Autonomous Driving Development Platform for Data Driven Engineering and Testing
AI/Machine Learning/Deep Learning
Big Data Analytics
TimeTuesday, June 18th2:07pm - 2:30pm CEST
DescriptionThis talk provides insights into autonomous driving development platforms. It covers the whole process to support the development of intelligent functionalities for autonomous driving. T-Systems/Cray will present its portfolio of platform technologies and services to support this ecosystem.
Platforms for developing AI based safety critical devices and functions need specific software and hardware optimizations. Because of the shift from code to data driven engineering and the increasing need for virtual and physical tests, co-design of workloads and underlying platform becomes a necessity.
Short development cycles reduce space for any kind of data movements or overheads. The capability to instantly analyze data on the edge or near a testbed becomes more important. Large test data sets from distributed field tests must be analyzed in a geo-federated way.
Not only bridging geo-distance but also system borders becomes crucial to efficiently run simulations without duplicating data and orchestration code. Re-simulation has to be seamless from numerical to physical simulations on HIL’s and testbeds. Orchestration, workload management and APIs provide the basis for such an integrated development and simulation platform. Seamlessly embedding development and test pipelines by optimizing data flows reduces time and cost to get results.
System Architect Technology & Innovation bei T-Systems. Senior Solution Architect