Abstract

Temporal fringe pattern analysis is invaluable in transient phenomena studies but necessitates long processing times. Here we describe a parallel computing strategy based on the single-program multiple-data model and hyperthreading processor technology to reduce the execution time. In a two-node cluster workstation configuration we found that execution periods were reduced by 1.6 times when four virtual processors were used. To allow even lower execution times with an increasing number of processors, the time allocated for data transfer, data read, and waiting should be minimized. Parallel computing is found here to present a feasible approach to reduce execution times in temporal fringe pattern analysis.

© 2005 Optical Society of America

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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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  25. www.mathworks.com .
  26. www.scilab.org .

2005 (1)

2004 (1)

G. Argentini, “Cluster computing performances using virtual processors and MATLAB 6.5,” Comput. Res. Reposit. cs.DC/0401006 (2004).

2003 (3)

D. Ambrosi, D. Paoletti, G. Schirripa Spagnalo, “Study of free-convective onset on a horizontal wire using speckle pattern interferometry,” Int. J. Heat Mass Transfer 46, 4145–4155 (2003).
[CrossRef]

G. Argentini, “Using virtual processors for SPMD programs,” Comput. Res. Reposit, cs.DC/0312049 (2003).

V. D. Madjarova, H. Kadono, S. Toyooka, “Dynamic electronic speckle pattern interferometry (DESPI) phase analysis with temporal Hilbert transform,” Opt. Express 11, 617–623 (2003).
[CrossRef] [PubMed]

2002 (4)

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Sinusoidal least-squares fitting for temporal fringe pattern analysis,” J. Mod. Opt. 49, 2257–2266 (2002).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Synchronous detection techniques for temporal fringe pattern analysis,” Opt. Commun. 204, 75–81 (2002).
[CrossRef]

W. Magro, P. Petersen, S. Shah, “Hyper-threading technology: impact on computer-intensive workloads,” Intel Technol. J. 6, 58–66 (2002).

2000 (2)

1998 (1)

K. M. Hung, T. Yamada, “Phase unwrapping by regions using the least-squares approach,” Opt. Eng. 37, 2965–2970 (1998).
[CrossRef]

1996 (1)

1995 (2)

J. L. Marroquin, M. Rivera, “Quadratic regularization functionals for phase unwrapping,” J. Opt. Soc. Am. A 12, 2393–2400 (1995).
[CrossRef]

T. W. Ng, “Carrier-modulated object step-loading method of automated analysis in digital speckle shearing interferometry,” J. Mod. Opt. 42, 2109–2118 (1995).
[CrossRef]

1994 (1)

T. W. Ng, F. S. Chau, “Automated analysis in digital speckle shearing interferometry using an objet step-loading method,” Opt. Commun. 108, 214–218 (1994).
[CrossRef]

1993 (1)

1987 (1)

1986 (1)

1985 (1)

1983 (1)

1982 (1)

Ambrosi, D.

D. Ambrosi, D. Paoletti, G. Schirripa Spagnalo, “Study of free-convective onset on a horizontal wire using speckle pattern interferometry,” Int. J. Heat Mass Transfer 46, 4145–4155 (2003).
[CrossRef]

Ang, K. T.

T. W. Ng, K. T. Ang, “Data compression for speckle correlation interferometry temporal fringe pattern analysis,” Appl. Opt. 44, 2799–2804 (2005).
[CrossRef] [PubMed]

T. W. Ng, K. T. Ang, “Fourier transform method of data compression and temporal fringe pattern analysis,” Appl. Opt. (to be published).

Argentini, G.

G. Argentini, “Cluster computing performances using virtual processors and MATLAB 6.5,” Comput. Res. Reposit. cs.DC/0401006 (2004).

G. Argentini, “Using virtual processors for SPMD programs,” Comput. Res. Reposit, cs.DC/0312049 (2003).

Astrakharchik-Farrimond, E.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Barton, J. S.

Buckberry, C.

Carlsson, T. E.

Chau, F. S.

T. W. Ng, F. S. Chau, “Automated analysis in digital speckle shearing interferometry using an objet step-loading method,” Opt. Commun. 108, 214–218 (1994).
[CrossRef]

Creath, K.

Galizzi, G. E.

Ghiglia, D. C.

Gomez-Pedrero, J. A.

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Sinusoidal least-squares fitting for temporal fringe pattern analysis,” J. Mod. Opt. 49, 2257–2266 (2002).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Synchronous detection techniques for temporal fringe pattern analysis,” Opt. Commun. 204, 75–81 (2002).
[CrossRef]

Grama, A.

A. Grama, G. Karypis, V. Kumar, A. Gupta, An Introduction to Parallel Computing: Design and Analysis of Algorithms, 2nd ed. (Addison Wesley, 2003).

Gupta, A.

A. Grama, G. Karypis, V. Kumar, A. Gupta, An Introduction to Parallel Computing: Design and Analysis of Algorithms, 2nd ed. (Addison Wesley, 2003).

Hung, K. M.

K. M. Hung, T. Yamada, “Phase unwrapping by regions using the least-squares approach,” Opt. Eng. 37, 2965–2970 (1998).
[CrossRef]

Huntley, J. M.

Ina, H.

Jones, J. D. C.

Kadono, H.

Karypis, G.

A. Grama, G. Karypis, V. Kumar, A. Gupta, An Introduction to Parallel Computing: Design and Analysis of Algorithms, 2nd ed. (Addison Wesley, 2003).

Kaufmann, G. H.

Kerr, D.

Kilpatrick, J. M.

Kobayashi, S.

Kumar, V.

A. Grama, G. Karypis, V. Kumar, A. Gupta, An Introduction to Parallel Computing: Design and Analysis of Algorithms, 2nd ed. (Addison Wesley, 2003).

Madjarova, V. D.

Magro, W.

W. Magro, P. Petersen, S. Shah, “Hyper-threading technology: impact on computer-intensive workloads,” Intel Technol. J. 6, 58–66 (2002).

Marroquin, J. L.

Mastin, G. A.

Moore, A. J.

Morgan, S. P.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Ng, T. W.

T. W. Ng, K. T. Ang, “Data compression for speckle correlation interferometry temporal fringe pattern analysis,” Appl. Opt. 44, 2799–2804 (2005).
[CrossRef] [PubMed]

T. W. Ng, “Carrier-modulated object step-loading method of automated analysis in digital speckle shearing interferometry,” J. Mod. Opt. 42, 2109–2118 (1995).
[CrossRef]

T. W. Ng, F. S. Chau, “Automated analysis in digital speckle shearing interferometry using an objet step-loading method,” Opt. Commun. 108, 214–218 (1994).
[CrossRef]

T. W. Ng, K. T. Ang, “Fourier transform method of data compression and temporal fringe pattern analysis,” Appl. Opt. (to be published).

Paoletti, D.

D. Ambrosi, D. Paoletti, G. Schirripa Spagnalo, “Study of free-convective onset on a horizontal wire using speckle pattern interferometry,” Int. J. Heat Mass Transfer 46, 4145–4155 (2003).
[CrossRef]

Petersen, P.

W. Magro, P. Petersen, S. Shah, “Hyper-threading technology: impact on computer-intensive workloads,” Intel Technol. J. 6, 58–66 (2002).

Quiroga, J. A.

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Synchronous detection techniques for temporal fringe pattern analysis,” Opt. Commun. 204, 75–81 (2002).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Sinusoidal least-squares fitting for temporal fringe pattern analysis,” J. Mod. Opt. 49, 2257–2266 (2002).
[CrossRef]

Reeves, M.

Rivera, M.

Robinson, D. W.

Romero, L. A.

Saldner, H.

Sawyer, N. B. E.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Schirripa Spagnalo, G.

D. Ambrosi, D. Paoletti, G. Schirripa Spagnalo, “Study of free-convective onset on a horizontal wire using speckle pattern interferometry,” Int. J. Heat Mass Transfer 46, 4145–4155 (2003).
[CrossRef]

See, C. W.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Shah, S.

W. Magro, P. Petersen, S. Shah, “Hyper-threading technology: impact on computer-intensive workloads,” Intel Technol. J. 6, 58–66 (2002).

Shekunov, B. Y.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Slettemoen, G. A.

Somekh, M. G.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Takeda, M.

Toyooka, S.

Villa, J.

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Synchronous detection techniques for temporal fringe pattern analysis,” Opt. Commun. 204, 75–81 (2002).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Sinusoidal least-squares fitting for temporal fringe pattern analysis,” J. Mod. Opt. 49, 2257–2266 (2002).
[CrossRef]

Wei, A.

Wyant, J. C.

Yamada, T.

K. M. Hung, T. Yamada, “Phase unwrapping by regions using the least-squares approach,” Opt. Eng. 37, 2965–2970 (1998).
[CrossRef]

York, P.

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Appl. Opt. (6)

Comput. Res. Reposit, cs.DC/0312049 (1)

G. Argentini, “Using virtual processors for SPMD programs,” Comput. Res. Reposit, cs.DC/0312049 (2003).

Comput. Res. Reposit. cs.DC/0401006 (1)

G. Argentini, “Cluster computing performances using virtual processors and MATLAB 6.5,” Comput. Res. Reposit. cs.DC/0401006 (2004).

Exp. Fluids (1)

E. Astrakharchik-Farrimond, B. Y. Shekunov, P. York, N. B. E. Sawyer, S. P. Morgan, M. G. Somekh, C. W. See “Dynamic measurements in supercritical flow using instantaneous phase-shift interferometry,” Exp. Fluids 33, 307–314 (2002).
[CrossRef]

Int. J. Heat Mass Transfer (1)

D. Ambrosi, D. Paoletti, G. Schirripa Spagnalo, “Study of free-convective onset on a horizontal wire using speckle pattern interferometry,” Int. J. Heat Mass Transfer 46, 4145–4155 (2003).
[CrossRef]

Intel Technol. J. (1)

W. Magro, P. Petersen, S. Shah, “Hyper-threading technology: impact on computer-intensive workloads,” Intel Technol. J. 6, 58–66 (2002).

J. Mod. Opt. (2)

T. W. Ng, “Carrier-modulated object step-loading method of automated analysis in digital speckle shearing interferometry,” J. Mod. Opt. 42, 2109–2118 (1995).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Sinusoidal least-squares fitting for temporal fringe pattern analysis,” J. Mod. Opt. 49, 2257–2266 (2002).
[CrossRef]

J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (3)

Opt. Commun. (2)

T. W. Ng, F. S. Chau, “Automated analysis in digital speckle shearing interferometry using an objet step-loading method,” Opt. Commun. 108, 214–218 (1994).
[CrossRef]

J. Villa, J. A. Gomez-Pedrero, J. A. Quiroga, “Synchronous detection techniques for temporal fringe pattern analysis,” Opt. Commun. 204, 75–81 (2002).
[CrossRef]

Opt. Eng. (1)

K. M. Hung, T. Yamada, “Phase unwrapping by regions using the least-squares approach,” Opt. Eng. 37, 2965–2970 (1998).
[CrossRef]

Opt. Express (1)

Opt. Lett. (1)

Other (4)

T. W. Ng, K. T. Ang, “Fourier transform method of data compression and temporal fringe pattern analysis,” Appl. Opt. (to be published).

A. Grama, G. Karypis, V. Kumar, A. Gupta, An Introduction to Parallel Computing: Design and Analysis of Algorithms, 2nd ed. (Addison Wesley, 2003).

www.mathworks.com .

www.scilab.org .

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Figures (4)

Fig. 1
Fig. 1

Digital speckle interferometry image and the intensity distribution from a single line of data plotted under temporal loading evolution.

Fig. 2
Fig. 2

Speckle interferometry intensity fringe patterns with carrier modulation generated for (a) a single frame and (b) two subtracted frames, one with deformation.

Fig. 3
Fig. 3

Plots of the measured execution times when a different number of processors are used.

Fig. 4
Fig. 4

Speedup factors calculated with Amdahl’s law with solid plots, different values of P as well as speedup factors determined from, scatter plot with triangles, total execution times and, scatter plot with squares, processing execution times for the different number of processors.

Equations (3)

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i ( x , y , k ) = i B ( x , y ) + i M ( x , y ) cos [ ϕ ( x , y ) + Δ ( x , y , k ) ] ,
S ( N ) = t ( 1 ) t ( N ) ,
S ( N ) = 1 ( P / N ) + ( 1 P ) ,

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