Optimization of Parallel Computing Algorithms for Electromagnetic Field Simulation in Next-Generation Antenna Design
DOI:
https://doi.org/10.70062/jeci.v1i3.229Keywords:
Antenna design, CUDA, Electromagnetic field simulations, FDTD, Parallel processingAbstract
Modern antenna design faces significant challenges in terms of simulation time and accuracy for electromagnetic (EM) field simulations. These simulations, especially those involving large-scale or complex antenna designs, are heavily reliant on intensive computations that require substantial computational resources. To address this, parallel computing approaches using GPUs (Graphics Processing Units) through the CUDA (Compute Unified Device Architecture) platform have shown significant results in accelerating EM simulations. In this study, we implemented CUDA-based parallel processing to improve the efficiency of electromagnetic field simulations in antenna design. By utilizing simulation methods such as FDTD (Finite Difference Time Domain) and MoM (Method of Moments), we achieved a reduction in simulation time by up to 40%, with speedups of up to 40.16× for FDTD simulations and approximately 10 times faster for MoM simulations. Additionally, memory optimization and algorithm improvements, such as memory coalescing and shared memory usage, ensured that the speedup did not sacrifice simulation accuracy. While there were challenges in adapting sequential algorithms to parallel execution and managing memory on the GPU, the use of profiling tools helped identify and resolve performance bottlenecks. The findings of this research demonstrate the effectiveness of CUDA-based processing in accelerating EM field simulations, which has significant implications for antenna design cycles. Future research could focus on further improving parallel processing algorithms and expanding the use of GPU acceleration in other antenna design simulation areas.
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