Introducing Xavier, the NVIDIA AI Supercomputer for the Future of Autonomous Transportation

At the inaugural GPU Technology Conference Europe, NVIDIA CEO Jen-Hsun Huang today unveiled Xavier, our all-new AI supercomputer, designed for use in self-driving cars.

“This is the greatest SoC endeavor I have ever known, and we have been building chips for a very long time,” Huang said to the conference’s 1,600 attendees.

Xavier is a complete system-on-chip (SoC), integrating a new GPU architecture called Volta, a custom 8 core CPU architecture, and a new computer vision accelerator. The processor will deliver 20 TOPS (trillion operations per second) of performance, while consuming only 20 watts of power. As the brain of a self-driving car, Xavier is designed to be compliant with critical automotive standards, such as the ISO 26262 functional safety specification.

At the inaugural GPU Technology Conference Europe, NVIDIA CEO Jen-Hsun Huang today unveiled Xavier, our all-new AI supercomputer, designed for use in self-driving cars.
At the inaugural GPU Technology Conference Europe, NVIDIA CEO Jen-Hsun Huang today unveiled Xavier, our all-new AI supercomputer, designed for use in self-driving cars.

Packed with 7 billion transistors, and manufactured using cutting-edge 16nm FinFET process technology, a single Xavier AI processor will be able to replace today’s DRIVE PX 2 configured with dual mobile SoCs and dual discrete GPUs — at a fraction of the power consumption.

Because autonomous driving is an incredibly compute-intense process, the need for an efficient AI processor is paramount. Xavier will bring self-driving car technology to automakers, tier 1 suppliers, startups and R&D organizations that are building autonomous vehicles, whether cars, trucks, shuttles or taxis.

Xavier samples will be available the fourth quarter of 2017 to automakers, tier 1 suppliers, startups and research institutions who are developing self-driving cars.

 

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  • Mexor

    What is a computer vision accelerator?

  • Sykobee

    Probably a dedicated DSP (e.g., Tensilica) that does some stuff before the visual data hits the GPU, improving efficiency.

  • Mexor

    Thanks. I should have been more specific. “What is the computer vision accelerator?” As in, specifically, what does NVIDIA mean by it? The reason I ask is because it seems to take up a large number of transistors on this SOC, unless I’m missing something. Does it run CUDA code? Will it need to be programmed for differently?

  • https://google.com/+RenaudLepage Renaud Lepage

    The only thing I want to know is, when can I get my hands on a tablet or AndroidTV that’s powered by Xavier.

  • Mehmed

    So Between October and December 2017 we will see this little guy.
    Great.