High-performance scientific simulations require computational systems capable of handling large-scale numerical models with high accuracy and efficiency. Traditional standalone programming environments often fail to meet the growing demands of modern scientific computing due to limitations in speed, scalability, and hardware utilization. This paper proposes a hybrid computational framework integrating C/C++ and MATLAB to leverage the strengths of both low-level high-performance programming and high-level numerical computing environments. The framework is designed to support parallel processing, GPU acceleration, and hardware-level optimization using technologies such as CUDA, FPGA, and GPU computing architectures. The proposed system is particularly suitable for applications in photovoltaic system modeling, signal processing, and large-scale scientific simulations. The paper discusses architecture design, implementation strategies, and performance considerations while referencing established research in high-performance computing and simulation methodologies.

High-Performance Computing (HPC), Hybrid Computational Framework, C/C++ Programming, MATLAB Simulation

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