ADV MATH SCI JOURNAL Advances in Mathematics: Scientific Journal 9 (2020), no.9, 7363–7373 ISSN: 1857-8365 (printed); 1857-8438 (electronic) https://doi.org/10.37418/amsj.9.9.83 A GPU PARALLELIZATION FOR GRID GENERATION OF FUZZY TOPOGRAPHIC TOPOLOGICAL MAPPING NORMA ALIAS 1 , MUHAMMAD ZILLULLAH MUKARAM, AND TAHIR AHMAD ABSTRACT. The fundamental in grid generation for multidimensional geomet- rical shape is to construct its grid form. Techniques for creating the grid forms and the smaller shapes formed is the basis of grid generation [1]. The form it- self will determine the quality of the generation process and well grid-construc- ted to describe numerical evaluation and speed. In this paper, a structured grid for Fuzzy Topographic Topological Mapping (FTTM) is proposed to improve the quality of grid in numerical perspectives. FTTM is a mathematical model to de- tect the neuro-inverse magnetic region for neurological disorder [2]. The detec- tion region is based on 4 vertices of FTTM and homeomorphic to each other [3]. A computable homeomorphism will use to define the vertices and edges compo- nents of FTTM. The edges represent their homeomorphisms. A topology on grid generation of FTTM addresses the fuzzy topographic and mapping algorithm. The mathematical modeling of FTTM performs the grid structure, design the grid-connected and synchronize the grid generation. For large and extended FTTM, mesh refinement coupled with fine granularity is used to generate the grid via multi-component and multi-version parallelization scheme. The detail of the construction and performance of the strategy is elaborated, evaluated and reported in the paper. 1 corresponding author 2010 Mathematics Subject Classification. 65Y05, 54A40. Key words and phrases. FTTM, Parallel algorithm, grid generation, Parallel performance evaluation. 7363