Physics-based seismic hazard analysis on petascale heterogeneous supercomputers

Yifeng Cui, E. Poyraz, K. Olsen, Jun Zhou, K. Withers, S. Callaghan, J. Larkin, C. Guest, D. J. Choi, A. Chourasia, Zheqiang Shi, S. Day, P. Maechling, T. Jordan
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引用次数: 65

Abstract

We have developed a highly scalable and efficient GPU-based finite-difference code (AWP) for earthquake simulation that implements high throughput, memory locality, communication reduction and communication / computation overlap and achieves linear scalability on Cray XK7 Titan at ORNL and NCSA's Blue Waters system. We simulate realistic 0-10 Hz earthquake ground motions relevant to building engineering design using high-performance AWP. Moreover, we show that AWP provides a speedup by a factor of 110 in key strain tensor calculations critical to probabilistic seismic hazard analysis (PSHA). These performance improvements to critical scientific application software, coupled with improved co-scheduling capabilities of our workflow-managed systems, make a statewide hazard model a goal reachable with existing supercomputers. The performance improvements of GPU-based AWP are expected to save millions of core-hours over the next few years as physics-based seismic hazard analysis is developed using heterogeneous petascale supercomputers.
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基于物理的千万亿次异构超级计算机地震危险性分析
我们开发了一种高度可扩展和高效的基于gpu的有限差分代码(AWP),用于地震模拟,实现了高吞吐量、内存局域性、通信减少和通信/计算重叠,并在ORNL的Cray XK7 Titan和NCSA的Blue Waters系统上实现了线性可扩展性。我们使用高性能AWP模拟与建筑工程设计相关的真实0-10 Hz地震地面运动。此外,我们表明AWP在概率地震危害分析(PSHA)的关键应变张量计算中提供了110倍的加速。这些关键科学应用软件的性能改进,加上我们的工作流管理系统改进的协同调度能力,使全州范围的危害模型成为现有超级计算机可以实现的目标。基于gpu的AWP的性能改进有望在未来几年内节省数百万核小时,因为基于物理的地震危害分析是使用异构千兆级超级计算机开发的。
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