  Recently, AMD platforms have not supported offloading C++17 PSTL (StdPar)
programs to the GPU. Our previous work highlights how StdPar is able to achieve
good performance across NVIDIA and Intel GPU platforms. In that work, we
acknowledged AMD's past effort such as HCC, which unfortunately is deprecated
and does not support newer hardware platforms.
  Recent developments by AMD, Codeplay, and AdaptiveCpp (previously known as
hipSYCL or OpenSYCL) have enabled multiple paths for StdPar programs to run on
AMD GPUs. This informal report discusses our experiences and evaluation of
currently available StdPar implementations for AMD GPUs. We conduct benchmarks
using our suite of HPC mini-apps with ports in many heterogeneous programming
models, including StdPar. We then compare the performance of StdPar, using all
available StdPar compilers, to contemporary heterogeneous programming models
supported on AMD GPUs: HIP, OpenCL, Thrust, Kokkos, OpenMP, SYCL. Where
appropriate, we discuss issues encountered and workarounds applied during our
evaluation.
  Finally, the StdPar model discussed in this report largely depends on Unified
Shared Memory (USM) performance and very few AMD GPUs have proper support for
this feature. As such, this report demonstrates a proof-of-concept host-side
userspace pagefault solution for models that use the HIP API. We discuss
performance improvements achieved with our solution using the same set of
benchmarks.
