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We review the basic equations, numerical solution techniques, and new application areas of a novel multi-purpose computer code framework, PISALE, for the solution of complex Partial Differential Equation (PDE) systems on modern computing platforms. We describe how the code solves equations in the fluid approximation using a novel combination of ALE and AMR methods. Sample problems from areas of ground water flow, high-speed impacts, and X-ray Free Electron Laser (XFEL) experiments are given. 

Particulate matter and small debris present in the atmosphere are known to cause substantial progressive damage to leading edges and control surfaces on hypersonic vehicles. This study seeks to predict the material responses (mechanical and thermal) to high-speed, small particle impact loading during hypersonic flight. To address such challenges, a multi-material fluid-based approach for modeling problems in this regime is examined. This method combines Arbitrary Lagrangian Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR) and multi- zone physics. The parameter regime of particles (2-5 μm) impacting a material surface at high speeds (125 - 600 ms−1) is investigated. 

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.