22 citations · 29 across the 7 of their papers we have counts for
5 papers · 1 filter
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks
Michaela Blott, Thomas Preusser, Nicholas Fraser +3
Convolutional Neural Networks have rapidly become the most successful machine learning algorithm, enabling ubiquitous machine vision and intelligent decisions on even embedded comp…
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic
Michaela Blott, Thomas B. Preusser, Nicholas Fraser +4
Convolutional Neural Networks have dramatically improved in recent years, surpassing human accuracy on certain problems and performance exceeding that of traditional computer visio…
Generic and Universal Parallel Matrix Summation with a Flexible Compression Goal for Xilinx FPGAs
Thomas B. Preußer
Bit matrix compression is a highly relevant operation in computer arithmetic. Essentially being a multi-operand addition, it is the key operation behind fast multiplication and man…
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices
Thomas B. Preußer, Giulio Gambardella, Nicholas Fraser +1
Neural networks have established as a generic and powerful means to approach challenging problems such as image classification, object detection or decision making. Their successfu…
QBM - Mapping User-Specified Functions to Programmable Logic through a QBF Satisfiability Problem
Thomas B. Preußer
This is a brief overview on the background behind the test set formulas generated by the QBM tool. After establishing its application context, its formal approach to the generation…