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Wavelet-adaptive solvers on multi-core architectures for the simulation of complex systems

机译:多核架构上的小波自适应求解器,用于复杂系统的仿真

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We build wavelet-based adaptive numerical methods for the simulation of advection-dominated flows that develop multiple spatial scales, with an emphasis on fluid mechanics problems. Wavelet-based adaptivity is inherently sequential and in this work we demonstrate that these numerical methods can be implemented in software that is capable of harnessing the capabilities of multi-core architectures while maintaining their computational efficiency. Recent designs in frameworks for multi-core software development allow us to rethink parallelism as task-based, where parallel tasks are specified and automatically mapped onto physical threads. This way of exposing parallelism enables the parallelization of algorithms that were considered inherently sequential, such as wavelet-based adaptive simulations. In this paper we present a framework that combines wavelet-based adaptivity with the task-based parallelism. We demonstrate the promising performance obtained by simulating various physical systems on different multi-core architectures using up to 16 cores.
机译:我们建立了基于小波的自适应数值方法来模拟以对流为主的流动,该流动发展了多个空间尺度,重点是流体力学问题。基于小波的适应性本质上是顺序的,在这项工作中,我们证明了这些数值方法可以在软件中实现,该软件能够利用多核体系结构的功能,同时保持其计算效率。多核软件开发框架中的最新设计使我们能够重新考虑将并行性视为基于任务的方法,在该方法中,并行任务被指定并自动映射到物理线程上。这种公开并行性的方式可以使被认为是固有顺序的算法并行化,例如基于小波的自适应仿真。在本文中,我们提出了一个结合了基于小波的适应性和基于任务的并行性的框架。我们演示了通过使用多达16个内核在不同的多核体系结构上模拟各种物理系统而获得的有希望的性能。

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