Actas de congresos
Towards a Strategy for Performance Prediction on Heterogeneous Architectures
Fecha
2019-01-01Registro en:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11333 LNCS, p. 247-253.
1611-3349
0302-9743
10.1007/978-3-030-15996-2_18
2-s2.0-85064598015
Autor
Universidade Estadual Paulista (UNESP)
Institución
Resumen
Performance prediction of applications has always been a great challenge, even for homogeneous architectures. However, today’s trend is the design of cluster running in a heterogeneous architecture, which increases the complexity of new strategies to predict the behavior and time spent by an application to run. In this paper we present a strategy that predicts the performance of an application on different architectures and rank then according to the performance that the application can achieve on each architecture. The proposed strategy was able to correctly rank three of four applications tested without overhead implications. Our next step is to extend the metrics in order to increase the accuracy.