Imperial College London
Alternate

ProfessorChristos-SavvasBouganis

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Intelligent Digital Systems
 
 
 
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Contact

 

+44 (0)20 7594 6144christos-savvas.bouganis Website

 
 
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Location

 

904Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Kouris:2018:10.1109/FPL.2018.00034,
author = {Kouris, A and Venieris, SI and Bouganis, C-S},
doi = {10.1109/FPL.2018.00034},
pages = {155--162},
publisher = {IEEE},
title = {CascadeC(NN): pushing the performance limits of quantisation in convolutional neural networks},
url = {http://dx.doi.org/10.1109/FPL.2018.00034},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, aiming to perform high-throughput inference. A two-stage architecture tailored for any given CNN-FPGA pair is generated, consisting of a low-and high-precision unit in a cascade. A confidence evaluation unit is employed to identify misclassified cases from the excessively low-precision unit and forward them to the high-precision unit for re-processing. Experiments demonstrate that the proposed toolflow can achieve a performance boost up to 55% for VGG-16 and 48% for AlexNet over the baseline design for the same resource budget and accuracy, without the need of retraining the model or accessing the training data.
AU  - Kouris,A
AU  - Venieris,SI
AU  - Bouganis,C-S
DO  - 10.1109/FPL.2018.00034
EP  - 162
PB  - IEEE
PY  - 2018///
SN  - 1946-1488
SP  - 155
TI  - CascadeC(NN): pushing the performance limits of quantisation in convolutional neural networks
UR  - http://dx.doi.org/10.1109/FPL.2018.00034
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000460538500027&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/69927
ER  -
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