Accelerating Electromagnetic Field Simulations Based on Memory-Optimized CPML-FDTD with OpenACC

Abstract

Although GPUs can offer higher computing power at low power consumption, their low-level programming can be relatively complex and consume programming time. For this reason, directive-based alternatives such as OpenACC could be used to specify high-level parallelism without original code modification, giving very accurate results. Nevertheless, in the FDTD method, absorbing boundary conditions are commonly used. The key to successful performance is correctly implementing the boundary conditions that play an essential role in memory use. This work accelerates the simulations of electromagnetic wave propagation that solve the Maxwell curl equations by FDTD using CMPL boundary in TE mode using OpenACC directives. A gain of acceleration optimizing the use of memory is shows, checking the loops intensities, and the use of single precision to improve the performance is also analyzed, producing an acceleration of around 5X for double precision and 11X for single precision respectively, comparing with the serial vectorized version, without introducing errors in long-term simulations. The scenarios of simulation established are common of interest and are solved at different frequencies supported by a Mid-range cards GeForce RTX 3060 and Titan RTX.

Accelerated Medical Microwave Tomography via Heterogeneous Computing

“…The computation in the CPML regions is likewise incorporated into the kernels updating the H and E fields. Other implementations either expand the CPML region to whole domain and assign zero values at the non-boundary regions [32], [33] or update the CPML regions into multiple independent kernels [33], [34]. The first approach increases unnecessarily the memory requirements.…”