A checkpointing strategy for scalable recovery on distributed parallel systems

Abstract

In this paper, we describe a new scheme for checkpointing parallel applications on message-passing scalable distributed memory systems. The novelty of our scheme is that a checkpointed application can be restored, from its checkpointed state, in a reconfigured form. Thus, a parallel application may be checkpointed while executing with t1 tasks on p1 processors, and then restarted from the checkpointed state with t2 tasks on p2 processors. As a result, applications can recover from partial failures in the underlying system. Also, the reconfigurable checkpointed states can be migrated from one parallel system to another even if they do not have the same number of processors. We describe a new programming model for implementing a reconfigurable checkpointing scheme for parallel programs. This new model is derived from the DRMS programming model, developed in the context of run-time reconfiguration of parallel applications. A key component of our implementation is the distribution-independent representation of application array data structures in persistent storage. For further optimizing the performance of checkpoint/restart operations, we provide parallel array section streaming operations for such distributed arrays. We present performance data for the reconfigurable checkpointing and restarting of parallel applications and compare that with the performance of conventional forms of checkpointing. Our results demonstrate the advantages of the new scheme we describe. © 1997 ACM.