FPGA Hardware Acceleration for Convolutional Neural Networks: A Configurable Multi-Layer VHDL Implementation Scheme

Introduction / Main Floor: FPGA Hardware Acceleration for Convolutional Neural Networks: A Configurable Multi-Layer VHDL Implementation Scheme

This article introduces an FPGA-based hardware accelerator for convolutional neural networks, implemented in VHDL. It supports runtime configuration of kernel size, number of filters, stride, padding, and activation functions, enabling adaptation to different network layers without re-synthesis.