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At the Nvidia GTC conference today, the company announced its new DRIVE Thor platform for automotive. DRIVE Thor is intended to provide a platform that can support self-driving capabilities, vehicle operations such as parking assist, as well as in-vehicle entertainment. The system benefits from the Nvidia Grace CPU and GPU capabilities that come from Hopper architecture. The DRIVE Thor platform replaces the Atlan system that was announced in April 2021. Nvidia expects that the new DRIVE Thor technology will begin to show up in automakers 2025 vehicle models.
“Autonomous vehicles are one of the most complex computing challenges of our time,” Danny Shapiro, vice president of automotive at Nvidia, said during a press briefing. “To achieve the highest possible level of safety, we need diverse and redundant sensors and algorithms, which require massive compute.”
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Why use multiple computers when you can use one?
Shapiro explained that modern vehicles use a wide array of computers, distributed throughout the vehicle.
For example, many cars today have advanced driver assistance systems, with parking assist, various monitoring cameras and multiple digital instrument clusters, alongside some form of entertainment system.
“In 2025, these functions will no longer be separate computers,” Shapiro said. “Drive Thor will enable manufacturers to efficiently consolidate these functions into a single system, reducing overall system costs.”
The goal with Drive Thor is to provide automakers with the compute headroom and flexibility to build software-defined autonomous vehicles that are continuously upgradable through secure over the air updates.
Thor’s power isn’t a hammer, it’s an inference transformer
The mythical Norse God Thor relied on his hammer Mjölnir, but there’s nothing mystical about what brings power to Nvidia’s DRIVE Thor platform.
According to Shapiro, Thor is the first automotive chip to incorporate an inference transformer engine. A transformer is an AI technique that can quickly identify relationships between objects and is particularly useful for computer vision.
“Thor can accelerate inference performance of transformers, which is vital for supporting the massive and complex AI workloads in self-driving vehicles,” Shapiro said.
Going a step further, the way the system can handle multiple operations security in a real-time approach is with a capability called multi-compute domain isolation. Shapiro explained that the capability enables concurrent time-critical processes to run without interruption. Additionally, on one computer, a vehicle manufacturer can simultaneously run Linux, QNX and Android operating systems and applications.
Learning to self-drive with Drive SIM
The new DRIVE Thor system is one part of Nvidia’s overall automotive efforts.
Another key part is the Drive Sim technology, which can help to train self-driving vehicles, that will benefit from the Thor chip. Shapiro explained that Drive Sim uses a neural engine that can recreate and replay road situations in a digital twin model.
“Essentially, our researchers have developed an AI pipeline that can reconstruct a 3D scene from recorded sensor data,” Shapiro said. “At the end of the day, though, we’re creating a digital twin of the car and a digital twin of the environment.”
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