Performance Measurements Within Asynchronous Task-Based Runtime Systems: A Double White Dwarf Merger as an Application

Analyzing performance within asynchronous many-task-based runtime systems is challenging because millions of tasks are launched concurrently. Especially for long-term runs, the amount data collected becomes overwhelming. We study HPX and its performance-counter framework autonomic environment Exascale to collect energy consumption. added application-specific counters Octo-Tiger full 3-D adaptive multigrid code astrophysics application. This enables combined visualization physical highlight bottlenecks with respect different solvers. examine overhead introduced by these measurements, which around 1%, overall application runtime. perform a resolution four levels refinement analyze application's grid refinement. The measurements' overheads small, enabling use properties goal improving code's performance. All runs were obtained on NERSC's Cori, Louisiana Optical Network Infrastructure's QueenBee2, Indiana University's Big Red 3.