Performance and Accuracy Trade-offs of HPC Application Modeling and Simulation

High Performance Computing (HPC) applications and systems are often studied through modeling and simulation at various granularities. As the size of HPC systems and applications and the cost of high fidelity simulation continue to grow, a good understanding of the trade-offs of the complexity and accuracy of HPC application modeling and simulation schemes can help balance the competing goals of accuracy and time. In this work, we investigate the complexity and accuracy trade-off using an MPI application modeling tool and an MPI application simulation tool. The performance and accuracy results of modeling and simulation of a large spectrum of HPC applications on three supercomputers are measured and compared. The results show that although modeling is often one to two orders of magnitude faster than simulation, it achieves within 5 % of predicted application time in comparison to simulation for 85% of cases in our data set. We further enhance the modeling tool with a statistical model to predict whether simulation can yield significantly different results than modeling. The enhanced tool achieves a very high successful prediction rate of 93.2% on our dataset and is thus effective in determining whether modeling or simulation should be used.