
LogicNets: CoDesigned Neural Networks and Circuits for ExtremeThroughput Applications
Deployment of deep neural networks for applications that require very hi...
read it

Evolutionary Bin Packing for MemoryEfficient Dataflow Inference Acceleration on FPGA
Convolutional neural network (CNN) dataflow inference accelerators imple...
read it

Efficient ErrorTolerant Quantized Neural Network Accelerators
Neural Networks are currently one of the most widely deployed machine le...
read it

QuTiBench: Benchmarking Neural Networks on Heterogeneous Hardware
Neural Networks have become one of the most successful universal machine...
read it

Synetgy: Algorithmhardware Codesign for ConvNet Accelerators on Embedded FPGAs
Using FPGAs to accelerate ConvNets has attracted significant attention i...
read it

FINNR: An EndtoEnd DeepLearning Framework for Fast Exploration of Quantized Neural Networks
Convolutional Neural Networks have rapidly become the most successful ma...
read it

FINNL: Library Extensions and Design Tradeoff Analysis for Variable Precision LSTM Networks on FPGAs
It is well known that many types of artificial neural networks, includin...
read it

SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks
Inference for stateoftheart deep neural networks is computationally e...
read it

Inference of Quantized Neural Networks on Heterogeneous AllProgrammable Devices
Neural networks have established as a generic and powerful means to appr...
read it

Compressing Low Precision Deep Neural Networks Using SparsityInduced Regularization in Ternary Networks
A low precision deep neural network training technique for producing spa...
read it

Scaling Binarized Neural Networks on Reconfigurable Logic
Binarized neural networks (BNNs) are gaining interest in the deep learni...
read it

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference
Research has shown that convolutional neural networks contain significan...
read it