Tools for Enabling Automatic Validation of Large-Scale Parallel Application Simulations

Validation is highly important in parallel application simulations with a large number of parameters, a process that can vary depending on the structure of the simulator and the granularity of the models used. Common practice involves calculating the percentage error between the projected and the real execution time of a benchmark program. However, this coarse-grained approach often suffers from a parameter insensitivity problem in regions of high-dimensional parameter space. In this work we demonstrate the use of our fine-grained validation toolset to capture and compare the statistical characteristics of a parallel application's execution. It is the first toolset to apply fine-grained statistics to large-scale simulation validation, and our experimental evaluation shows that it offers a significant improvement in fidelity when compared to validation using total execution time.