R Coronae Borealis (RCB) stars are rare hydrogen-deficient carbon-rich variable supergiants thought to be the result of dynamically unstable white dwarf mergers. We attempt to model RCB stars through all the relevant timescales by simulating a merger event in Octo-tiger, a 3D adaptive mesh refinement (AMR) hydrodynamics code, and mapping the post-merger object into MESA, a 1D stellar evolution code. We then post-process the nucleosynthesis on a much larger nuclear reaction network to study the enhancement of s-process elements. We present models that match observations or previous studies in most surface abundances, isotopic ratios, early evolution, and lifetimes. We also observe similar mixing behavior to previous modeling attempts that result in the partial He-burning products visible on the surface in observations. However, we do note that our subsolar models lack any enhancement in s-process elements, which we attribute to a lack of hydrogen in the envelope. We also find that the 16O/18O isotopic ratio is very sensitive to initial hydrogen abundance and increases outside of the acceptable range with a hydrogen mass fraction greater than 10−4.
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 Cþþ parallel programming model that is embodied in the HPX library and being incorporated into the ISO Cþþ 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.
We introduce a new computer code, Octo-tiger/HPX. Octo-tiger/HPX simulates classically selfgravitating hydrodynamic fluids on an adaptive mesh refinement (AMR) grid. It is particularly suited for modeling interacting binary star systems. To that end, Octo-tiger/HPX uses special techniques to ensure the conservation of linear momentum, angular momentum, and energy to machine precision. Octo-tiger/HPX makes use of the new distributed C++ runtime system, High Performance Para eX, to enable execution on massively parallel computers.
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