ProAI: An Efficient Embedded AI Hardware for Automotive Applications -- a Benchmark Study
Sven Mantowsky, Falk Heuer, Syed Saqib Bukhari, Michael Keckeisen,, Georg Schneider

TL;DR
ProAI is an automotive embedded AI hardware platform that offers high performance and power efficiency for multitask deep neural network applications, outperforming other SBCs like Jetson Nano in FPS per watt.
Contribution
This study benchmarks ProAI against other SBCs, demonstrating its superior performance and efficiency for automotive AI tasks with safety certification.
Findings
ProAI nearly doubles FPS per watt compared to a modern workstation laptop.
ProAI is almost four times more efficient than Jetson Nano.
ProAI has reserve capacity for more complex tasks based on CPU and GPU utilization.
Abstract
Development in the field of Single Board Computers (SBC) have been increasing for several years. They provide a good balance between computing performance and power consumption which is usually required for mobile platforms, like application in vehicles for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD). However, there is an ever-increasing need of more powerful and efficient SBCs which can run power intensive Deep Neural Networks (DNNs) in real-time and can also satisfy necessary functional safety requirements such as Automotive Safety Integrity Level (ASIL). ProAI is being developed by ZF mainly to run powerful and efficient applications such as multitask DNNs and on top of that it also has the required safety certification for AD. In this work, we compare and discuss state of the art SBC on the basis of power intensive multitask DNN architecture called…
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