Parallel implementation of Multi-dimensional Ensemble Empirical Mode Decomposition

Author

Chang, Li-Wen ; Lo, Men-Tzung ; Anssari, Nasser ; Hsu, Ke-Hsin ; Huang, Norden E. ; Hwu, Wen-Mei W.

Author_Institution

Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA

fYear

2011

fDate

22-27 May 2011

Firstpage

1621

Lastpage

1624

Abstract

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.

Keywords

computer graphic equipment; coprocessors; multiprocessing systems; parallel architectures; parallel programming; CUDA programming model; NVIDIA Tesla C2050; OpenMP programming model; double precision GPU implementation; many-core architecture; multicore CPU implementation; multicore architecture; multidimensional ensemble empirical mode decomposition; octal-core Intel Xeon CPU; parallel implementation; sequential C implementation; Graphics processing unit; Instruction sets; Interpolation; Parallel processing; Programming; Spline; CUDA; GPGPU; Multi-dimensional Ensemble Empirical Mode Decomposition; OpenMP;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on

Conference_Location

Prague

ISSN

1520-6149

Print_ISBN

978-1-4577-0538-0

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2011.5946808

Filename

5946808