Parallelizing Hilbert-Huang transform on a GPU

Proceedings - 2010 1st International Conference on Networking and Computing, ICNC 2010

Volumn , Issue , 2010, Pages 184-190

  Waskito, Pulung ^a   Miwa, Shinobu ^a   Mitsukura, Yasue ^a   Nakajo, Hironori ^a  

^a TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

Author keywords

CUDA; Empirical mode decomposition (EMD); GPU; Hilbert Huang transform (HHT)

Indexed keywords

COMPUTATION COMPLEXITY; CUDA; DUAL CORE CPU; EMPIRICAL MODE DECOMPOSITION (EMD); EVALUATION RESULTS; GPU; GPU IMPLEMENTATION; HILBERT HUANG TRANSFORMS; PARALLEL IMPLEMENTATIONS; PARALLELIZING; SINGLE CPU; SWITCHING METHODS;

SIGNAL PROCESSING;

MATHEMATICAL TRANSFORMATIONS;

EID: 79951784325     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IC-NC.2010.44     Document Type: Conference Paper

References (19)

1. N. E. Huang et al, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", In Proc. of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, vol.454, no.1971, p.903-995, March 1998D
2. R. M. Rao and A. S. Bopardikar, "Wavelet Transforms, Introduction to Theory and Applications", Addison Wesley Longman, 1998.
3. Z. Wu and N. E. Huang, "Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method", Advances in Adaptive Data Analysis vol.1, no.1, p.1-41, 2009.
4. N. Rehman and D. P. Mandic "Multivariate empirical mode decomposition", Proc. of the Royal Society A, vol.466, no.2117, p.1291-1302, 2010.
5. NVIDIA, "NVIDIA CUDA: Compute Unified Device Architecture", http://developer.nvidia.com/object/cuda.html.
6. NVIDIA, "NVIDIA CUDA Programming Guide 2.3, 2009", http://developer.download.nvidia.com/compute/cuda/2 3/ toolkit/docs/NVIDIA CUDA Programming Guide 2.3.pdf.
7. N. K. Govindaraju, B. Lloyd, Y. Dotsenko, B. Smith, and J. Manferdelli, "High Performance Discrete Fourier Transforms on Graphics Processors", In Proc. of Supercomputing, p.1-12, November 2008.
8. A. Nukada, Y. Ogata, T. Endo, and S. Matsuoka, "Bandwidth Intensive 3-D FFT Kernel for GPUs Using CUDA", In Proc. of Supercomputing, p.1-6, October 2008.
9. J. Franco, G. Bernabe, J. Fernandez, and M. E. Acacio, "A Parallel Implementation of the 2D Wavelet Transform Using CUDA", Parallel, Distributed, and Network-Based Processing, Euromicro Conference, p.111-118, Los Alamitos, CA, USA, 2009.
10. P. Waskito, S. Miwa, Y. Mitsukura, and H. Nakajo, "Parallelizing Hilbert-Huang Transform and Its Acceleration using GPU", In The Annual Symposium on Advanced Computing Systems and Infrastructures (SACSIS2010) (poster), Vol.2010, No.5, pp.139-140, May 2010 (in Japanese).
11. P. Waskito, S. Miwa, Y. Mitsukura, and H. Nakajo, "Accelerating Hilbert-Huang Transform using GPU" In Summer United Workshops on Parallel, Distributed and Cooperative Processing (SWoPP 2010), 2010.
12. Y. Zhang, J. Cohen, J. D. Owens, "Fast Tridiagonal Solvers on the GPU", Principles and Practice of Parallel Programming, Bangalore, India, January 2010.
13. S. McKinley and M. Levine, "Cubic Spline Interpolation", College of the Redwoods, 1998D
14. Press W. H. et al., "Numerical Recipes in C: The Art of Scientific Computing", Cambridge University Press; 2nd edition, p.113-116, 1992.
15. G. Barnes, "A Method for Implementing Lock-Free Shared- Data Structures", In Proc. of the 5th ACM Symposium on Parallel Algorithms and Architectures, June 1993.
16. S . Xiao and W. C. Feng, "Inter-Block GPU Communication via Fast Barrier Synchronization", In Proc. of International Parallel and Distributed Processing Symposium, Atlanta, USA, April 2010.
17. D. A. Bini and B. Meini, "The cyclic reduction algorithm: from Poisson equation to stochastic processes and beyond", In Journal of Numerical Algorithms vol.31, p.23-60, 2009.
18. J. Verkaik and H. X. Lin, "A class of novel parallel algorithm for the solution of tridiagonal systems", In Journal of Parallel Computing vol.31, no.6, p.563-587, 2005.
19. T. Takahashi et al, "MIST: Media Integration Standard Toolkit", http://mist.suenaga.cse.nagoya-u.ac.jp/