  Benchmarking and comparing performance of a scientific simulation across
hardware platforms is a complex task. When the simulation in question is
constructed with an asynchronous, many-task (AMT) runtime offloading work to
GPUs, the task becomes even more complex. In this paper, we discuss the use of
a uniquely suited performance measurement library, APEX, to capture the
performance behavior of a simulation built on HPX, a highly scalable,
distributed AMT runtime. We examine the performance of the astrophysics
simulation carried-out by Octo-Tiger on two different supercomputing
architectures. We analyze the results of scaling and measurement overheads. In
addition, we look in-depth at two similarly configured executions on the two
systems to study how architectural differences affect performance and identify
opportunities for optimization. As one such opportunity, we optimize the
communication for the hydro solver and investigated its performance impact.
