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Empirical Installation of Linear Algebra Shared-Memory Subroutines for Auto-Tuning

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Empirical Installation of Linear Algebra Shared-Memory Subroutines for Auto-Tuning

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Cámara, J.; Cuenca, J.; Giménez, D.; García, LP.; Vidal Maciá, AM. (2014). Empirical Installation of Linear Algebra Shared-Memory Subroutines for Auto-Tuning. International Journal of Parallel Programming. 42(3):408-434. https://doi.org/10.1007/s10766-013-0249-6

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Título: Empirical Installation of Linear Algebra Shared-Memory Subroutines for Auto-Tuning
Autor: Cámara, Jesús Cuenca, Javier Giménez, Domingo García, Luis Pedro Vidal Maciá, Antonio Manuel
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
The introduction of auto-tuning techniques in linear algebra shared-memory routines is analyzed. Information obtained in the installation of the routines is used at running time to take some decisions to reduce the total ...[+]
Palabras clave: Linear algebra libraries , Linear algebra routines , Empirical installation , Shared-memory , Auto-tuning
Derechos de uso: Reserva de todos los derechos
Fuente:
International Journal of Parallel Programming. (issn: 0885-7458 )
DOI: 10.1007/s10766-013-0249-6
Editorial:
Springer Verlag (Germany)
Versión del editor: http://dx.doi.org/10.1007/s10766-013-0249-6
Código del Proyecto:
info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO09%2F2009%2F013/ES/Computacion de altas prestaciones sobre arquitecturas actuales en porblemas de procesado múltiple de señal/
info:eu-repo/grantAgreement/MINECO//TIN2012-38341-C04-03/ES/MEJORA DE ARQUITECTURA DE SERVIDORES, SERVICIOS Y APLICACIONES/
info:eu-repo/grantAgreement/f SéNeCa//08763%2FPI%2F08/ES/
Descripción: The final publication is available at Springer via http://dx.doi.org/10.1007/s10766-013-0249-6
Agradecimientos:
Partially supported by Fundacion Seneca, Consejeria de Educacion de la Region de Murcia, 08763/PI/08, PROMETEO/2009/013 from Generalitat Valenciana, the Spanish Ministry of Education and Science through TIN2012-38341-C04-03, ...[+]
Tipo: Artículo

References

Agullo, E., Demmel, J., Dongarra, J., Hadri, B., Kurzak, J., Langou, J., Ltaief, H., Luszczek, P., Tomov, S.: Numerical linear algebra on emerging architectures: the PLASMA and MAGMA projects. J. Phys. Conf. Ser. 180(1), 1–5 (2009)

Alberti, P., Alonso, P., Vidal, A.M., Cuenca, J., Giménez, D.: Designing polylibraries to speed up linear algebra computations. Int. J. High Perform. Comput. Netw. 1/2/3(1), 75–84 (2004)

Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J.J., Du Croz, J., Grenbaum, A., Hammarling, S., McKenney, A., Ostrouchov, S., D. Sorensen, S.: LAPACK User’s Guide. Society for Industrial and Applied Mathematics, Philadelphia (1995) [+]
Agullo, E., Demmel, J., Dongarra, J., Hadri, B., Kurzak, J., Langou, J., Ltaief, H., Luszczek, P., Tomov, S.: Numerical linear algebra on emerging architectures: the PLASMA and MAGMA projects. J. Phys. Conf. Ser. 180(1), 1–5 (2009)

Alberti, P., Alonso, P., Vidal, A.M., Cuenca, J., Giménez, D.: Designing polylibraries to speed up linear algebra computations. Int. J. High Perform. Comput. Netw. 1/2/3(1), 75–84 (2004)

Anderson, E., Bai, Z., Bischof, C., Demmel, J., Dongarra, J.J., Du Croz, J., Grenbaum, A., Hammarling, S., McKenney, A., Ostrouchov, S., D. Sorensen, S.: LAPACK User’s Guide. Society for Industrial and Applied Mathematics, Philadelphia (1995)

Bernabé, G., Cuenca, J., Giménez, D.: Optimization techniques for 3D-FWT on systems with manycore GPUs and multicore CPUs. In: ICCS (2013)

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)

Cámara, J., Cuenca, J., Giménez, D., Vidal. A.M.: Empirical autotuning of two-level parallel linear algebra routines on large cc-NUMA systems. In: ISPA (2012)

Caron, E., Desprez, F., Suter, F.: Parallel extension of a dynamic performance forecasting tool. Scalable Comput. Pract. Exp. 6(1), 57–69 (2005)

Chen, Z., Dongarra, J., Luszczek, P., Roche, K.: Self adapting software for numerical linear algebra and LAPACK for clusters. Parallel Comput. 29, 1723–1743 (2003)

Cuenca, J., Giménez, D., González, J.: Achitecture of an automatic tuned linear algebra library. Parallel Comput. 30(2), 187–220 (2004)

Cuenca, J., García, L.P., Giménez, D.: Improving linear algebra computation on NUMA platforms through auto-tuned nested parallelism. In: Proceedings of the 2012 EUROMICRO Conference on Parallel, Distributed and Network Processing (2012)

Frigo, M.: FFTW: An adaptive software architecture for the FFT. In: Proceedings of the ICASSP Conference, vol. 3, p. 1381 (1998)

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

Im, E.-J., Yelick, K., Vuduc, R.: Sparsity: optimization framework for sparse matrix kernels. Int. J. High Perform. Comput. Appl. (IJHPCA) 18(1), 135–158 (2004)

Intel MKL web page.: http://software.intel.com/en-us/intel-mkl/

Jerez, S., Montávez, J.-P., Giménez, D.: Optimizing the execution of a parallel meteorology simulation code. In: Proceedings of the 23rd IEEE International Parallel and Distributed Processing Symposium. IEEE (2009)

Katagiri, T., Kise, K., Honda, H., Yuba, T.: Fiber: a generalized framework for auto-tuning software. Springer LNCS 2858, 146–159 (2003)

Katagiri, T., Kise, K., Honda, H., Yuba, T.: ABCLib-DRSSED: a parallel eigensolver with an auto-tuning facility. Parallel Comput. 32(3), 231–250 (2006)

Kurzak, J., Tomov, S., Dongarra, J.: Autotuning gemm kernels for the FERMI GPU. IEEE Trans. Parallel Distrib. Syst. 23(11), 2045–2057 (2012)

Lastovetsky, A.L., Reddy, R., Higgins, R.: Building the functional performance model of a processor. In: SAC, pp. 746–753 (2006)

Li, J., Skjellum, A., Falgout, R.D.: A poly-algorithm for parallel dense matrix multiplication on two-dimensional process grid topologies. Concurrency Pract. Exp. 9(5), 345–389 (1997)

Naono, K., Teranishi, K., Cavazos, J., Suda, R., (eds.): Software Automatic Tuning. From Concepts to State-of-the-Art Results. Springer, Berlin (2010)

Nath, R., Tomov, S., Dongarra, J.: An improved MAGMA gemm for FERMI graphics processing units. IJHPCA 24(4), 511–515 (2010)

Petitet, A., Blackford, L.S., Dongarra, J., Ellis, B., Fagg, G.E., Roche, K., Vadhiyar, S.S.: Numerical libraries and the grid. IJHPCA 15(4), 359–374 (2001)

PLASMA.: http://icl.cs.utk.edu/plasma/

Püschel, M., Moura, J.M.F., Singer, B., Xiong, J., Johnson, J.R., Padua, D.A., Veloso, M.M., Johnson, R.W.: Spiral: a generator for platform-adapted libraries of signal processing algorithms. IJHPCA 18(1), 21–45 (2004)

Seshagiri, L., Wu, M.-S., Sosonkina, M., Zhang, Z., Gordon, M.S., Schmidt, M.W.: Enhancing adaptive middleware for quantum chemistry applications with a database framework. In: IPDPS Workshops, pp. 1–8 (2010)

Tanaka, T., Katagiri, T., Yuba, T.: d-Spline based incremental parameter estimation in automatic performance tuning. In: PARA, pp. 986–995 (2006)

Vuduc, R., Demmel, J., Bilmes, J.: Statistical models for automatic performance tuning. In: International Conference on Computational Science (1), pp. 117–126 (2001)

Whaley, R.C., Petitet, A., Dongarra, J.: Automated empirical optimizations of software and the ATLAS project. Parallel Comput. 27(1–2), 3–35 (2001)

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