A new type of mass structured data duplicate data check

Abstract

In this study, the data processing method of a large-scale isoface is used to reduce the storage space of internal memory, improve data structure, and achieve predictability. The design of an algorithm mainly includes the following tasks: increasing the operation speed by improving the parallel granular of the GPU, finishing the segmentation of the adaptive tetrahedral octree, calculating the dual points through the quadric error function in four-dimensional space, searching for the minimum edge as well as finishing the data structure of the edge and the design of the octree node, and proposing that the algorithm be constantly performed until all levels of the minimum edge are found. The result of the algorithm design for the large-scale data is that the speed of parallel algorithms improves and the effect becomes more obvious. Research on large-scale data access high-speed ratio and structure improvement have experimental and theoretical reference value.