A Fault Tolerant Implementation for a Massively Parallel Seismic Framework

Suha N. Kayum, H. Alsalim, T. Tonellot, A. Momin
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引用次数: 1

Abstract

An increase in the acquisition of seismic data volumes has resulted in applications processing seismic data running for weeks or months on large supercomputers. A fault occurring during processing would jeopardize the fidelity and quality of the results, hence necessitating a resilient application. GeoDRIVE is a High-Performance Computing (HPC) software framework tailored to massive seismic applications and supercomputers. A fault tolerance mechanism that capitalizes on Boost.asio for network communication is presented and tested quantitatively and qualitatively by simulating faults using fault injection. Resource provisioning is also illustrated by adding more resources to a job during simulation. Finally, a large-scale job of 2,500 seismic experiments and 358 billion grid elements is executed on 32,000 cores. Subsets of nodes are killed at different times, validating the resilience of the mechanism in large scale. While the implementation is demonstrated in a seismic application context, it can be tailored to any HPC application with embarrassingly parallel properties.
大规模并行地震框架的容错实现
地震数据采集量的增加导致处理地震数据的应用程序在大型超级计算机上运行数周或数月。在处理过程中发生的错误将危及结果的保真度和质量,因此需要弹性应用程序。GeoDRIVE是为大规模地震应用和超级计算机量身定制的高性能计算(HPC)软件框架。一种利用Boost的容错机制。通过故障注入模拟故障,提出了网络通信的Asio,并对其进行了定量和定性的测试。通过在模拟期间向作业添加更多资源,还可以说明资源配置。最后,在32000个岩心上执行了2500个地震实验和3580亿个网格单元的大规模工作。节点子集在不同的时间被杀死,验证了大规模机制的弹性。虽然实现是在地震应用环境中演示的,但它可以适用于任何具有令人尴尬的并行特性的高性能计算应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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