@article {933,
	title = {Assessing General-purpose Algorithms to Cope with Fail-stop and Silent Errors},
	journal = {ACM Transactions on Parallel Computing},
	year = {2016},
	month = {2016-08},
	abstract = {In this paper, we combine the traditional checkpointing and rollback recovery strategies with verification mechanisms to cope with both fail-stop and silent errors. The objective is to minimize makespan and/or energy consumption. For divisible load applications, we use first-order approximations to find the optimal checkpointing period to minimize execution time, with an additional verification mechanism to detect silent
errors before each checkpoint, hence extending the classical formula by Young and Daly for fail-stop errors only. We further extend the approach to include intermediate verifications, and to consider a bi-criteria problem involving both time and energy (linear combination of execution time and energy consumption). Then, we focus on application workflows whose dependence graph is a linear chain of tasks. Here, we determine the optimal checkpointing and verification locations, with or without intermediate verifications, for the bicriteria problem. Rather than using a single speed during the whole execution, we further introduce a new execution scenario, which allows for changing the execution speed via dynamic voltage and frequency scaling (DVFS). We determine in this scenario the optimal checkpointing and verification locations, as well as the optimal speed pairs. Finally, we conduct an extensive set of simulations to support the theoretical study, and to assess the performance of each algorithm, showing that the best overall performance is achieved under the most flexible scenario using intermediate verifications and different speeds.},
	keywords = {checkpoint, fail-stop error, failure, HPC, resilience, silent data corruption, silent error, verification},
	doi = {10.1145/2897189},
	author = {Anne Benoit and Aurelien Cavelan and Yves Robert and Hongyang Sun}
}
@conference {930,
	title = {Optimal Resilience Patterns to Cope with Fail-stop and Silent Errors},
	booktitle = {2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
	year = {2016},
	month = {2016-05},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Chicago, IL},
	abstract = {This work focuses on resilience techniques at extreme scale. Many papers deal with fail-stop errors. Many others deal with silent errors (or silent data corruptions). But very few papers deal with fail-stop and silent errors simultaneously. However, HPC applications will obviously have to cope with both error sources. This paper presents a unified framework and optimal algorithmic solutions to this double challenge. Silent errors are handled via verification mechanisms (either partially or fully accurate) and in-memory checkpoints. Fail-stop errors are processed via disk checkpoints. All verification and checkpoint types are combined into computational patterns. We provide a unified model, and a full characterization of the optimal pattern. Our results nicely extend several published solutions and demonstrate how to make use of different techniques to solve the double threat of fail-stop and silent errors. Extensive simulations based on real data confirm the accuracy of the model, and show that patterns that combine all resilience mechanisms are required to provide acceptable overheads.},
	keywords = {fail-stop errors, multilevel checkpoint, optimal pattern, resilience, silent errors, verification},
	doi = {10.1109/IPDPS.2016.39},
	author = {Anne Benoit and Aurelien Cavelan and Yves Robert and Hongyang Sun}
}
@article {931,
	title = {Efficient Checkpoint/Verification Patterns},
	journal = {International Journal on High Performance Computing Applications},
	year = {2015},
	month = {2015-07},
	abstract = {Errors have become a critical problem for high performance computing. Checkpointing protocols are often used for error recovery after fail-stop failures. However, silent errors cannot be ignored, and their peculiarity is that such errors are identified only when the corrupted data is activated. To cope with silent errors, we need a verification mechanism to check whether the application state is correct. Checkpoints should be supplemented with verifications to detect silent errors. When a verification is successful, only the last checkpoint needs to be kept in memory because it is known to be correct. In this paper, we analytically determine the best balance of verifications and checkpoints so as to optimize platform throughput. We introduce a balanced algorithm using a pattern with p checkpoints and q verifications, which regularly interleaves both checkpoints and verifications across same-size computational chunks. We show how to compute the waste of an arbitrary pattern, and we prove that the balanced algorithm is optimal when the platform MTBF (Mean Time Between Failures) is large in front of the other parameters (checkpointing, verification and recovery costs). We conduct several simulations to show the gain achieved by this balanced algorithm for well-chosen values of p and q, compared to the base algorithm that always perform a verification just before taking a checkpoint (p = q = 1), and we exhibit gains of up to 19\%.},
	keywords = {checkpointing, Fault tolerance, High Performance Computing, silent data corruption, silent error, verification},
	doi = {10.1177/1094342015594531},
	author = {Anne Benoit and Saurabh K. Raina and Yves Robert}
}
@techreport {684,
	title = {On the Combination of Silent Error Detection and Checkpointing},
	journal = {UT-CS-13-710},
	year = {2013},
	month = {2013-06},
	publisher = {University of Tennessee Computer Science Technical Report},
	abstract = {In this paper, we revisit traditional checkpointing and rollback recovery strategies, with a focus on silent data corruption errors. Contrarily to fail-stop failures, such latent errors cannot be detected immediately, and a mechanism to detect them must be provided. We consider two models: (i) errors are detected after some delays following a probability distribution (typically, an Exponential distribution); (ii) errors are detected through some verification mechanism. In both cases, we compute the optimal period in order to minimize the waste, i.e., the fraction of time where nodes do not perform useful computations. In practice, only a fixed number of checkpoints can be kept in memory, and the first model may lead to an irrecoverable failure. In this case, we compute the minimum period required for an acceptable risk. For the second model, there is no risk of irrecoverable failure, owing to the verification mechanism, but the corresponding overhead is included in the waste. Finally, both models are instantiated using realistic scenarios and application/architecture parameters.},
	keywords = {checkpointing, error recovery, High-performance computing, silent data corruption, verification},
	url = {http://www.netlib.org/lapack/lawnspdf/lawn278.pdf},
	author = {Guillaume Aupy and Anne Benoit and Thomas Herault and Yves Robert and Frederic Vivien and Dounia Zaidouni}
}
