apfp

PaddlePaddle High Performance Deep Learning Inference Engine for Mobile and Edge (飞桨高性能深度学习端侧推理引擎）

Machine learning on FPGAs using HLS

Silice is an easy-to-learn, powerful hardware description language, that simplifies designing hardware algorithms with parallelism and pipelines.

Brevitas: neural network quantization in PyTorch

Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.

Samples for Intel® oneAPI Toolkits

Dataflow compiler for QNN inference on FPGAs

A lightweight high performance tensor algebra framework for modern C++

This project accelerates CNN computation with the help of FPGA, for more than 50x speed-up compared with CPU.

QKeras: a quantization deep learning library for Tensorflow Keras