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Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids
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DOI：10.1016/j.advengsoft.2020.102962.png)
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Abstract
En 中文
We discuss the implementation of a finite element method, used to numerically solve the Euler equations of compressible flows, using an asynchronous runtime system (RTS). The algorithm is implemented for distributed-memory machines, using stationary unstructured 3D meshes, combining data-, and task-parallelism on top of the Charm++ RTS. Charm++'s execution model is asynchronous by default, allowing arbitrary overlap of computation and communication. Task-parallelism allows scheduling parts of an algorithm independently of, or dependent on, each other. Built-in automatic load balancing enables continuous redistribution of computational load by migration of work units based on real-time CPU load measurement. The RTS also features automatic checkpointing, fault tolerance, resilience against hardware failure, and supports power-, and energy-aware computation. We demonstrate scalability up to 25 x 10(9) cells at O(10(4)) compute cores and the benefits of automatic load balancing for irregular workloads. The full source code with documentation is available at https://quinoacomputing.org.
Keywords:
Shock hydrodynamics
Finite element method
Flux-corrected transport
Charm plus
Automatic load balancing
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