PARALLEL IMPLEMENTATION OF MULTI-DIMENSIONAL ENSEMBLE EMPIRICAL MODE DECOMPOSITION
Parallel Software Implementation of DSP Algorithms
Presented by: Li-Wen Chang, Author(s): Li-Wen Chang, University of Illinois Urbana-Champaign, United States; Men-Tzung Lo, National Central University, Taiwan; Nasser Anssari, University of Illinois Urbana-Champaign, United States; Ke-Hsin Hsu, Norden Huang, National Central University, Taiwan; Wen-mei Hwu, University of Illinois Urbana-Champaign, United States
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.