在所调研的论文《Evaluating Fast Algorithm for Convolutional Neural Networks on FPGAs》中显示了FPGA加速器加速CNN的资源利用情况,如表一所示。在这些设计中,可以得出结论,DSP是消耗最多的资源,因为典型CNN的操作主要由MAC单元组成,乘法器通常由DSP在FPGA上实现。 表1 先前FPGA加速CNN的资源使用情况 除了空间卷积算...
CNN-卷积神经网络在FPGA上的实现(一)卷积神经网络(CNN)已被证明在复杂的图像识别问题上非常有效。本文将讨论如何使用 Nallatech公司基于AlteraOpenCL软件开发套件编程的FPGA加速产品来加速CNN卷积神经网络的计算。可以通过调整计算精度来优化图像分类性能。降低计算精度可使FPGA加速器每秒处理越来越多的图像。 Caffe深度学习...
This paper discusses an FPGA implementation targeted at the ImageNet CNN?– Convolutional Neural Network, however the approach used here would apply equally well to other networks. ImageNet是一个备受推荐且使用最为广泛的CNN卷积神经网络,具有免费的训练数据集和基准。 本文讨论了针对ImageNet CNN - 卷积...
该加速器在国内FPGA上的实现和部署已经完成,其性能与具有相同规模硬件资源的国外FPGA相当。 本文论证了基于国产FPGA的CNN异构方案的可行性,该研究是国产FPGA应用生态中CNN加速领域的一次罕见尝试。 REFERENCES: [1]Zhang. C, et al. "Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks. ...
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,对于低延迟至关重要的情况是理想的,例如障碍物避让,可以做到大于100Hz的帧速率分类图像。 The intrinsic scalability demonstrated by our FPGAimplementation can be utilized to implement complex CNN – Convolutional Neural Networks on increasingly smaller...
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...
fully functionalproof-of-concept CNN implementation on a Zynq System-on-Chip. The ZynqNetEmbedded CNN is designed for image classification on ImageNet and consists of ZynqNetCNN, an optimized and customized CNN topology, and the ZynqNet FPGAAccelerator, an FPGA-based architecture for its evaluation....
An implementation of CNN-UM on Field Programmable Gate Arrays (FPGA) appears attractive because their full computational power comes to a life only in hardware. Besides FPGA there are many different possibilities to implement a CNN-UM. The following questions will be answered while reading this ...
whichsignifi-cantlyreducesoperationsandparameterswithonlylimitedlossinaccuracy.Thishighlystructuredmodelisverysuitableforfield-programmablegatearray(FPGA)implementation.Inthisbrief,ascalablehighperformancedepthwiseseparableconvo-lutionoptimizedCNNacceleratorisproposed.TheacceleratorcanbefitintoanFPGAofdifferentsizes,...
Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs Convolutional neural networks (CNNs) have been widely applied in many deep learning applications. In recent years, the FPGA implementation for CNNs has att... X Wei,CH Yu,Z Peng,... - Design Automation ...