Driving Against the Memory Wall: The Role of Memory for Autonomous Driving
Matthias Jung, Norbert Wehn · Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology) · 2018
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.