research
∙
12/04/2021
Logic Shrinkage: Learned FPGA Netlist Sparsity for Efficient Neural Network Inference
FPGA-specific DNN architectures using the native LUTs as independently t...
share
research
∙
06/26/2021
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments
This paper presents novel reconfigurable architectures for reducing the ...
research
∙
02/08/2021
Enabling Binary Neural Network Training on the Edge
The ever-growing computational demands of increasingly complex machine l...
research
∙
10/24/2019
LUTNet: Learning FPGA Configurations for Highly Efficient Neural Network Inference
Research has shown that deep neural networks contain significant redunda...
research
∙
10/21/2019
Automatic Generation of Multi-precision Multi-arithmetic CNN Accelerators for FPGAs
Modern deep Convolutional Neural Networks (CNNs) are computationally dem...
research
∙
04/01/2019
LUTNet: Rethinking Inference in FPGA Soft Logic
Research has shown that deep neural networks contain significant redunda...
research
∙
01/21/2019
