Hardware Acceleration

Shanghai Jiao Tong University: Accelerating LSTM Training Based on Approximate Random Dropout

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Shanghai Jiao Tong University: Accelerating LSTM Training Based on Approximate Random Dropout

Machine Heart Release Authors: Song Zhuoran, Wang Ru, Ru Dongyu, Peng Zhenghao, Jiang Li Shanghai Jiao Tong University In this article, the authors utilize the Dropout method to generate a large amount of sparsity during the neural network training process for acceleration. This paper has been accepted by the Design Automation and Test in Europe … Read more

F-CNN: Training Convolutional Neural Networks with FPGA Framework

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F-CNN: Training Convolutional Neural Networks with FPGA Framework

Author: Amber Original submission to SSD Fans, earn >= 100 CNY for articles. Since AlexNet won the ImageNet challenge in 2012, deep learning technology has been increasingly used in various fields of artificial intelligence. Among them, Convolutional Neural Networks (CNN) have excelled in image classification tasks. However, due to the high computational cost of CNNs, … Read more