Accumulating knowledge for a performance portable kinetic plasma simulation code with Kokkos and directives

Asahi, Yuichi   ; Latu, G.*; Bigot, J.*; Grandgirard, V.*

To prepare the performance portable version of the kinetic plasma simulation code, we develop a simplified but self-contained semi-Lagrangian mini-app with Kokkos performance portable framework and OpenMP/OpenACC which works on both CPUs and GPUs. We investigate the performance of the mini-app over the novel arm-based processor Fujitsu A64FX, Nvidia Tesla GPU, and Intel Skylake, where the arm-based architectures and GPUs are supposed to be major architectures in the exa-scale supercomputing era. The porting cost is highly suppressed with both Kokkos and directive implementations, where the code duplication is avoided. The higher performance portability is achieved with OpenMP/OpenACC, particularly for the compute intense kernels among the hotspots. Unfortunately, a relatively low performance is obtained on A64FX for kernels with indirect memory accesses. We also discuss what kind of Kokkos/OpenMP/OpenACC features are useful to improve the readability and productivity.