UofUtah HLS CNN Acceleration

• Dataflow Accelerators for deep convolutional neural networks via Vitis HLS and Finn compiler for AMD-Xilinx FPGAs.

ANN_MNIST

• 3 Layer Multilayer Perceptron implemented in Vitis-HLS for MNIST hand written digit recongition. Fully Connected layers represented as Matrix-Vector Multiplication and each layer is fully pipelined and unrolled for maximum throughput and performance.

Lenet5_Notebooks:

• Quantization Aware training for 5 layer CNN (Lenet5) implementation in Brevitas using 8 bit quantizations for inputs, weights, and activations. Train on MNIST handwritted digits dataset, export to onnx, apply transformations, export to FINN for Vitis-HLS acclerator generation and deploy on AMD Kria KV260 SOM for inference evalution via PYNQ.

-FPGA Folding: Adjust onnx nodes

Resnet 50/18 Notebooks:

In progress.

Validation and Results: Deployed as PYNQ overlay on AMD Kria KV260 SOM.