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Parallel implementation of multi-dimensional ensemble empirical mode decomposition (2011)
| Content Provider | CiteSeerX |
|---|---|
| Author | Chang, Li-Wen Lo, Men-Tzung Anssari, Nasser Hsu, Ke-Hsin Huang, Norden E. Hwu, Wen-Mei W. |
| Description | 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. International Conference on Acoustics, Speech, and Signal Processing |
| File Format | |
| Language | English |
| Publisher Date | 2011-01-01 |
| Access Restriction | Open |
| Subject Keyword | Cuda Programming Model Octal-core Intel Xeon X7550 Cpu Parallel Implementation Nvidia Tesla C2050 Multi-core Cpu Implementation Sequential Implementation Multi-dimensional Ensemble Empirical Mode Decomposition Double Precision Gpu Implementation Openmp Programming Model |
| Content Type | Text |
| Resource Type | Article |