模拟神经网络传输的职业教育视频资源开发

Development of Video Resources in Vocational Education Based on Simulated Neural Network Transmission

面对职业教育视频资源在传输过程中网络结构和硬件资源占用关系这一问题,论文利用矩阵乘法改进了全连接深度神经网络(DNN)的矩阵计算形式,以此动态模拟职业教育视频资源传输状态。将矩阵乘法引入DNN前向传播过程使计算简化,以探究职业教育视频资源库作为硬件实现平台,基于乘累加器IP核与乘加器IP核设计了两种矩阵乘法计算架构,实现了模拟全连接DNN前向传播的职业教育视频资源传输计算过程,并对两种方案在实现不同结构的前向传播计算时的硬件资源占用情况进行对比,得出结论:在实现相同网络的视频资源传播计算情况下,乘累加器方案比乘加器方案消耗更少的硬件资源。

In the face of the problem of network structure and hardware resource occupancy in video transmission in vocational education,this paper uses matrix multiplication to improve the matrix calculation form of full connection depth neural network(DNN)to dynamically simulate the video resources of vocational education Transmission status.The matrix multiplication is introduced into the DNN forward propagation process to simplify the calculation to explore the vocational education video resource library as the hardware implementation platform.Based on the accumulator IP core and the multiplier IP core,two matrix multiplication algorithms are designed to realize the simulation connecting the DNN forward communication of the vocational education video resource transmission calculation process,and the two programs in the realization of the different structure of the forward communication calculation of hardware resource occupancy compared to the conclusion:in the realization of the same network of video resource propagation calculation in the case of a multiplier,the multiplier scheme consumes less hardware resources than the multiplier scheme.