The current challenge involves developing performance-portable and maintainable code for AI methods, in general, on HPC systems. This task will become even more challenging with the increasing heterogeneity of HPC systems. In a typical HPC system, internode communication is necessary and the message passing interface (MPI) has proven to be a flexible and effective solution for doing this. The socalled MPI+X paradigm combines MPI with intra-node parallelization models and/or accelerator offloading models (X). The choice of accelerator offloading model is largely determined by the specific accelerators in use, together with problem requirements and personal taste.