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Currently, the area of geometric modeling and the construction of 3D modelsbased on point clouds from laser sensors is actively developing. One of thebasic tasks of geometric modeling is the reconstruction of a surface from acloud of points. The aim of this work is to develop a parallel least-squaressurface reconstruction method on a distributed memory supercomputer that allowsachieving optimal results both in scalability and surface reconstructionquality. The focus of the work is on the surface reconstruction algorithm basedon the least squares method, in connection with which the algorithm was calledthe moving least squares method.

Investigation of the efficiency of the moving least squares method in the reconstruction of a three-dimensional surface on a supercomputer