  The increasing availability of machines relying on non-GPU architectures,
such as ARM A64FX in high-performance computing, provides a set of interesting
challenges to application developers. In addition to requiring code portability
across different parallelization schemes, programs targeting these
architectures have to be highly adaptable in terms of compute kernel sizes to
accommodate different execution characteristics for various heterogeneous
workloads. In this paper, we demonstrate an approach to code and performance
portability that is based entirely on established standards in the industry. In
addition to applying Kokkos as an abstraction over the execution of compute
kernels on different heterogeneous execution environments, we show that the use
of standard C++ constructs as exposed by the HPX runtime system enables superb
portability in terms of code and performance based on the real-world Octo-Tiger
astrophysics application. We report our experience with porting Octo-Tiger to
the ARM A64FX architecture provided by Stony Brook's Ookami and Riken's
Supercomputer Fugaku and compare the resulting performance with that achieved
on well established GPU-oriented HPC machines such as ORNL's Summit, NERSC's
Perlmutter and CSCS's Piz Daint systems. Octo-Tiger scaled well on
Supercomputer Fugaku without any major code changes due to the abstraction
levels provided by HPX and Kokkos. Adding vectorization support for ARM's SVE
to Octo-Tiger was trivial thanks to using standard C++
