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A New Load Balancing Approach for Coupled Multi-Physics Simulations

机译:一种新的负载平衡方法,用于耦合多物理模拟

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The simulation of multi-physics and multi-scale problems requires very highly scalable approaches to be efficient on today's supercomputers. Thus, the need of scalable approaches to realise large problems in a feasible time has to be addressed respectively. In this paper, we present an approach to run such complex simulations more efficiently by proposing a new load balancing approach across several solvers used in a partitioned simulation. We demonstrate the applicability of the approach for a small academic test case representing a fluid-acoustic coupling. The partitioned approach allows for a different treatment of each subdomain, hence the best-suited configuration for each of them. We show how well our approach is scalable by running scalability measurements on the SuperMUC supercomputer at the LRZ supercomputing center. The central issue in partitioned simulation that we address in this paper is the inter-solver load imbalance. We present a new method to efficiently distribute the total number of requested cores between the solvers to reduce or ideally remove the time that one solver needs to wait until the other one finishes its computation. To demonstrate the effectiveness of our proposed method, we use a simple Gaussian pulse located inside a cubic domain. The domain is decomposed into an inner and an outer subdomains, while the pulse is located in the inner part and it spreads over the time to the outer subdomain. In the inner domain, we solve the Euler equations while in the outer domain a linearized set of Euler equations is solved. We use a two-way explicit coupling, i.e., the inner part provides its values at the coupling interface to the outer subdomain and receives information from the outer subdomain. This procedure is done for the outer domain as well. Hence both domains provide and receive information from each other. It is obvious that, if one of the solvers is slower, the other one will be idle at the end of each time step. For communication and data exchange between the subdomains, we use the preCICE coupling library. Numerical results show that the presented framework can scale up to (at least) 560 cores. In addition, the proposed load balancing method is able to almost remove the load imbalance between the coupling partners. The effect of using this method is significant and in most cases that we simulated, the run-time could be reduced by more than 40 percents in comparison to the results of the old load-balancing scheme.
机译:多物理和多尺度问题的模拟需要非常高度可扩展的方法,以便在今天的超级计算机上有效。因此,必须分别解决可扩展方法来实现在可行时间中的大问题。在本文中,我们通过在分区模拟中使用的几个求解器上提出新的负载平衡方法,更有效地提供一种方法来更有效地运行这种复杂模拟。我们展示了代表流体声耦合的小型学术测试箱的方法的适用性。分区方法允许对每个子域的不同处理,因此对每个子域进行最适合的配置。我们展示了通过在LRZ超级计算中心的SuperMuc超级计算机上运行可扩展性测量来缩放的方法如何进行扩展。我们在本文中的分区模拟中的核心问题是辅助际负载不平衡。我们提出了一种新的方法,可以有效地分布求解器之间所请求的核心总数,以减少或理想地删除一个解决措施需要等待的时间,直到另一个求解器才能完成其计算。为了展示我们所提出的方法的有效性,我们使用位于立方域内的简单高斯脉冲。域将域分解成内部和外部子域,而脉冲位于内部部分中,并且它将时间传播到外部子域。在内部结构域中,我们在外部域中解决了欧拉方程,解决了线性化的欧拉方程组。我们使用双向显式耦合,即内部部分在耦合接口处提供给外部子域的值,并从外部子域接收信息。此过程也为外部域完成。因此,两个域都提供和接收彼此的信息。很明显,如果其中一个求解器较慢,则另一个求解器在每次步骤结束时都会空转。对于子域之间的通信和数据交换,我们使用Precice耦合库。数值结果表明,所提出的框架可以扩展到(至少)560核。另外,所提出的负载平衡方法能够几乎去除耦合伙伴之间的负载不平衡。使用该方法的效果是显着的,在大多数情况下,我们模拟的情况下,与旧负载平衡方案的结果相比,运行时间可以减少超过40%。

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