Master Thesis "ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network"
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
This repository is the backup of XJTU-Tripler project, participating dac19 system design contest
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
This is the first step to implement RNN on FPGAs. All modules are heavily commented. We will use High-Level Synthesis to turn these code into Hardware Description Languages (HDL).
The resnet20 cnn inference accelerator on cifar10 net about twn net with hls tool
PyTorch implementation of DiracDeltaNet from paper Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs
A Convolutional Neural Network Accelerator, which increases the process of convolution calculation. Based on Xilinx HLS design suite.
A FPGA-based Accelerator for Shufflenetv2 implemented on Xillinx Zynq-7000 SoC