Implementation of Radio Wave Propagation using RT Cores and Consideration of Programming Models

With the NVIDIA Turing architecture generation, several NVIDIA graphics processing units (GPUs) have introduced ray tracing acceleration hardware (RT cores). Ray tracing processing can be regarded as a simulation of wave and particle propagation, collision, and reflection. Therefore, it is expected to be applied to computational science and high-performance computing. However, few studies have been conducted using RT cores. The purpose of this research is to demonstrate the use of RT cores in the scientific and technical computing fields. We implemented a radio wave propagation loss calculation with the programmable ray tracing application framework OptiX and evaluated its performance. Furthermore, we investigated the challenges of reducing the description of framework-specific settings and the needs of hardware allocation. In the simple two spheres experiment, the RT core implementation showed the highest performance. Moreover, the acceleration was super linear scaling, between (10000, 5000) and (20000, 10000). In the experiment with a sphere and planes, the performance achieved by the RT cores was up to approximately 390 times higher than the parallel execution of the BVH search algorithm. We also proved that a large number of RT cores yielded higher performance. In the open data problem space experiment, we evaluated various GPUs and revealed that a larger number of RT cores is effective. These results show that RT cores are sufficiently effective for radio propagation calculations with an adequate number of ray projections. Through this research, we contributed to the RT core use in computational science by proposing an implementation method for ray tracing applications and revealing the effects of RT cores in radio wave propagation loss calculations.