Abstract
Various mechanisms for fault-tolerance (FT) are used today in order to reduce the impact of failures on application execution. In the case of system failure, standard FT mechanisms are checkpoint/restart (for reactive FT) and migration (for pro-active FT). However, each of these mechanisms create an overhead on application execution, overhead that for instance becomes critical on large-scale systems where previous studies have shown that applications may spend more time checkpointing state than performing useful work.
In order to decrease this overhead, researchers try to both optimize existing FT mechanisms and implement new FT policies. For instance, combining reactive and pro-active approaches in order to decrease the number of checkpoints that must be performed during the application�'s execution. However, currently no solutions exist which enable the evaluation of these FT approaches through simulation, instead experimentations must be done using real platforms. This increases complexity and limits experimentation into alternate solutions.
This paper presents a simulation framework that evaluates different FT mechanisms and policies. The framework uses system failure logs for the simulation with a default behavior based on logs taken from the ASCI White at Lawrence Livermore National Laboratory. We evaluate the accuracy of our simulator comparing simulated results with those taken from experiments done on a 32-node compute cluster. Therefore such a simulator can be used to develop new FT policies and/or to tune existing policies.
