The push towards automated and connected driving functionalities mandates the use of heterogeneous HW platforms in order to provide the required computational resources. For these platforms, the established methods for performance modelling in industry are no longer effective. In this paper, we propose an initial modelling concept for heterogeneous platforms which can then be fed into appropriate tools to derive effective performance predictions. The approach is demonstrated for a prototypical automated driving application on the Nvidia Tegra X2 platform.
System Performance Modelling of Heterogeneous HW Platforms: An Automated Driving Case Study / Wurst, F.; Dasari, D.; Hamann, A.; Ziegenbein, D.; Sanudo, I.; Capodieci, N.; Bertogna, M.; Burgio, P.. - (2019), pp. 365-372. (Intervento presentato al convegno 22nd Euromicro Conference on Digital System Design, DSD 2019 tenutosi a grc nel 2019) [10.1109/DSD.2019.00060].
System Performance Modelling of Heterogeneous HW Platforms: An Automated Driving Case Study
Sanudo I.;Capodieci N.;Bertogna M.;Burgio P.
2019
Abstract
The push towards automated and connected driving functionalities mandates the use of heterogeneous HW platforms in order to provide the required computational resources. For these platforms, the established methods for performance modelling in industry are no longer effective. In this paper, we propose an initial modelling concept for heterogeneous platforms which can then be fed into appropriate tools to derive effective performance predictions. The approach is demonstrated for a prototypical automated driving application on the Nvidia Tegra X2 platform.
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