Mobileye’s EyeQ Ultra Targets Consumer AVs
25 January, 2022
Leveraging 5 nanometer process technology, EyeQ Ultra can handle all the needs of Level 4 autonomous driving. Prof. Amnon Shashua: “Consumer AV is the end game for the industry”
Mobileye’s new EyeQ Ultra system-on-chip (SoC) for autonomous driving is optimized for low cost vehicles . The company said that at only 176 TOPS, it can handle all the needs and applications of Level 4 (L4) autonomous driving without the power consumption and costs related to integrating multiple SoCs together. “Consumer AV is the end game for the industry,” said Prof. Amnon Shashua, Mobileye president and CEO. “By developing the entire self-driving solution – from hardware and software to mapping and service models – we can reach the performance-and-cost optimization that will make consumer AVs a reality.”
EyeQ Ultra packs the performance of 10 EyeQ5s in a single package. Leveraging 5 nanometer process technology, EyeQ Ultra can handle all the needs and applications of Level 4 (L4) autonomous driving without the power consumption and costs related to integrating multiple SoCs together. Like its EyeQ predecessors, EyeQ Ultra has been engineered in tandem with Mobileye software, enabling extreme power efficiency with zero performance sacrifices.
First silicon is expected at the end of 2023
EyeQ Ultra (photo above) utilizes an array of four classes of proprietary accelerators, each built for a specific task. They are paired with additional CPU cores, ISPs (Image Signal Processors) and GPUs, and is capable of processing input from two sensing subsystems – one camera-only system and the other radar and lidar combined – as well as the vehicle’s central computing system, the high-definition map and driving policy software.
First silicon for the EyeQ Ultra SoC is expected at the end of 2023, with full automotive-grade production in 2025. The new AV solution is supported by some 200 petabytes dataset that helps the AV and computer vision system handle edge cases and thereby achieve the very high mean time between failure (MTBF) needed in self-driving vehicles.
The compute engine relies on 500,000 peak CPU cores at the AWS cloud to crunch 50 million datasets monthly – the equivalent to 100 petabytes being processed every month related to 500,000 hours of driving. “The sheer size of Mobileye’s dataset makes the company one of AWS’s largest customers by volume stored globally.”
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