77 citations · 125 across the 7 of their papers we have counts for
4 papers · 1 filter
Logic Shrinkage: Learned FPGA Netlist Sparsity for Efficient Neural Network Inference
Erwei Wang, James J. Davis, Georgios-Ilias Stavrou +3
FPGA-specific DNN architectures using the native LUTs as independently trainable inference operators have been shown to achieve favorable area-accuracy and energy-accuracy tradeoff…
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
Zhiqiang Que, Erwei Wang, Umar Marikar +10
This paper presents novel reconfigurable architectures for reducing the latency of recurrent neural networks (RNNs) that are used for detecting gravitational waves. Gravitational i…
LUTNet: Learning FPGA Configurations for Highly Efficient Neural Network Inference
Erwei Wang, James J. Davis, Peter Y. K. Cheung +1
Research has shown that deep neural networks contain significant redundancy, and thus that high classification accuracy can be achieved even when weights and activations are quanti…
LUTNet: Rethinking Inference in FPGA Soft Logic
Erwei Wang, James J. Davis, Peter Y. K. Cheung +1
Research has shown that deep neural networks contain significant redundancy, and that high classification accuracies can be achieved even when weights and activations are quantised…