Beyond HMI and graphics - why GPUs matter for autonomy

By _Imagination Blog

May 9, 2022

Autonomous vehicle (AV) development is gaining momentum, with major players such as Renesas, driving innovation for Level 2+ and Level 3 solutions, part of the industry-standard six levels of autonomous driving. The new R-Car V4H SoC from Renesas brings significantly more performance in deep learning, enabling fast image recognition and processing of surroundings via automotive sensors (cameras, radar and lidar).

Cities are also preparing for the autonomous revolution through laws, regulations, and infrastructures. Germany, Japan and South Korea have become the first countries to support a legal basis for Level 3 driving solutions – with manufacturers such as Mercedes-Benz racing for international validation to start production on Level 3 vehicles.

Even at these lower levels of autonomy cars can generate 25GB of data per hour from a variety of sensors, so high-performance, low-power SoC are an essential piece of the puzzle. When it comes to full AVs, the automotive SoC represents the foundation on which manufacturers build their solutions and dedicated AI accelerators inside of these are the traditional component associated with powering AI for autonomous driving. However, what some don’t appreciate is that the conventional GPUs can also play a vital role in processing sensor input as their architecture is designed with parallel computing in mind.

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