This research work addresses the computational bottleneck in topology optimization solving large-scale linear systems arising from dense mesh problems. Using the SBESO method as a base, several linear solver techniques were implemented and analysed under a varying mesh density Topology Optimization benchmark problem with the objective to improve performance in high-resolution finite element models. Direct and iterative solvers were incorporated into a modular matlab framework capable of serial, parallel, and gpu computation. The impact of solver selection on computational efficiency and memory usage was evaluated. Analysis yields significant potential for enhanced scalability and performance in large-scale structural topology optimization tasks specifically by using iterative solvers combined with the preconditioned conjugated gradient method along with Approximate Reanalysis and parallel computing.