FPGA acceleratorMonte CarloUncertainty? 2022 The Author(s)A resource efficient hardware accelerator for Bayesian neural network (BNN) named B2N2, Bernoulli random number based Bayesian neural network accelerator
测试设计包括四百个神经元的单层,并使用FPGA上可用资源的约40%。这使其适用于边缘的时间受限应用,同时为FPGA上的其他加速任务留出空间。 关键词 SNN,LIF,MNIST,FPGA,神经加速 引言 人工神经网络是一种复杂的计算学习模型,通常利用企业数据中心和公共云基础设施的计算能力来加快训练和推理。然而,基于云的人工神经...
FPGAVGG16Floating pointFixed pointConvolutional Neural Network (CNN) has been extensively used for image recognition due to its great accuracy. This accuracy is achieved through emulating the optic nerves behavior in living human beings. The speedy progress of the current applications derived from deep...
The peak and average performances of the SNN accelerator are 5.98 TOPS and 5.14 TOPS respectively, the power consumption is 6.943 W and the energy efficiency is 0.74 TOPS/W, during the inference process. Introduction The artificial neural network (ANN) boosts in recent years, especially in the ...
题目:High-Performance FPGA-based Accelerator for Bayesian Recurrent Neural Networks 作者:Martin Ferianc, Zhiqiang Que, Hongxiang Fan, Wayne Luk, Miguel Rodrigues, 是来自IC和UCL的团队 链接: https://arxiv.org/pdf/2106.06048.pdfarxiv.org/pdf/2106.06048.pdf 总结:第一个在FPGA上做贝叶斯RNN加速...
Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks (FPGA'15) Source:Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural NetworksAbstract:尽管目前FPGA加速器已经展示出相比通用加速器更好的性能,但其设计空间未能完全发掘。… Terre...发表于论文阅读笔... 基于FPGA...
An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs Abstract 深度卷积神经网络(CNN)在广泛的应用中都实现了最先进的性能。但是,复杂的人工智能(AI)任务广泛需要更复杂的更深的CNN模型,这些模型通常对算力的要求极高。尽管最近在网络压缩方面的研究进展(例如剪枝)已经显著减轻...
Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks (FPGA'15) Abstract: 尽管目前FPGA加速器已经展示出相比通用加速器更好的性能,但其设计空间未能完全发掘。一个重要问题是计算吞吐率与内存带宽不匹配,现有设计要么不能充分利用逻辑资源,要么不能充分利用存储带宽。同时,DNN应用不断增加的...
the accelerator design space has not been well exploited. One critical problem is that the computation throughput may not well match the memory bandwidth provided an FPGA platform. Consequently, existing approaches cannot achieve best performance due to under-utilization ...
62/373,919 (Attorney Docket No. NVIDP1137+/16-SC-0139-US01) titled “Sparse Convolutional Neural Network Accelerator,” filed Aug. 11, 2016, the entire contents of which is incorporated herein by reference. This application is a continuation-in-part of U.S. application Ser. No. 15/458,...