HyperLink   Parallel Implementation of Multi-Dimensional Ensemble Empirical Mode Decomposition
Publication Year:
  Li-Wen Chang, Men-Tzung Lo, Nasser Anssari, Ke-Hsin Hsu, Norden E. Huang, Wen-mei Hwu
  Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing, May 2011

In this paper, we propose and evaluate two parallel implementations of Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) for multi-core (CPU) and many-core (GPU) architectures. Relative to a sequential C implementation, our double precision GPU implementation, using the CUDA programming model, achieves up to 48.6x speedup on NVIDIA Tesla C2050. Our multi-core CPU implementation, using the OpenMP programming model, achieves up to 11.3x speedup on two octal-core Intel Xeon x7550 CPUs.