Although FPGA vendors such as Altera and Xilinx have released OpenCL framework to ease the programming, tuning the OpenCL codes for desirable performance on FPGAs is still challenging. In this paper, we look int
To explore a reasonable implementation of the spiking neural networks, a novel method is proposed in which the network topology is simulated by the software simulation libraries, and the key computations are handed over to the FPGA forparallel computing to meet the requirements of easydevelopment, ...
This paper presents a hardware implementation of multilayer feedforward neural networks (NN) using reconfigurable field-programmable gate arrays (FPGAs). Despite improvements in FPGA densities, the numerous multipliers in an NN limit the size of the network that can be implemented using a single FPGA...
2020OFC论文阅读 T4D.2 FPGA Implementation of Deep Neural Network Based Equalizers for High-Speed PON,程序员大本营,技术文章内容聚合第一站。
Therefore, the implementation of CNN-based target detection algorithm accelerator using FPGA has become a hot research topic. For example, in 2016, Chen et al. designed a SIMD convolutional neural network acceleration system based on FPGA, which reduced the gap between the theoretical and actual ...
Recurrent Neural Networks (RNNs) have the ability to retain memory and learn data sequences, and are a recent breakthrough of machine learning. Due to the recurrent nature of RNNs, it is sometimes hard to parallelize all its computations on conventional
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. After training phase, a confusion matrix is...
FPGA implementation ofCellular Neural Network(CNN) Initialization CNN CNN.vis Top-level design with initialization for A, B, I template SixteenbySixteen.javagenerates Verilog code for 16x16 layer modulesixteenbysixteen.v Default CornerDetection
FPGA Implementation of the Locally Recurrent Probabilistic Neural NetworkThis study is part of the Instituto Nacional de Ciência e Tecnologia em reas midas (INAU / CNPq / UFMT), Cuiaba, Mato Grosso, Research Program on the Pantanal wetlands. The main goal of this proj…" [more]...
Neuromorphic computing is considered to be the future of machine learning, and it provides a new way of cognitive computing. Inspired by the excellent performance of spiking neural networks (SNNs) on the fields of low-power consumption and parallel compu