Driving Against the Memory Wall: The Role of Memory for Autonomous Driving

  • Autonomous driving is disrupting the conventional automotive development. In fact, autonomous driving kicks off the consolidation of control units, i.e. the transition from distributed Electronic Control Units (ECUs) to centralized domain controllers. Platforms like Audi’s zFAS demonstrate this very clearly, where GPUs, Custom SoCs, Microcontrollers, and FPGAs are integrated on a single domain controller in order to perform sensor fusion, processing and decision making on a single Printed Circuit Board (PCB). The communication between these heterogeneous components and the algorithms for Advanced Driving Assistant Systems (ADAS) itself requires a huge amount of memory bandwidth, which will bring the Memory Wall from High Performance Computing (HPC) and data-centers directly in our cars. In this paper we highlight the roles and issues of Dynamic Random Access Memories (DRAMs) for future autonomous driving architectures.

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Verfasserangaben:Matthias Jung, Norbert Wehn
URN (Permalink):urn:nbn:de:hbz:386-kluedo-52862
Titel des übergeordneten Werkes (Englisch):Workshop 23.03. 2018: New Platforms for Future Cars: Current and Emerging Trends at IEEE Conference Design, Automation and Test in Europe (DATE)
Sprache der Veröffentlichung:Englisch
Veröffentlichungsdatum (online):05.06.2018
Jahr der Veröffentlichung:2018
Veröffentlichende Institution:Technische Universität Kaiserslautern
Datum der Publikation (Server):07.06.2018
Fachbereiche / Organisatorische Einheiten:Fachbereich Elektrotechnik und Informationstechnik
CCS-Klassifikation (Informatik):B. Hardware / B.3 MEMORY STRUCTURES / B.3.1 Semiconductor Memories (NEW) (B.7.1) / Dynamic memory (DRAM) (NEW)
DDC-Sachgruppen:6 Technik, Medizin, angewandte Wissenschaften / 621.3 Elektrontechnik, Elektronik
Lizenz (Deutsch):Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0)