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Abstract:

The running times of many computational science applications are much longer than the mean-time-to-failure of current high-performance computing platforms. Therefore, to run to completion, these applications must tolerate hardware failures. Checkpoint-and-restart (CPR) is the most commonly used scheme for accomplishing this- the state of computation is saved periodically on stable storage, and when a hardware failure is detected, the computation is restarted from the most recently saved state. Most automatic CPR schemes in the literature can be classified as blocking, system-level checkpointing schemes because they take core-dump style snapshots of the computational state when all the processes are blocked at global barriers in the program. Unfortunately, a system that implements this style of checkpointing is tied to a particular platform; in addition, it cannot be used if there are no global barriers in the program. In our research project, we are exploring an alternative called non-blocking application-level checkpointing. In our approach, programs are transformed by a pre-processor so that they become selfcheckpointing and self-restartable on any platform; there is also no assumption about the existence of global barriers in the code. In this paper, we describe our implementation of non-blocking application-level checkpointing. We present experimental results on both a Windows cluster and the Lemieux system at the Pittsburgh Supercomputer Center, and argue that these results demonstrate both the platform-independence and the scalability of our approach. 1.

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