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Octo-Tiger is a code for modeling three-dimensional self-gravitating astrophysical fluids. It was particularly designed for the study of dynamical mass transfer between interacting binary stars. Octo-Tiger is parallelized for distributed systems using the asynchronous many-task runtime system, the C++ standard library for parallelism and concurrency (HPX) and utilizes CUDA for its gravity solver. Recently, we have remodeled Octo-Tiger’s hydro solver to use a three-dimensional reconstruction scheme. In addition, we have ported the hydro solver to GPU using CUDA kernels. We present scaling results for the new hydro kernels on ORNL’s Summit machine using a Sedov-Taylor blast wave problem. We also compare Octo-Tiger’s new hydro scheme with its old hydro scheme, using a rotating star as a test problem. 

ABSTRACT octo-tiger is an astrophysics code to simulate the evolution of self-gravitating and rotating systems of arbitrary geometry based on the fast multipole method, using adaptive mesh refinement. octo-tiger is currently optimized to simulate the merger of well-resolved stars that can be approximated by barotropic structures, such as white dwarfs (WDs) or main-sequence stars. The gravity solver conserves angular momentum to machine precision, thanks to a ‘correction’ algorithm. This code uses hpx parallelization, allowing the overlap of work and communication and leading to excellent scaling properties, allowing for the computation of large problems in reasonable wall-clock times. In this paper, we investigate the code performance and precision by running benchmarking tests. These include simple problems, such as the Sod shock tube, as well as sophisticated, full, WD binary simulations. Results are compared to analytical solutions, when known, and to other grid-based codes such as flash. We also compute the interaction between two WDs from the early mass transfer through to the merger and compare with past simulations of similar systems. We measure octo-tiger’s scaling properties up to a core count of ∼80 000, showing excellent performance for large problems. Finally, we outline the current and planned areas of development aimed at tackling a number of physical phenomena connected to observations of transients. 

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.