Abstract：The demand of industrial manufacturing and engineering development for simulation analysis and calculation is increasing, the scale of simulation analysis model is larger, the accuracy of the calculation is higher, there are more and more multidisciplinary simulation, all above needs more high performance computing capability. A number of independent high performance computing cluster is not enough conducive to resource sharing and efficiency. This paper presents a design method of high performance computing platform based on multi cluster.

Abstract：In the field of electricity safety, there are a lots of data and knowledge has not been excavated and utilized, constructing a knowledge graph in the electricity safety field can not only integrate power knowledge, but also greatly improve the efficiency of the power industry. Named entity recognition(NER) is the basis for constructing knowledge graph, this paper studies the named entity recognition based on dictionaries and rules, through three methods: the domain entity dictionary, the word-building feature character rule matching and the part-of-speech combination feature rule matching，to accurately extract electricity safety related entities from non-structured text, providing high-quality and high-precision entities for the construction of knowledge graph in the field of electricity safety. In order to optimize the recognition process and improve the response speed, the general part-of-speech tagging task is sent to the edge node for processing, and the central server processes the rule template matching task. Experimental results show that using the three methods comprehensively to recognition the domain entity of small-scale electricity safety text, the F1 score can reach more than 85%.

Abstract：With the rapid development of power transmission and distribution grid, power transmission and distribution services have put forward higher requirements for differentiated communication metrics such as delay, energy efficiency, and reliability. Based on the characteristics of high speed and large connectivity of 5G and flexible and wide coverage of satellite, combined with the advantages of efficient data processing of edge computing, a 5G satellite integrated networking architecture for power transmission and distribution scenarios is constructed. Then，with the optimization goal of maximizing the weighted difference between the average energy efficiency and the total delay of data offloading in the transmission and distribution services, an optimization problem of data offloading in 5G satellite integrated networking is constructed. A differentiated service requirement-aware learning-based data offloading algorithm(DSRL-DO) for 5G satellite integrated networking is proposed to solve the problem. Finally, the simulation results show that the proposed algorithm can reduce the data offloading delay while ensuring high energy efficiency, and effectively meet the differentiated requirements of power transmission and distribution services.