Unveiling Performance Insights and Portability Achievements Between CUDA and SYCL for Particle-in-Cell Codes on Different GPU Architectures

The HPC systems worldwide are getting more powerful with the combination of CPU, GPU, and other accelerators (e.g., FPGAs and Quantum Processors). Many programming frameworks mainly offer excellent support portability to the existing scientific codes to use the exascale HPC systems. This study evaluates the performance and portability of CUDA and SYCL for one of the most used plasma kinetic simulation codes Particle-In-Cell (PIC). The PIC codes are numerical modelling tools used for handling the extreme nonlinear methods in fusion devices. The experimental work showed that accelerating the PIC code with CUDA and SYCL achieve similar performance on NVIDIA devices, the latter demonstrated remarkable code portability to other GPU architectures. This brief study highlights the potential of SYCL as a viable solution for achieving both performance and portability in the heterogeneous computing ecosystem.