Towards a Strategy for Performance Prediction on Heterogeneous Architectures
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Data
2019-01-01
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Resumo
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.
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Heterogeneous systems, Parallel processing, Performance prediction
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 11333 LNCS, p. 247-253.