# 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.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-05-11T23:55:21.000Z
- 最近活动: 2026-05-11T23:57:48.929Z
- 热度: 0.0
- 关键词: FPGA, CNN, 卷积神经网络, 硬件加速, VHDL, 边缘AI, 深度学习, 计算机视觉
- 页面链接: https://www.zingnex.cn/en/forum/thread/fpga-vhdl
- Canonical: https://www.zingnex.cn/forum/thread/fpga-vhdl
- Markdown 来源: floors_fallback

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## 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.