Engineers from wide ranges of industries face ever increasing needs for complex, realistic models to analyze the most challenging industrial problems; AcuSolve is designed to tackle these finite element-based Computational Fluid Dynamics (CFD) simulations with superior robustness, speed, and accuracy. AcuSolve simulations are designed to carry out on large-scale computational systems effectively. The breakthrough in HPC parallel computing that allows such complex analyses to be performed that generate the high-quality results, while reducing simulation time from days to just hours. Behind this type of computational improvement that makes AcuSolve perform, it involves complex calculations and data exchanges among computational systems. The more complex simulations are being performed, the higher demands from the cluster performance are. In this analysis, the HPC Advisory Council has performed a deep investigation and profiling for the AcuSolve CFD solver to evaluate its performance and scaling capabilities and to explore potential optimizations. This study presents the optimization techniques and networking profiling results to further understand AcuSolve dependencies on the CPUs, communication networks, IO subsystems and the underlying hardware. The paper will review the effects by comparing various hardware using different simulation models.