%0 Journal Article
%T Harnessing billions of tasks for a scalable portable hydrodynamic simulation of the merger of two stars
%A Adrian Serio
%A Alice E Koniges
%A Bryce Adelstein Lelbach
%A David Eder
%A David Pfander
%A Dirk Pfl¨¹ger
%A Dominic Marcello
%A Geoffrey C Clayton
%A Hartmut Kaiser
%A John Biddiscombe
%A Juhan Frank
%A Kevin A Huck
%A Matthias Kretz
%A Patricia Grubel
%A Thomas Heller
%J The International Journal of High Performance Computing Applications
%@ 1741-2846
%D 2019
%R 10.1177/1094342018819744
%X We present a highly scalable demonstration of a portable asynchronous many-task programming model and runtime system applied to a grid-based adaptive mesh refinement hydrodynamic simulation of a double white dwarf merger with 14 levels of refinement that spans 17 orders of magnitude in astrophysical densities. The code uses the portable C++ parallel programming model that is embodied in the HPX library and being incorporated into the ISO C++ standard. The model represents a significant shift from existing bulk synchronous parallel programming models under consideration for exascale systems. Through the use of the Futurization technique, seemingly sequential code is transformed into wait-free asynchronous tasks. We demonstrate the potential of our model by showing results from strong scaling runs on National Energy Research Scientific Computing Center¡¯s Cori system (658,784 Intel Knight¡¯s Landing cores) that achieve a parallel efficiency of 96.8% using billions of asynchronous tasks
%K Parallel runtime
%K binary star merger
%K asynchronous tasks
%K HPX
%K C++
%U https://journals.sagepub.com/doi/full/10.1177/1094342018819744