Reliability-Aware Speedup Models for Parallel Applications with Coordinated Checkpointing/Restart

Speedup models are powerful analytical tools for evaluating and predicting the performance of parallel applications. Unfortunately, the well-known speedup models like Amdahl´s law and Gustafson´s law do not take reliability into consideration and therefore cannot accurately account for application performance in the presence of failures. In this study, we enhance Amdahl´s law and Gustafson´s law by considering the impact of failures and the effect of coordinated checkpointing/restart. Unlike existing analytical studies relying on Exponential failure distribution alone, in this work we consider both Exponential and Weibull failure distributions in the construction of our reliability-aware speedup models. The derived reliability-aware models are validated through trace-based simulations under a variety of parameter settings. Our trace-based simulations demonstrate these models can effectively quantify failure impact on application speedup. Moreover, we present two case studies to illustrate the use of these reliability-aware speedup models.