Harnessing billions of tasks for a scalable portable hydrodynamic simulation of the merger of two stars
| Autor: | David Pfander, Matthias Kretz, Juhan Frank, Dominic Marcello, Geoffrey C. Clayton, Patricia Grubel, Kevin Huck, Adrian Serio, David C. Eder, Thomas Heller, Dirk Pflüger, John Biddiscombe, Hartmut Kaiser, Bryce Adelstein Lelbach, Alice Koniges |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
020203 distributed computing
Computer science Adaptive mesh refinement Technische Fakultät 02 engineering and technology Parallel computing Grid Theoretical Computer Science Runtime system Stars Hardware and Architecture Asynchronous communication Scalability 0202 electrical engineering electronic engineering information engineering Programming paradigm ddc:000 Computer Science::Distributed Parallel and Cluster Computing Software |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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