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Conference Papers Year : 2016

Performance Prediction of Application Mapping in Manycore Systems with Artificial Neural Networks

Abstract

The growing demand for smarter high-performance embedded systems leads to the integration of multiple functionalities in on-chip systems with tens (even hundreds) of cores. This trend opens a very challenging question about the optimal resource allocation in those manycore systems. Answering this question is key to meet the performance and energy requirements. This paper deals with a learning technique applicable to manycore systems in order to predict mapping-related performances. The resulting prediction models can enable to improve dynamic resource allocation decisions. Our proposal is demonstrated on two automotive application case studies with very promising results.
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lirmm-01385641 , version 1 (21-10-2016)

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Abdoulaye Gamatié, Roman Ursu, Manuel Selva, Gilles Sassatelli. Performance Prediction of Application Mapping in Manycore Systems with Artificial Neural Networks. MCSoC: Embedded Multicore/Many-core Systems-on-Chip, Sep 2016, Lyon, France. pp.185-192, ⟨10.1109/MCSoC.2016.17⟩. ⟨lirmm-01385641⟩
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