基于交叉乘法器多数据流协同算法的计算机辅助实验室研究

Hao Wu Hao Wu, Xiao Xu Hao Wu, Ninghui Guo Xiao Xu, Zinan Peng Ninghui Guo, Yujia Zhai Zinan Peng, Sijia Wu Yujia Zhai
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引用次数: 0

摘要

本文开发了一套基于网格数据云平台的移动实验室。本实验室提出了一种基于跨总线四层时空模型和交叉乘法器的多数据流协同算法。该算法实现了对大部分数据流进行整体更新的目的。系统建立了多角度的数据流统计分析系统,对多个数据流进行挖掘和监控。本文将大多数数据流划分为若干线性模块,并形成相应的矩阵。最后,本文的仿真测试结果表明,基于电网的移动实验室计算机辅助系统的CPU占用非常小。系统处理效率高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Computer Aided Laboratory Based on Cross-Multiplier Multi-Data Flow Collaborative Algorithm
The paper develops a set of mobile laboratories based on the grid data cloud platform. The laboratory proposed a multi-data flow cooperative algorithm based on a cross-bus four-layer temporal space model and a cross-directional multiplier. This algorithm achieves the purpose of updating most data streams as a whole. The system establishes a statistical analysis system of data flow from multiple perspectives and mines and monitors multiple data flows. The paper divides most data streams into several linear modules, and corresponding matrices are formed. Finally, the simulated test results of the paper show that the CPU usage of the mobile laboratory computer-aided system based on the power network is very small. The system processing efficiency is high.  
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