@inbook{747cbb3f5f514e88aae8afe642c9ca23,
title = "Predicting performance of hybrid master/worker applications using model-based regression trees",
abstract = "Nowadays, there are several features related to node architecture, network topology and programming model that significantly affect the performance of applications. Therefore, the task of adjusting the values of parameters of hybrid parallel applications to achieve the best performance requires a high degree of expertise and a huge effort. Determining a performance model that considers all the system and application features is a very complex task that in most cases produces poor results. In order to simplify this goal and improve the results, we introduce a model-based regression tree technique to improve the accuracy of performance prediction for parallel Master/Worker applications on homogeneous multicore systems. The technique has been used to model the iteration time of the general expression for performance prediction. This approach significantly reduces the effort in getting an accurate prediction model, although it requires a relatively large training data set. The proposed model determines the configuration of the appropriate number of workers and threads of the hybrid application to achieve the best possible performance.",
keywords = "Hybrid applications, Master/Worker, Multicore, Performance model, Regression tree",
author = "Abel Castellanos and Andreu Moreno and Joan Sorribes and Tom{\`a}s Margalef",
year = "2014",
month = mar,
day = "9",
doi = "10.1109/HPCC.2014.61",
language = "Ingl{\'e}s estadounidense",
series = "Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "355--362",
booktitle = "Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014",
address = "Estados Unidos",
}