Anticipating the behavior of applications, studying, and designing algorithms are some of the most important purposes for the performance and correction studies about simulations and applications relating to intensive computing. Often studies that evaluate performance on a single-node of a simulation don’t consider Non-Uniform Memory Access (NUMA) as having a critical effect. This work focuses on accurately predicting the performance of task-based OpenMP applications from traces collected through the OMPT interface. We first introduce TiKKi, a tool that records a rich high-level representation of the execution trace of a real OpenMP application. With this trace, an accurate prediction of the execution time is modeled from the architecture of the machine and sOMP, a SimGrid-based simulator for task-based applications with data dependencies. These predictions are improved when the model takes into account memory transfers. We show that good precision (10% relative error on average) can be obtained for various grains and on different numbers of cores inside different shared-memory architectures.