https://github.com/Haleski47/RTL-Implementation-of-Two-Layer-CNN https://github.com/Di5h3z/ECE-564-Convolutional-Neural-Network-Accelerator 具有详细设计的两层 CNN 详细的设计文档: https://github.com/Haleski47/RTL-Implemen
FPGA的特点是并行和流水线处理，而CNN的特点是模块化好和参数共享，所以CNN非常适合用FPGA加速。理论上，...
基于RISC-V软核CPU的国产FPGA CNN异构方案的实现 本文原标题《Implementation of CNN Hetero geneous Scheme Based on Domestic FPGA with RISC-V Soft Core CPU》,发表于“第五届IEEE国际集成电路技术与应用学术会议(ICTA 2022)”。 作者:吴海龙, 李金东, 陈翔,电子与信息工程学院,中山大学,中国 摘要:现场可编程门...
In this context, an optimized CNN is proposed to be implemented on Pynq-Z2 board for Electrocardiography (ECG) signal class detection. As first step, a CNN has been implemented on the processor ARM Cortex A9 of Pynq Z2. Implementation results show the efficiency of our purpose, ach...
LeNet-5诞生于上世纪90年代，是CNN的开山之作，最早的卷积神经网络之一，用于手写数字识别（图像分类任务...
整体来说,cnn这种应用流水线控制相对cpu简单,没有写cpu的那一堆hazard让人烦心,也不用写汇编器啥的。太大的cnn放在fpga里挺费劲,做出创新很难,但是fpga上写个能用的lenet这种级别的cnn还是挺容易的。最后还可以依照惯例跟cpu比性能,跟gpu比功耗。
一种基于FPGA的CNN硬件加速器实现[J]. 电子技术应用,2023,49(12):20-25.英文引用格式: Qiu Zhenbo. An FPGA-based implementation of CNN hardware accelerator[J]. Application of Electronic Technique,2023,49(12):20-25.An FPGA-based implementation of CNN hardware accelerator ...
In this work, Convolutional Neural Network (CNN) is applied for defect identification of Swiven Cap (one type of medical component) based on Field-Programmable Gate Array (FPGA) implementation. Caffe is used as the platform to develop the CNN model. Afte
1 Caffe implementation of ImageNet. http://caffe.berkeleyvision.org 结论及应用 FPGA架构的独特灵活性允许将逻辑精度调整到特定网络设计所需的最小值。通过限制CNN卷积神经网络计算的比特精度,可以显着增加每秒可处理的图像数量,从而提高性能并降低功耗。 FPGA实现的非批处理方法允许在9毫秒(单帧周期)中的对象识别...
[1] C. Zhang et al, “Energy-efficient CNN implementation on a deeply pipelined FPGA cluster,” in Proc. Int. Symp. Low Power Electron. [2] N. Suda et al, “Throughput-optimized OpenCL-based FPGA accelerator for large-scale convolutional neural networks,” in Proc. ACM/SIGDA Int. [...