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T++: An object-oriented language to express task and data parallelism on Multi-SIMD computers

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Parallel Computing Technologies (PaCT 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 964))

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Abstract

In this paper we introduce T++: a parallel language with object-oriented features designed for Multi-SIMD parallel computers. We propose a new approach to express simultaneously task and data parallelism. We describe the advantages of an object-oriented approach and what kind of semantics we choose to structure our task-data-parallelism. Finally, we explain how to implement it efficiently on a proprietary Multi-SIMD architecture: the SYMPHONIE concept.

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References

  1. K. M. Chandy and C. Kesselman. The cc++ language definition. Technical Report Caltech-CS-TR-92-02, California Institue of Technology, 1992.

    Google Scholar 

  2. K. M. Chandy and C. Kesselman. The derivation of compositional programs. In Joint International Conference and Symposium on Logic Programming. MIT Press, 1992.

    Google Scholar 

  3. H. Essafi, D. Juvin, J.L. Basille and J.Y. Latil. Sympati 2, a 1.5 d processor array for image application. In J.L. Lacoume A. Chehikian N. Martin and J. Malbos, editors, Signal Processing IV: Theories and Applications. Elsevier Science Publishers B.V. (North-Holland), 1988.

    Google Scholar 

  4. T. Mac Donald. C for numerical computing. J. of Supercomputing, 5, 1991.

    Google Scholar 

  5. P. Dutilleux. An implementation of the algorithme à trous to compute wavelet transform. Springer-Verlag, 1989.

    Google Scholar 

  6. D. Esteban and C. Galand. Application of quadraqture mirror filters to split band voice coding systems. In International Conference on Acoustic, Speech and Signal Processing, pages 191–195, Washington, USA, May 1977.

    Google Scholar 

  7. I. Foster and K.M. Chandy. Fortran m: A language for modular parallel programming. J. Parallel and Distributed Computing, 1992. (to appear), Preprint MCS-P327-0992.

    Google Scholar 

  8. C. Galand. Codage en sous-bandes: théorie et application à la compression numérique du signal de la parole. PhD thesis, Université de Nice-France, March 1983.

    Google Scholar 

  9. M. Pic H. Essafi. Application of parallel computing to wavelet transform. In International Conference on Wavelets and Applications, Toulouse, 1992.

    Google Scholar 

  10. Hpc++, extreme computing. Technical report, California Institute of Technology and CICA, University of Indiana, 1994. http://www.cica.indiana.edu/extreme/hpc++/index.html.

    Google Scholar 

  11. B. Avalani I. Foster, M. Xu and A. Choudhary. A compilation system that integrates high performance fortran and fortran m. In Scalable High Peformance Computing Conf. IEEE Computer Science Press, 1994. (to appear).

    Google Scholar 

  12. D. Lee. Scrambled storage for parallel memory systems. In Internat. Symp. Comput. Architecture, 1988.

    Google Scholar 

  13. S. G. Mallat. Multifrequency channel decompositions of images and wavelet models. IEEE Trans. on Acoustics, Speech and Signal Processing, 37(12):2091–2110, 1989.

    Google Scholar 

  14. S. G. Mallat. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on Pattern Analysis and Machine Inte lligence, 11(7):674–693, 1989.

    Google Scholar 

  15. Morlet J. M. Holschneider, Krondland-Martinet R. and Tchamitchian P. The algorithme à trous., May 1988.

    Google Scholar 

  16. D. Juvin, M. Pic, H. Essafi. Wavelet transform on parallel simd architectures. In Visual Information Processing II, volume 1961 of SPIE Proceedings, Orlando, 1993. SPIE.

    Google Scholar 

  17. N. Paris. Definition of pompc. Technical Report LIENS-92-5-bis, Ecole Normale Supérieure, 1992.

    Google Scholar 

  18. D.J. Kuck P. Budnik. the organization and use of parallel memories. IEEE Trans. Comput., C-20, 1971.

    Google Scholar 

  19. M.J. Quinn, P.J. Hatcher. Data-Parallel Programming on MIMD computers. M.I.T. Press, Cambridge (Massachusetts), 1991.

    Google Scholar 

  20. R. Stallman. Using and porting gnu cc. Technical report, GNU is Not Un*x, 1994.

    Google Scholar 

  21. D. Juvin T. Colette, H. Essafi and J. Kaiser. Sympati x: A simd computer performing the low and intermediate levels of image processing. In PARLE, June 1992.

    Google Scholar 

  22. C* programming guide. Technical report, Thinking Machines Corporation, 1991.

    Google Scholar 

  23. M.V. Wickerhauser. Picture compression by best-basis sub-band coding. Technical report, Yale University, New Haven, Connecticut, 1990.

    Google Scholar 

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Victor Malyshkin

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© 1995 Springer-Verlag Berlin Heidelberg

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Pic, M.M., Essafi, H., Viala, M., Nicolas, L. (1995). T++: An object-oriented language to express task and data parallelism on Multi-SIMD computers. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1995. Lecture Notes in Computer Science, vol 964. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60222-4_117

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  • DOI: https://doi.org/10.1007/3-540-60222-4_117

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  • Print ISBN: 978-3-540-60222-4

  • Online ISBN: 978-3-540-44754-2

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