Defining the Hardware Backbone of Autonomous Driving

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Discover the future of computing for autonomous vehicles at Hardware.AD!
Join now to explore cutting-edge hardware and computing technologies that enable autonomous driving. Discuss best-in-class hardware for AI applications and real-time AI processing, Automated Driving HPC, automotive SoCs, zonal networking, sensor fusion, power efficiency, and safety-critical compute for autonomous vehicles with leading engineers, architects, and IT infrastructure practitioners.
Be part of the innovation driving the future of AD systems. See you in Berlin!

"Continuous improvement is better than delayed perfection."

Mark Twain (1835 - 1910) American writer

HIGHLIGHTS

KEY TOPICS

Automotive SoCs: What compute architectures are best suited for handling high-bandwidth sensor fusion in real-time autonomous driving?

AI Accelerators & NPUs: How can NPUs and AI accelerators improve latency and power efficiency for deep-learning models in autonomous perception?

Memory & Storage: How can high-speed, non-volatile storage solutions keep up with the massive data logging requirements of autonomous vehicle fleets?

Zonal Controllers & Networking: What networking protocols and architectures enable deterministic, low-latency communication between zonal controllers and central compute units?

AI Accelerators & NPUs + Power Management: How can AI model compression and specialized compute units reduce power consumption without compromising real-time inference accuracy?

Zonal Controllers & Networking: What are the biggest integration challenges when transitioning from a distributed ECU architecture to a zonal E/E architecture?

Hardware and Software Co-design: How do hardware and software co-design approaches impact the reliability and certification of safety-critical autonomous driving systems?

Safety-Critical Compute: How can fail-operational safety architectures be implemented to ensure ASIL-D compliance in centralized compute systems?

Sensors (LiDAR, Radar, Cameras): What are the key trade-offs between LiDAR, radar, and camera-based perception for Level 4 and Level 5 autonomy?

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WHAT OUR ATTENDEES SAY

NetApp_BP-2022 Solutions Architect – Automotive & Edge

The event was very successful to us and we were able to have fruitful conversations and promising follow-ups.
Bosch_Speaker-2022 Embedded Systems Engineer – Automotive SoC


From a professional standpoint, the conference was a success. Networking, sharing of insights and opinions was beneficial. Setup and your organization was excellent.
Luxoft_Del-2022 Technical Lead – ECU Consolidation Projects


Perfect networking experience.
Incredibuild_BP-2022 CI/CD Acceleration Specialist
Very successful event with lots of interesting discussions and knowledge sharing. We learned a lot and made some great connections; we will be happy to join such future events.
Mercedes_Sp-2022 Hardware Engineer Very valuable time and good to meet the community. Also the co-location with the Agile Automotive Engineering Summit was advantageous. Arrrival_Sp-2022 Design Verification Engineer
Very valuable time and good to meet the community. Also the co-location with the Agile Automotive Engineering Summit was advantageous.
Fraunhofer-IESE_Del-2022 Systems Engineer - Cloud-native Automotive Software
A really good and educational experience with great people.

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