The rapid evolution of multicore processor architectures has intensified the demand for efficient cache management Wind energy has emerged as a vital component of sustainable power generation, but maximizing its efficiency depends largely on the aerodynamic design of turbine blades. The present study focuses on the aerodynamic optimization of horizontal axis wind turbine blades using Computational Fluid Dynamics (CFD). Blade models were analyzed using ANSYS Fluent under varying wind speeds and angles of attack to evaluate lift, drag, and pressure distribution. Parametric optimization techniques were applied to modify chord length, twist angle, and airfoil geometry to enhance performance. Results indicate that optimized blade configurations achieved up to 14 percent improvement in power coefficient compared to baseline models, with a significant reduction in drag-to-lift ratio. Streamline and pressure contour analysis confirmed smoother flow separation and improved aerodynamic efficiency. The findings highlight that CFD-driven optimization is an effective approach for designing high-performance wind turbine blades, enabling greater energy capture and supporting the transition to renewable energy systems.