.png){kind=icon}
返回
Hardware Implementation of Energy Efficient Deep Learning Neural Network Based on Nanoscale Flash Computing Array
.png){kind=icon}
PRE
AI
DOI：10.1002/admt.201800720.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Deep learning neural network (DNN) can provide efficient approaches to process the increasing unstructured data, such as images, audio, and video. To improve the computing power and the energy efficiency of data processing in DNN, a universal and reconfigurable computing paradigm with the hardware implementation scheme including the convolution, pooling, and fully connected layers is developed based on nanoscale flash computing arrays, which can be massively fabricated. Via precisely tuning the threshold voltage, the fabricated 65 nm nanoscale flash cells can exhibit 16 levels (four bits) of storage states. To confirm the feasibility of the computing paradigm, an exemplary five-layer DNN is simulated based on the measured data from the nor-type (NOR) flash memory and exhibits 97.8% recognition accuracy of Modified National Institute of Standards and Technology (MNIST) handwritten digit database with the speed of 4.2 x 10(5) fps at 104 MHz operating frequency. The proposed paradigm with low energy and chip cost shows great promise for future energy efficient and massively parallel data processing of DNN.
Keyword:
deep learning
energy efficiency
hardware acceleration
in-memory computing
nanoscale flash
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.2
论文数:
5.3K
被引数:
2.4W
机构
引用论文
Mimicking Biological Synaptic Functionality with an Indium Phosphide Synaptic Device on Silicon for Scalable Neuromorphic Computing.png)
ACS NANO
ACS NANOIF16
PREAI
分享收藏A Functional Hybrid Memristor Crossbar-Array/CMOS System for Data Storage and Neuromorphic Applications用于数据存储和神经形态应用的功能性混合忆阻器交叉阵列/CMOS系统NANO LETTERS
NANO LETTERSIF9.1
PREAI
分享收藏HfOx-Based Vertical Resistive Switching Random Access Memory Suitable for Bit-Cost-Effective Three-Dimensional Cross-Point ArchitectureACS NANO
ACS NANOIF16
PREAI
分享收藏分享收藏Neuro-Inspired Computing With Emerging Nonvolatile Memory具有新兴非易失性存储器的神经启发计算PROCEEDINGS OF THE IEEE
OAAI
PROCEEDINGS OF THE IEEEIF25.9
OAAI分享收藏Electronic system with memristive synapses for pattern recognition用于模式识别的具有忆阻突触的电子系统SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏
查看更多内容