Evaluating cooperative checkpointing for supercomputing systems

Cooperative checkpointing, in which the system dynamically skips checkpoints requested by applications at runtime, can exploit system-level information to improve performance and reliability in the face of failures. We evaluate the applicability of cooperative checkpointing to large-scale systems through simulation studies considering real workloads, failure logs, and different network topologies. We consider two cooperative checkpointing algorithms: work-based cooperative checkpointing uses a heuristic based on the amount of unsaved work and risk-based cooperative checkpointing leverages failure event prediction. Our results demonstrate that, compared to periodic checkpointing, risk-based checkpointing with event prediction accuracy as low as 10% is able to significantly improve system utilization and reduce average bounded slowdown by a factor of 9, without losing any additional work to failures. Similarly, work-based checkpointing conferred tremendous performance benefits in the face of large checkpoint overheads