Performance of Message-Passing MATLAB Toolboxes

  • Javier Fernández
  • Antonio Cañas
  • Antonio F. Díaz
  • Jesús González
  • Julio Ortega
  • Alberto Prieto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2565)


In this work we compare some of the freely available parallel Toolboxes for MATLAB, which differ in purpose and implementation details: while DP-Toolbox and MultiMATLAB offer a higher-level parallel environment, the goals of PVMTB and MPITB, developed by us [7], are to closely adhere to the PVM system and MPI standard, respectively. DP-Toolbox is also based on PVM, and MultiMATLAB on MPI. These Toolboxes allow the user to build a parallel application under the rapid-prototyping MATLAB environment. The differences between them are illustrated by means of a performance test and a simple case study frequently found in the literature. Thus, depending on the preferred message-passing software and the performance requirements of the application, the user can either choose a higher-level Toolbox and benefit from easier coding, or directly interface the message-passing routines and benefit from greater control and performance. Topics: Problem Solving Environments, Parallel and Distributed Computing, Cluster and Grid Computing.


Parallel Application Master Process Parallel Virtual Machine Library Call Slave Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    J. Arndt, C. Haenel: “π-Unleashed”, Springer-Verlag, 2001, ISBN: 3540665722, 237
  2. [2]
    C. Chang, G. Czajkowski, X. Liu, V. Menon, C. Myers, A.E. Trefethen, L. N. Trefethen: “The Cornell MultiMatlab Project”, Proceedings of the POOMA’96 Conference, Sanfa Fe, New-Mexico, 230
  3. [3]
    R. Choi: Parallel Matlab survey, 228
  4. [4]
    Cornell Theory Center: “New Parallel Programming Tools for Matlab”, 230
  5. [5]
    H. Dietz: “Parallel Processing HOWTO”, January 1998, Linux Documentation Project, 236, 237
  6. [6]
    S. Dormido-Canto, A.P. Madrid, S. Dormido: “Programming on Clusters for Solving Control Problems”, Proceedings of the 4th Asian Control Conference ASCC2002, Suntec Singapore, Singapore, September 2002, Session WA9-11 PaperID 1343 in 236 Summary.pdf
  7. [7]
    J. Fernández-Baldomero: “Message Passing under Matlab”, Proceedings of the HPC 2001 (Adrian Tentner, Ed.), pp.73–82. ASTC 2001, Seattle, Washington, 228, 230, 231, 236, 238
  8. [8]
    J. Fernández-Baldomero: MPITB home page, 230
  9. [9]
    J. Fernández-Baldomero: PVMTB home page, 230
  10. [10]
    V. GarcÍa-Osorio, B. E. Ydstie: LDParallel, Distributed Modeling of Simulation of Chemical Systems”, American Institute of Chemical Engineers, Annual Meeting, Reno NV, November 2001. 237
  11. [11]
    A. Geist, A. Beguelin, J. Dongarra, W. Jiang, R. Mancheck, V. Sunderam: “PVM: Parallel Virtual Machine. A Users’ Guide and Tutorial for Networked Parallel Computing”, The MIT Press, Cambridge, Massachusetts, 1994, 229zbMATHGoogle Scholar
  12. [12]
    S. Goasguen, A. Butt, K. D. Colby, M. S. Lundstrom: “Parallelization of the Nanoscale Device Simulator nanoMOS 2.0 using a 100 Nodes Linux Cluster”, Proceedings of the 2nd IEEE Conference on Nanotechnology IEEE-NANO’02, Arlington VA, USA, August 2002, Session WA7#0840 in 237
  13. [13]
    W. Gropp, E. Lusk: “Reproducible Measurements of MPI Performance Characteristics”, Proceedings of the EuroPVM/MPI’99 Conference, Barcelona, Spain, September 1999, 234, 236
  14. [14]
    W. Gropp, E. Lusk, A. Skjelum: “Using MPI: Portable Parallel Programming with the Message-Passing Interface”, The MIT Press, 1994, 229
  15. [15]
    LAM Home Page, 229
  16. [16]
    The MathWorks, Inc.: “Matlab based books” web page, 228
  17. [17]
  18. [18]
    V. S. Menon, A.E. Trefethen: “MultiMATLAB: Integrating MATLAB with High-Performance Parallel Computing”, Proceedings of Supercomputing’97, ACM SIG ARCH and IEEE Computer Society, 1997, 228, 230, 231
  19. [19]
    C. Moler: “Why there isn’t a parallel Matlab”, Matlab news & notes, Cleve’s Corner Spring 1995, 229
  20. [20]
    C. Moler: “Matlab incorporates LAPACK”, Matlab news & notes, Cleve’s Corner Winter 2000, 229
  21. [21]
    S. Pawletta, W. Drewelow, P. Duenow, T. Pawletta, M. Suesse: “A Matlab Toolbox for Distributed and Parallel Processing”, Proceedings of the Matlab’95 Conference (C. Moler, S. Little, Eds.), MathWorks Inc., Cambridge, MA, October 1995, 229
  22. [22]
    M. J. Quinn: “Parallel Computing Theory and Practice, 2nd Edition”, McGraw Hill, New York, 1994. 236Google Scholar
  23. [23]
    A.E. Trefethen, V. S. Menon, C.C. Chang, G. J. Czajkowski, C. Myers, L.N. Trefethen: “MultiMatlab: Matlab on Multiple Processors”, Tech. Report 96-239, Cornell Theory Center, 1996, 230

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Javier Fernández
    • 1
  • Antonio Cañas
    • 1
  • Antonio F. Díaz
    • 1
  • Jesús González
    • 1
  • Julio Ortega
    • 1
  • Alberto Prieto
    • 1
  1. 1.Dept. of Computer Technology and ArchitectureETSII, University of GranadaGranadaSpain

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