Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights
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表征存储故障对 HPC 应用程序的影响：方法和见解
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Dingwen Tao
中科院分区：
文献类型：
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作者：
Bo Fang;Daoce Wang;Sian Jin;Q. Koziol;Zhao Zhang;Qiang Guan;S. Byna;S. Krishnamoorthy;Dingwen Tao
近年来，随着科学模拟日益复杂，人工智能模型的训练需求日益增长，需要大量、快速的数据访问，这促使高性能计算（HPC）平台配备更先进的存储基础设施，如固态硬盘（ssd）。虽然ssd提供高性能的I/O，但HPC应用程序在ssd相关故障下面临的可靠性挑战仍然不清楚，特别是导致数据损坏的故障。本文的目标是了解ssd相关故障对复杂HPC应用程序行为的影响。为此，我们提出了基于fuse的故障注入框架FFIS，该框架系统地将存储故障引入应用层，从而对ssd产生的错误进行建模。FFIS能够将不同的I/O相关故障植入到从底层文件系统返回的数据中，从而能够对科学文件格式的错误恢复特性进行调查。我们用三个具有代表性的真实HPC应用程序演示了FFIS的使用，展示了每个应用程序如何对数据损坏做出反应，并提供了对HPC应用程序广泛采用的HDF5文件格式的错误弹性的见解。
In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses, which urges high-performance computing (HPC) platforms to equip with more advanced storage infrastructures such as solid-state disks (SSDs). While SSDs offer high-performance I/O, the reliability challenges faced by the HPC applications under the SSD-related failures remains unclear, in particular for failures resulting in data corruptions. The goal of this paper is to understand the impact of SSD-related faults on the behaviors of complex HPC applications. To this end, we propose FFIS, a FUSE-based fault injection framework that systematically introduces storage faults into the application layer to model the errors originated from SSDs. FFIS is able to plant different I/O related faults into the data returned from underlying file systems, which enables the investigation on the error resilience characteristics of the scientific file format. We demonstrate the use of FFIS with three representative real HPC applications, showing how each application reacts to the data corruptions, and provide insights on the error resilience of the widely adopted HDF5 file format for the HPC applications.
通过细粒度速率-质量建模进行宇宙学模拟的原位有损压缩的自适应配置
DOI：
10.1145/3431379.3460653
发表时间：
2021
期刊：
The 30th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2021
影响因子：
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作者：
Jin, Sian;Pulido, Jesus;Grosset, Pascal;Tian, Jiannan;Tao, Dingwen;Ahrens, James
通讯作者：
Ahrens, James
PFault：分析高性能并行文件系统可靠性的通用框架
DOI：
10.1145/3205289.3205302
发表时间：
2018
期刊：
Proceedings of the 2018 International Conference on Supercomputing (ICS
影响因子：
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作者：
Cao, Jinrui;Gatla, Om Rameshwar;Zheng, Mai;Dai, Dong;Eswarappa, Vidya;Mu, Yan;Chen, Yong
通讯作者：
Chen, Yong
了解用于超大规模宇宙学模拟的基于 GPU 的有损压缩
DOI：
10.1109/ipdps47924.2020.00021
发表时间：
2020
期刊：
The 34th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2020
影响因子：
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作者：
Jin, Sian;Grosset, Pascal;Biwer, Christopher;Pulido, Jesus;Tian, Jiannan;Tao, Dingwen;Ahrens, James
通讯作者：
Ahrens, James