In this paper, we show parallel implementation of Hilbert-Huang Transform on GPU. This implementation focused on the reducing the computation complexity from O(N) on a single CPU to O(N/P log (N)) on GPU, as well as the use of 'shared-global' switching method to increase performance. Evaluation results show our single GPU implementation using Tesla C1060 achieves 29.0x speedup in best case, and a total of 7.1x speedup for all results when compared to a single Intel dual core CPU.