On the Use of Cluster-Based Partial Message Logging to Improve Fault Tolerance for MPI HPC Applications

Thomas Ropars, Amina Guermouche, Bora Uçar, Esteban Meneses, Laxmikant V. Kalé, and Franck Cappello

Abstract. Fault tolerance is becoming a major concern in HPC systems. The two traditional approaches for message passing applications, coordinated checkpointing and message logging, have severe scalability issues. Coordinated checkpointing protocols make all processes roll back after a failure. Message logging protocols log a huge amount of data and can induce an overhead on communication performance. Hierarchical rollback-recovery protocols based on the combination of coordinated checkpointing and message logging are an alternative. These partial message logging protocols are based on process clustering: only messages between clusters are logged to limit the consequence of a failure to one cluster. These protocols would work efficiently only if one can find clusters of processes in the applications such that the ratio of logged messages is very low. We study the communication patterns of message passing HPC applications to show that partial message logging is suitable in most cases. We propose a partitioning algorithm to find suitable clusters of processes given the communication pattern of an application. Finally, we evaluate the efficiency of partial message logging using two state of the art protocols on a set of representative applications.

Key words. High performance computing, checkpointing, rollback, fault tolerance, graph partitioning