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A two-scale method using a list of active sub-domains for a fully parallelized solution of wave equations

机译:一种使用活动子域列表的完全尺度波动方程的两尺度方法

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Wave form modeling is used in a vast number of applications. Therefore, different methods have been developed that exhibit different strengths and weaknesses in accuracy, stability and computational cost. The latter remains a problem for most applications. Parallel programming has had a large impact on wave field modeling since the solution of the wave equation can be divided into independent steps. The finite difference solution of the wave equation is particularly suitable for GPU acceleration; however, one problem is the rather limited global memory current CPUs are equipped with. For this reason, most large-scale applications require multiple GPUs to be employed. This paper proposes a method to optimally distribute the workload on different GPUs by avoiding devices that are running idle. This is done by using a list of active sub-domains so that a certain sub-domain is activated only if the amplitude inside the subdomain exceeds a given threshold. During the computation, every CPU checks if the sub-domain needs to be active. If not, the CPU can be assigned to another sub-domain. The method was applied to synthetic examples to test the accuracy and the efficiency of the method. The results show that the method offers a more efficient utilization of multi-CPU computer architectures. (C) 2015 The Author. Published by Elsevier B.V.
机译:波形建模被广泛应用。因此,已经开发出在准确性,稳定性和计算成本上表现出不同优点和缺点的不同方法。对于大多数应用而言,后者仍然是一个问题。并行编程对波场建模有很大的影响,因为波动方程的解可以分为独立的步骤。波动方程的有限差分解特别适用于GPU加速。但是,一个问题是当前CPU配备的全局内存有限。因此,大多数大型应用程序需要使用多个GPU。本文提出了一种通过避免设备处于空闲状态来在不同GPU上最佳分配工作负载的方法。这是通过使用活动子域的列表来完成的,以便仅在子域内的幅度超过给定阈值时才激活某个子域。在计算期间,每个CPU都会检查子域是否需要处于活动状态。如果不是,则可以将CPU分配给另一个子域。将该方法应用于合成实例,验证了方法的准确性和有效性。结果表明,该方法可以更有效地利用多CPU计算机体系结构。 (C)2015作者。由Elsevier B.V.发布

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