 (2016) - [i1]Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. CoRR abs/1612.07119 (2016) - 2015
- [c5]Nicholas J. Fraser, Duncan J. M. Moss, JunKyu Lee, Stephen Tridgell, Craig T. Jin, Philip Heng Wai Leong:
A fully pipelined kernel normalised least mean squares processor for accelerated parameter optimisation. FPL 2015: 1-6 - [c4]Stephen Tridgell, Duncan J. M. Moss, Nicholas J. Fraser, Philip Heng Wai Leong:
Braiding: A scheme for resolving hazards in kernel adaptive filters. FPT 2015: 136-143 - [c3]Nicholas J. Fraser, Duncan J. M. Moss, Nicolas Epain, Philip Heng Wai Leong:
Distributed kernel learning using Kernel Recursive Least Squares. ICASSP 2015: 5500-5504 - 2014
- [c2]Duncan J. M. Moss, Zhe Zhang, Nicholas J. Fraser, Philip Heng Wai Leong:
An FPGA-based spectral anomaly detection system. FPT 2014: 175-182 - 2013
- [c1]Yeyong Pang, Shaojun Wang, Yu Peng, Nicholas J. Fraser, Philip Heng Wai Leong:
A low latency kernel recursive least squares processor using FPGA technology. FPT 2013: 144-151
Coauthor Index
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