The next-generation of partially and fully autonomous cars will be powered by embedded many-core platforms. Technologies for Advanced Driver Assistance Systems (ADAS) need to process an unprecedented amount of data within tight power budgets, making those platform the ideal candidate architecture. Integrating tens-to-hundreds of computing elements that run at lower frequencies allows obtaining impressive performance capabilities at a reduced power consumption, that meets the size, weight and power (SWaP) budget of automotive systems. Unfortunately, the inherent architectural complexity of many-core platforms makes it almost impossible to derive real-time guarantees using “traditional” state-of-the-art techniques, ultimately preventing their adoption in real industrial settings. Having impressive average performances with no guaranteed bounds on the response times of the critical computing activities is of little if no use in safety-critical applications. Project Hercules will address this issue, and provide the required technological infrastructure to exploit the tremendous potential of embedded many-cores for the next generation of automotive systems. This work gives an overview of the integrated Hercules software framework, which allows achieving an order-of-magnitude of predictable performance on top of cutting-edge Commercial-Off-The-Shelf components (COTS). The proposed software stack will let both real-time and non real-time application coexist on next-generation, power-efficient embedded platforms, with preserved timing guarantees.

A software stack for next-generation automotive systems on many-core heterogeneous platforms / Burgio, Paolo; Bertogna, Marko; Capodieci, Nicola; Cavicchioli, Roberto; Sojka, Michal; Houdek, Přemysl; Marongiu, Andrea; Gai, Paolo; Scordino, Claudio; Morelli, Bruno. - In: MICROPROCESSORS AND MICROSYSTEMS. - ISSN 0141-9331. - (2017), pp. 299-311. [10.1016/j.micpro.2017.06.016]

A software stack for next-generation automotive systems on many-core heterogeneous platforms

Paolo Burgio;Marko Bertogna;Nicola Capodieci;Roberto Cavicchioli;Andrea Marongiu;
2017

Abstract

The next-generation of partially and fully autonomous cars will be powered by embedded many-core platforms. Technologies for Advanced Driver Assistance Systems (ADAS) need to process an unprecedented amount of data within tight power budgets, making those platform the ideal candidate architecture. Integrating tens-to-hundreds of computing elements that run at lower frequencies allows obtaining impressive performance capabilities at a reduced power consumption, that meets the size, weight and power (SWaP) budget of automotive systems. Unfortunately, the inherent architectural complexity of many-core platforms makes it almost impossible to derive real-time guarantees using “traditional” state-of-the-art techniques, ultimately preventing their adoption in real industrial settings. Having impressive average performances with no guaranteed bounds on the response times of the critical computing activities is of little if no use in safety-critical applications. Project Hercules will address this issue, and provide the required technological infrastructure to exploit the tremendous potential of embedded many-cores for the next generation of automotive systems. This work gives an overview of the integrated Hercules software framework, which allows achieving an order-of-magnitude of predictable performance on top of cutting-edge Commercial-Off-The-Shelf components (COTS). The proposed software stack will let both real-time and non real-time application coexist on next-generation, power-efficient embedded platforms, with preserved timing guarantees.
2017
299
311
A software stack for next-generation automotive systems on many-core heterogeneous platforms / Burgio, Paolo; Bertogna, Marko; Capodieci, Nicola; Cavicchioli, Roberto; Sojka, Michal; Houdek, Přemysl; Marongiu, Andrea; Gai, Paolo; Scordino, Claudio; Morelli, Bruno. - In: MICROPROCESSORS AND MICROSYSTEMS. - ISSN 0141-9331. - (2017), pp. 299-311. [10.1016/j.micpro.2017.06.016]
Burgio, Paolo; Bertogna, Marko; Capodieci, Nicola; Cavicchioli, Roberto; Sojka, Michal; Houdek, Přemysl; Marongiu, Andrea; Gai, Paolo; Scordino, Claud...espandi
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0141933116304550-main.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 2.68 MB
Formato Adobe PDF
2.68 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
j.micpro.2017.06.016.pdf

Open access

Tipologia: Versione dell'autore revisionata e accettata per la pubblicazione
Dimensione 5.52 MB
Formato Adobe PDF
5.52 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1172261
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 12
social impact