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Characterizing self-driving tasks in general-purpose architectures

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hdl:2117/356419

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Exenberger Becker, Pedro HenriqueMés informacióMés informació
Arnau Montañés, José MaríaMés informacióMés informació
González Colás, Antonio MaríaMés informacióMés informacióMés informació
Document typePart of book or chapter of book
Defense date2021-09-15
PublisherEuropean Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectCoCoUnit - CoCoUnit: An Energy-Efficient Processing Unit for Cognitive Computing (EC-H2020-833057)
ARQUITECTURAS DE DOMINIO ESPECIFICO PARA SISTEMAS DE COMPUTACION ENERGETICAMENTE EFICIENTES (AEI-PID2020-113172RB-I00)
Abstract
Autonomous Vehicles (AVs) have the potential to radically change the automotive industry. How- ever, computing solutions for AVs have to meet severe performance constraints to guarantee a safe driving experience. Current solutions either exhibit high cost or fail to meet the stringent latency constraints. Therefore, the popularization of AVs requires a low-cost yet effective computing sys- tem. Understanding the sources of latency is key in order to improve autonomous driving systems. Here, we present a detailed characterization of Autoware, a modern self-driving car system. We analyze the performance of the different components and leverage hardware counters to identify the main bottlenecks.
CitationExenberger, P.; Arnau, J.; González, A. Characterizing self-driving tasks in general-purpose architectures. A: "ACACES 2021 poster abstracts: September 15, 2021 Fiuggi, Italy". European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), 2021, p. 117-120. 
URIhttp://hdl.handle.net/2117/356419
ISBN978-88-905806-8-0
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