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Predicting Performance of Hybrid Master/Worker Applications Using Model-Based Regression Trees.

A. Castellanos, A. Moreno, J. Sorribes, and T. Margalef. HPCC/CSS/ICESS, page 355-362. IEEE, (2014)

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Designing parallel systems: a performance prediction problem.E. Luque, R. Suppi, and J. Sorribes. Information & Software Technology, 34 (12): 813-823 (1992)Load balancing in homogeneous pipeline based applications.A. Moreno, E. César, A. Guevara, J. Sorribes, and T. Margalef. Parallel Computing, 38 (3): 125-139 (2012)Predicting Performance of Hybrid Master/Worker Applications Using Model-Based Regression Trees.A. Castellanos, A. Moreno, J. Sorribes, and T. Margalef. HPCC/CSS/ICESS, page 355-362. IEEE, (2014)Modeling Master-Worker Applications in POETRIES.E. César, J. Mesa, J. Sorribes, and E. Luque. HIPS, page 22-30. IEEE Computer Society, (2004)Simulation in Parallel Software Design.R. Suppi, E. César, J. Falguera, M. Serranó, J. Sorribes, E. Luque, G. Dózsa, P. Kacsuk, and T. Fadgyas. Euro-PDS, page 51-60. IASTED/ACTA Press, (1997)Task distribution using factoring load balancing in Master-Worker applications.A. Moreno, E. César, J. Sorribes, T. Margalef, and E. Luque. Inf. Process. Lett., 109 (16): 902-906 (2009)Dynamic performance tuning supported by program specification.E. César, A. Morajko, T. Margalef, J. Sorribes, A. Espinosa, and E. Luque. Scientific Programming, 10 (1): 35-44 (2002)Automatic Tuning of Master/Worker Applications.A. Morajko, E. César, P. Caymes-Scutari, T. Margalef, J. Sorribes, and E. Luque. Euro-Par, volume 3648 of Lecture Notes in Computer Science, page 95-103. Springer, (2005)Dynamic Pipeline Mapping (DPM).A. Moreno, E. César, A. Guevara, J. Sorribes, T. Margalef, and E. Luque. Euro-Par, volume 5168 of Lecture Notes in Computer Science, page 295-304. Springer, (2008)Parallel systems development in education: a guided method.E. Luque, J. Sorribes, R. Suppi, E. César, J. Falguera, and M. Serranó. ITiCSE, page 156-158. ACM, (1996)

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Predicting Performance of Hybrid Master/Worker Applications Using Model-Based Regression Trees.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Predicting Performance of Hybrid Master/Worker Applications Using Model-Based Regression Trees.

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Predicting Performance of Hybrid Master/Worker Applications Using Model-Based Regression Trees.