Driving into the memory wall


== Abstract ==

utonomous driving is disrupting conventional automotive development. Underlying reasons include control unit consolidation, the use of components originally developed for the consumer market, and the large amount of data that must be processed. For instance, Audi's zFAS or NVIDIA's Xavier platform integrate GPUs, custom accelerators, and CPUs within a single domain controller to perform sensor fusion, processing, and decision making. The communication between these heterogeneous components and the algorithms for Advanced Driver Assistance Systems and Autonomous Driving require low latency and huge memory bandwidth, bringing the Memory Wall from high-performance computing in data centers directly to our cars. In this paper we discuss these and other requirements in using DRAM for near-term autonomous driving architectures.


== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1145/3240302.3240322 http://dx.doi.org/10.1145/3240302.3240322] under the license http://www.acm.org/publications/policies/copyright_policy#Background

* [http://publica.fraunhofer.de/documents/N-534994.html http://publica.fraunhofer.de/documents/N-534994.html]

* [http://dl.acm.org/ft_gateway.cfm?id=3240322&ftid=2028120&dwn=1 http://dl.acm.org/ft_gateway.cfm?id=3240322&ftid=2028120&dwn=1],
: [http://dx.doi.org/10.1145/3240302.3240322 http://dx.doi.org/10.1145/3240302.3240322] under the license http://www.acm.org/publications/policies/copyright_policy#Background

* [https://dblp.uni-trier.de/db/conf/memsys/memsys2018.html#0001MSDWW18 https://dblp.uni-trier.de/db/conf/memsys/memsys2018.html#0001MSDWW18],
: [https://dl.acm.org/citation.cfm?id=3240322 https://dl.acm.org/citation.cfm?id=3240322],
: [https://academic.microsoft.com/#/detail/2908483391 https://academic.microsoft.com/#/detail/2908483391]