Program performance optimisations, feedback-directed iterative compilation and auto-tuning systems all assume a fixed estimation of execution time given a fixed input data for the program. However, in practice we observe non-negligible program performance variations on hardware platforms. While these variations are insignificant for sequential applications, we show that parallel native OpenMP programs have less performance stability. This article does not try to quantify nor to qualify the factors influencing the variations of program execution times, that we let for a future work. This article demonstrates three observations: 1) The performance variations of sequential applications is insignificant. 2) OpenMP program execution times on multi-core platforms show important variations. 3) The distribution of the execution times is not a Gaussian distribution in almost all cases. We finish by a discussion explaining why considering the minimal or the mean execution time within a sample of experiments is not the best estimation of program performance.