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Programming parallel dense matrix factorizations with look-ahead and OpenMP

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Programming parallel dense matrix factorizations with look-ahead and OpenMP

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Catalán, S.; Castelló, A.; Igual, FD.; Rodríguez-Sánchez, R.; Quintana Ortí, ES. (2020). Programming parallel dense matrix factorizations with look-ahead and OpenMP. Cluster Computing. 23(1):359-375. https://doi.org/10.1007/s10586-019-02927-z

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Título: Programming parallel dense matrix factorizations with look-ahead and OpenMP
Autor: Catalán, Sandra Castelló, Adrián Igual, Francisco D. Rodríguez-Sánchez, Rafael Quintana Ortí, Enrique Salvador
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using OpenMP, that departs from the legacy (or conventional) solution, which simply extracts concurrency from a multi-threaded ...[+]
Palabras clave: Matrix factorizations , Look-ahead , Multi-threading , OpenMP , Lightweight threads , High performance computing
Derechos de uso: Reserva de todos los derechos
Fuente:
Cluster Computing. (issn: 1386-7857 )
DOI: 10.1007/s10586-019-02927-z
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s10586-019-02927-z
Código del Proyecto:
info:eu-repo/grantAgreement/EC/H2020/671602/EU/Programming Model INTERoperability ToWards Exascale (INTERTWinE)/
info:eu-repo/grantAgreement/MINECO//TIN2014-53495-R/ES/COMPUTACION HETEROGENEA DE BAJO CONSUMO/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-82972-R/ES/TECNICAS ALGORITMICAS PARA COMPUTACION DE ALTO RENDIMIENTO CONSCIENTE DEL CONSUMO ENERGETICO Y RESISTENTE A ERRORES/
info:eu-repo/grantAgreement/MINECO//TIN2015-65277-R/ES/COMPPUTACION HETEROGENEA EFICIENTE: DEL PROCESADOR AL DATACENTER/
Agradecimientos:
The researchers from Universidad Jaume I were supported by the CICYT Projects TIN2014-53495-R and TIN2017-82972-R of the MINECO and FEDER, and the H2020 EU FETHPC Project 671602 "INTERTWinE". The researchers from Universidad ...[+]
Tipo: Artículo

References

Anderson, E., Bai, Z., Susan Blackford, L., Demmel, J., Dongarra, J.J., Croz, J.D., Hammarling, S., Greenbaum, A., McKenney, A., Sorensen, D.C.: LAPACK Users’ guide. SIAM, 3rd edition (1999)

Badia, R.M., Herrero, J.R., Labarta, J., Pérez, J.M., Quintana-Ortí, E.S., Quintana-Ortí, G.: Parallelizing dense and banded linear algebra libraries using SMPSs. Conc. Comp. 21, 2438–2456 (2009)

Bientinesi, P., Gunnels, J.A., Myers, M.E., Quintana-Ortí, E.S., van de Geijn, R.A.: The science of deriving dense linear algebra algorithms. ACM Trans. Math. Softw. 31(1), 1–26 (2005) [+]
Anderson, E., Bai, Z., Susan Blackford, L., Demmel, J., Dongarra, J.J., Croz, J.D., Hammarling, S., Greenbaum, A., McKenney, A., Sorensen, D.C.: LAPACK Users’ guide. SIAM, 3rd edition (1999)

Badia, R.M., Herrero, J.R., Labarta, J., Pérez, J.M., Quintana-Ortí, E.S., Quintana-Ortí, G.: Parallelizing dense and banded linear algebra libraries using SMPSs. Conc. Comp. 21, 2438–2456 (2009)

Bientinesi, P., Gunnels, J.A., Myers, M.E., Quintana-Ortí, E.S., van de Geijn, R.A.: The science of deriving dense linear algebra algorithms. ACM Trans. Math. Softw. 31(1), 1–26 (2005)

Bischof, C.H., Lang, B., Sun, X.: Algorithm 807: the SBR toolbox–software for successive band reduction. ACM Trans. Math. Softw. 26(4), 602–616 (2000)

Buttari, A., Langou, J., Kurzak, J., Dongarra, J.: A class of parallel tiled linear algebra algorithms for multicore architectures. Parallel Comput. 35(1), 38–53 (2009)

Castelló, A., Mayo, R., Sala, K., Beltran, V., Balaji, P., Peña, A.J.: On the adequacy of lightweight thread approaches for high-level parallel programming models. Future Gener. Comput. Syst. 84, 22–31 (2018)

Castelló, A., Peña, A.J., Seo, S., Mayo, R., Balaji, P., Quintana-Ortí, E.S.: A review of lightweight thread approaches for high performance computing. In: Proceedings of the IEEE International Conference on Cluster Computing, Taipei, Taiwan (September 2016)

Castelló, A., Seo, S., Mayo, R., Balaji, P., Quintana-Ortí, E.S., Peña, A.J.: GLT: a unified API for lightweight thread libraries. In: Proceedings of the IEEE International European Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain (August 2017)

Castelló, A., Seo, S., Mayo, R., Balaji, P., Quintana-Ortí, E.S., Peña, A.J.: GLTO: on the adequacy of lightweight thread approaches for OpenMP implementations. In: Proceedings of the International Conference on Parallel Processing, Bristol, UK (August 2017)

Catalán, S, Herrero, JR., Quintana-Ortí, E.S., Rodríguez-Sánchez, R., van de Geijn, R.A.: A case for malleable thread-level linear algebra libraries: The LU factorization with partial pivoting. CoRR (2016) arXiv:1611.06365

Catalán, S., Igual, F.D., Mayo, R., Rguez-Sánchez, R.: Architecture-aware configuration and scheduling of matrix multiplication on asymmetric multicore processors. Clust. Comput. 19(3), 1037–1051 (2016)

Chameleon project. http://project.inria.fr/chameleon/

Demmel, J.: Applied Numerical Linear Algebra. Society for Industrial and Applied Mathematics, Paris (1997)

Dongarra, J.J., Croz, J.D., Hammarling, S., Duff, I.: A set of level 3 basic linear algebra subprograms. ACM Trans. Math. Softw. 16(1), 1–17 (1990)

FLAME project home page. http://www.cs.utexas.edu/users/flame/

Golub, G.H., Van Loan, C.F.: Matrix Computations, 3rd edn. The Johns Hopkins University Press, Baltimore (1996)

Goto, K., van de Geijn, R.A.: Anatomy of high-performance matrix multiplication. ACM Trans. Math. Softw. 34(3), 12:1–12:25 (2008)

Goto, K., van de Geijn, R.: High performance implementation of the level-3 BLAS. ACM Trans. Math. Softw. 35(1), 4:1–4:14 (2008)

Grosser, B., Lang, B.: Efficient parallel reduction to bidiagonal form. Parallel Comput. 25(8), 969–986 (1999)

Gunter, B.C., van de Geijn, R.A.: Parallel out-of-core computation and updating the QR factorization. ACM Trans. Math. Soft. 31(1), 60–78 (2005)

IBM. Engineering and Scientific Subroutine Library. http://www-03.ibm.com/systems/power/software/essl/ (2015)

Intel. Math Kernel Library. https://software.intel.com/en-us/intel-mkl (2015)

OmpSs project home page. http://pm.bsc.es/ompss

http://www.openblas.net (2015)

OpenMP API specification for parallel programming. http://www.openmp.org (2017)

PLASMA project home page. http://icl.cs.utk.edu/plasma

Quintana-Ortí, E.S., van de Geijn, R.A.: Updating an LU factorization with pivoting. ACM Trans. Math. Softw. 35(2), 11:1–11:16 (2008)

Quintana-Ortí, G., Quintana-Ortí, E.S., van de Geijn, R.A., Van Zee, F.G., Chan, E.: Programming matrix algorithms-by-blocks for thread-level parallelism. ACM Trans. Math. Softw. 36(3), 14:1–14:26 (2009)

Rodríguez-Sánchez, R., Catalán, Sandra, H., José, R., Quintana-Ortí, E.S., Tomás, A.E.: Two-sided reduction to compact band forms with look-ahead (2017) CoRR, arXiv:1709.00302

Seo, S., Amer, A., Balaji, P., Bordage, C., Bosilca, G., Brooks, A., Carns, P., Castelló, A., Genet, D., Herault, T., Iwasaki, S., Jindal, P., Kale, S., Krishnamoorthy, S., Lifflander, J., Lu, H., Meneses, E., Snir, M., Sun, Y., Taura, K., Beckman, P.: Argobots: a lightweight low-level threading and tasking framework. IEEE Trans. Parallel Distrib. Syst. PP(99), 1–1 (2017)

Smith, T.M., van de Geijn, R., Smelyanskiy, M., Hammond, J.R., Van Zee, F.G.: Anatomy of high-performance many-threaded matrix multiplication. In: Proceedings of IEEE 28th International Parallel and Distributed Processing Symposium, IPDPS’14, pp. 1049–1059 (2014)

StarPU project. http://runtime.bordeaux.inria.fr/StarPU/

Stein, D., Shah, D.: Implementing lightweight threads. In: USENIX Summer (1992)

Strazdins, P.: A comparison of lookahead and algorithmic blocking techniques for parallel matrix factorization. Technical Report TR-CS-98-07, Department of Computer Science, The Australian National University, Canberra 0200 ACT, Australia (1998)

Van Zee, F.G., van de Geijn, R.A.: BLIS: a framework for rapidly instantiating BLAS functionality. ACM Trans. Math. Softw. 41(3), 14:1–14:33 (2015)

Whaley, C.R., Dongarra, J.J.: Automatically tuned linear algebra software. In: Proceedings of SC’98 (1998)

Van Zee, F.G., Smith, T.M., Marker, B., Low, T., Van De Geijn, R.A., Igual, F.D., Smelyanskiy, M., Zhang, X., Kistler, M., Austel, V., Gunnels, J.A., Killough, L.: The BLIS framework: experiments in portability. ACM Trans. Math. Softw. 42(2), 12:1–12:19 (2016)

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