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ACR: Automatic Checkpoint/Restart for Soft and Hard Error Protection
| Citations: | 7 - 0 self |
BibTeX
@MISC{Ni_acr:automatic,
author = {Xiang Ni and Esteban Meneses and Nikhil Jain and Laxmikant V. Kalé},
title = {ACR: Automatic Checkpoint/Restart for Soft and Hard Error Protection},
year = {}
}
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Abstract
As machines increase in scale, many researchers have predicted that failure rates will correspondingly increase. Soft errors do not inhibit execution, but may silently generate incorrect results. Recent trends have shown that soft error rates are increasing, and hence they must be detected and handled to maintain correctness. We present a holistic methodology for automatically detecting and recovering from soft or hard faults with minimal application intervention. This is demonstrated by ACR: an automatic checkpoint/restart framework that performs application replication and automatically adapts the checkpoint period using online information about the current failure rate. ACR performs an application- and user-oblivious recovery. We empirically test ACR by injecting failures that follow different distributions for five applications and show low overhead when scaled to 131,072 cores. We also analyze the interaction between soft and hard errors and propose three recovery schemes that explore the trade-off between performance and reliability requirements.
Keyphrases
automatic checkpoint restart hard error protection soft error rate checkpoint period different distribution holistic methodology application replication incorrect result recovery scheme current failure rate soft error recent trend low overhead failure rate hard fault minimal application intervention automatic checkpoint restart framework hard error user-oblivious recovery online information machine increase reliability requirement many researcher
