Understanding three-dimensional seismic wave propagation in complex media remains one of the main challenges of quantitative seismology. Because of its simplicity and numerical efficiency, the finite-differences method is one of the standard techniques implemented to consider the elastodynamics equation. Additionally, this class of modelling heavily relies on parallel architectures in order to tackle large scale geometries including a detailed description of the physics. Last decade, significant efforts have been devoted towards efficient implementation of the finite-differences methods on emerging architectures. These contributions have demonstrated their efficiency leading to robust industrial applications. The growing representation of heterogeneous architectures combining general purpose multicore platforms and accelerators leads to redesign current parallel application. In this paper, we consider StarPU task-based runtime system in order to harness the power of heterogeneous CPU+GPU computing nodes. We detail our implementation and compare the performance obtained with the classical CPU or GPU only versions. Preliminary results demonstrate significant speedups in comparison with the best implementation suitable for homogeneous cores.