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首页> 外文期刊>Advances in Engineering Software >Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids
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Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids

机译:非结构化3D Eulerian网格上可压缩流的异步分布式存储器任务算法

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摘要

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 × 10~9 cells at (10~4) compute cores and the benefits of automatic load balancing for irregular workloads. '
机译:我们讨论了一种有限元方法的实现,用于使用异步运行时系统(RTS)进行数字解决可压缩流的欧拉方程。该算法用于分布式存储器,使用静止非结构化的3D网格,组合数据 - 以及在Charm ++ RT的顶部上的数据和任务并行性。默认情况下,Charm ++的执行模型是异步的,允许随意重叠计算和通信。任务并行性允许算法的调度部分独立于或依赖于彼此。内置自动负载均衡可以通过基于实时CPU负载测量来迁移工作单元的持续重新分配计算负载。 RTS还具有自动检查点,容错,抵御硬件故障的抵抗力,支持功率和能量感知计算。我们在(10〜4)计算核心上展示了高达25×10〜9个细胞的可扩展性以及用于不规则工作负载的自动负载平衡的益处。 '

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