Fixed-work versus fixed-time checkpointing on large-scale failure-prone platforms

Consider a High-Performance Computing (HPC) application executing on a large-scale failure-prone platform. The Fixed-Work Checkpointing ( FWC ) problem consists in minimizing the expected time to execute a fixed amount of work (namely a fraction or the totality of the application). Strategies for the FWC problem have received considerable attention and are well-understood. On the contrary, the dual problem, namely the Fixed-Time Checkpointing ( FTC ) problem, has been considered only very recently. The FTC problem consists in maximizing the expected work achieved during a fixed amount of time (namely the duration of a reservation granted to the application). This work provides a comparative overview of both problems. First we review existing strategies for the FWC problem and extend them to stochastic checkpoints, i.e., when the checkpoint is no longer a deterministic constant but obeys some probability distribution law instead. Then we provide a comprehensive study of the FTC problem. The problem turns out to be surprisingly difficult, even when restricting to taking one or two checkpoints. We provide a threshold-based heuristic to solve the general instance of the problem with an arbitrary number of checkpoints, and we have to resort to time discretization to provide an optimal strategy. We further extend this latter strategy to stochastic checkpoints.