Brook Auto: High-Level Certification-Friendly Programming for GPU-powered Automotive Systems

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dc.contributor	Barcelona Supercomputing Center
dc.contributor.author	Trompouki, Matina M.
dc.contributor.author	Kosmidis, Leonidas
dc.date	2018
dc.identifier.citation	Trompouki, M. M.; Kosmidis, L. Brook Auto: High-Level Certification-Friendly Programming for GPU-powered Automotive Systems. A: "DAC '18: Proceedings of the 55h Annual Design Automation Conference 2018". Association for Computing Machinery (ACM), 2018, p. 1-6.
dc.identifier.citation	978-1-4503-5700-5
dc.identifier.citation	10.1145/3195970.3196002
dc.identifier.uri	http://hdl.handle.net/2117/116182
dc.language.iso	eng
dc.publisher	Association for Computing Machinery (ACM)
dc.relation	eu-repo/grantAgreement/MINECO/PE2013-2016/TIN2015-65316-P
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica
dc.subject	High performance computing
dc.subject	Processors, High performance
dc.subject	Computing methodologies
dc.subject	Parallel programming languages
dc.subject	Graphics processors
dc.subject	Computer systems organization
dc.subject	Heterogeneous (hybrid) systems
dc.subject	Embedded software
dc.subject	Supercomputadors
dc.subject	Processament en paral·lel (Ordinadors)
dc.title	Brook Auto: High-Level Certification-Friendly Programming for GPU-powered Automotive Systems
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Modern automotive systems require increased performance to implement Advanced Driving Assistance Systems (ADAS). GPU-powered platforms are promising candidates for such computational tasks, however current low-level programming models challenge the accelerator software certification process, while they limit the hardware selection to a fraction of the available platforms. In this paper we present Brook Auto, a high-level programming language for automotive GPU systems which removes these limitations. We describe the challenges and solutions we faced in its implementation, as well as a complete evaluation in terms of performance and productivity, which shows the effectiveness of our method.
dc.description.abstract	This work has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence.
dc.description.abstract	Peer Reviewed

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