Speculative Checkpointing

In large scale parallel systems, storing memory images with checkpointing will involve massive amounts of concentrated I/O from many nodes, resulting in considerable execution overhead. For user-level checkpointing, overhead reduction usually involves both spatial, i.e., reducing the amount of checkpoint data, and temporal, i.e., spreading out I/O by checkpointing data as soon as their values become fixed. However, for system-level checkpointing, while being generic and effortless for the end-user, most efforts have focused on simple methods for spatial reductions only. Instead, we propose speculative checkpointing, which is an attempt to exploit temporal reduction in system-level checkpointing. We demonstrate that speculative checkpointing can be implemented as a simple extension of incremental checkpointing, a well-known checkpointing optimization algorithm for spatial reduction. Although shown to be useful and effective, the overall effectiveness of speculative checkpointing is greatly affected by the last-write heuristics of pages, and as such it is difficult to determine the theoretical upper bound of the effectiveness of speculative checkpointing in practical applications. In order to analyze this, we construct a checkpointing