Scalable Data Resilience for In-memory Data Staging
Scalable Data Resilience for In-memory Data Staging
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DOI：
10.1109/ipdps.2018.00021
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Shaohua Duan;P. Subedi;K. Teranishi;Philip E. Davis;H. Kolla;Marc Gamell;M. Parashar
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文献类型：
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作者：
Shaohua Duan;P. Subedi;K. Teranishi;Philip E. Davis;H. Kolla;Marc Gamell;M. Parashar
当前和计划中的高端HPC系统规模的急剧增加带来了新的挑战，例如数据移动和IO的成本不断增长，以及系统组件的平均故障间隔时间（MTBF）的减少。原位工作流，即在HPC系统上执行整个应用程序工作流，已经成为一种有吸引力的方法，通过将计算移近数据来解决与数据相关的挑战，并且基于阶段的框架已经有效地用于大规模支持原位工作流。然而，这些基于阶段的解决方案的弹性还没有得到解决，它们仍然容易受到代价高昂的数据故障的影响。此外，天真地使用数据弹性技术（如n-way复制和擦除代码）可能会影响延迟和/或导致显著的存储开销。在本文中，我们提出了CoREC，一个可扩展的弹性内存数据暂存运行时，用于大规模的原位工作流。CoREC使用了一种新颖的混合方法，结合了基于数据访问模式的动态复制和擦除编码。本文还介绍了负载平衡和避免冲突编码的优化，以及低开销、延迟数据恢复方案。我们已经实现了CoREC运行时，并在ORNL的Titan上部署了DataSpaces登台服务，并在论文中给出了一个实验评估。实验表明，CoREC可以容忍内存中的数据故障，同时保持低延迟和在大规模下保持高的整体存储效率。
The dramatic increase in the scale of current and planned high-end HPC systems is leading new challenges, such as the growing costs of data movement and IO, and the reduced mean times between failures (MTBF) of system components. In-situ workflows, i.e., executing the entire application workflows on the HPC system, have emerged as an attractive approach to address data-related challenges by moving computations closer to the data, and staging-based frameworks have been effectively used to support in-situ workflows at scale. However, the resilience of these staging-based solutions has not been addressed and they remain susceptible to expensive data failures. Furthermore, naive use of data resilience techniques such as n-way replication and erasure codes can impact latency and/or result in significant storage overheads. In this paper, we present CoREC, a scalable resilient in-memory data staging runtime for large-scale in-situ workflows. CoREC uses a novel hybrid approach that combines dynamic replication with erasure coding based on data access patterns. The paper also presents optimizations for load balancing and conflict avoiding encoding, and a low overhead, lazy data recovery scheme. We have implemented the CoREC runtime and have deployed with the DataSpaces staging service on Titan at ORNL, and present an experimental evaluation in the paper. The experiments demonstrate that CoREC can tolerate in-memory data failures while maintaining low latency and sustaining high overall storage efficiency at large scales.