Optimizing Data-Oriented Architecture for Generating Random Numbers Uniform with Stack Machines Indeterminate Structure

Regarding the importance of statistics and doing statistical calculations by computer, it is necessary to find the ways in accordance with advanced and new computer sciences for calculation. In this research, architecture is presented using data-oriented approach to optimize number distribution and usage of memory and expedite the computing of generating random numbers. To achieve these goals, generating random numbers has been modeled uniformly using data-oriented approach. Data-oriented approach is an approach that models the concepts as data structures and required results can be achieved through data processing and using a special memory instead of excessive calculations. In this paper, to generate uniform random numbers using data-oriented approach, non-precise stack machine structure (ADRNG) was used for modeling. Its advantage over previous approach, which was modeling with tree, is to prevent excessive use of data and to save memory and to prevent necessary time for managing excessive data. Finally, a new data-oriented architecture is presented using this model. Results from generating uniform random numbers through new approach in MATLAB stimulated environment and by calculating standard deviation and dispersion and comparing this with previous approach shows the optimization of generating uniform random numbers.