A study of parallel logic programming (PLP), efficient data structuring, and educational visualization is presented in this work. Yet, there are two major problems associated with PLP systems: the redundant computation that occurs during and the parallel execution of dependent goals, and the efficient management of multiple runtime environments. In order to address the latter problem, this study introduces the Segmented Parallel Block Array (SPBA), a memory-optimized data structure intended to support a variety of parallel processing algorithms. The purpose of this is to enhance the performance of PLP systems. Another critical aspect of algorithm design is the use of Data Structure and Algorithm Visualization (DSAV). Through its contribution to practical, real-world applications, DSAV promotes an understanding of algorithms that extends beyond traditional theoretical analyses. This work explores the educational potential of web-based visualizations, presenting a methodology to assist students and educators in gaining an understanding of practical implementation of algorithms and data structures. The proposed methods also advance smart energy systems by facilitating efficient algorithm modeling and simulation techniques for electric vehicles and microgrids, particularly in contexts demanding high-performance parallel processing and secure computation.