NVIDIA introduced NVIDIA DRIVE Thor, its next-generation centralized computer for safe and secure autonomous vehicles. DRIVE Thor, which achieves up to 2,000 teraflops of performance, unifies intelligent functions—including automated and assisted driving, parking, driver and occupant monitoring, digital instrument cluster, in-vehicle infotainment (IVI) and rear-seat entertainment—into a single architecture for greater efficiency and lower overall system cost.

DRIVE Thor replaces NVIDIA DRIVE Atlan (earlier post) and will be the follow-on to DRIVE Orin, which is currently in production and delivers 254 TOPS of performance.

The next-generation superchip incorporates the advanced AI capabilities first introduced in the NVIDIA Hopper Multi-Instance GPU architecture, along with the NVIDIA Grace CPU and NVIDIA Ada Lovelace GPU. DRIVE Thor with MIG support for graphics and compute uniquely enables IVI and advanced driver-assistance systems to run domain isolation, which allows concurrent time-critical processes to run without interruption.

Available for automakers’ 2025 models, it will accelerate production roadmaps by bringing higher performance and advanced features to market in the same timeline.

Signaling the transportation industry’s support for this new supercomputing architecture, Geely-owned automaker ZEEKR announced it will integrate DRIVE Thor on its centralized vehicle computer for its next-generation intelligent electric vehicles, starting production in early 2025.

DRIVE Thor supports multi-domain computing, isolating functions for automated driving and IVI. Typically, dozens of electric control units are distributed throughout a vehicle to power individual functions. With DRIVE Thor, manufacturers can efficiently consolidate many functions on a single system-on-a-chip (SoC), which eases supply constraints and simplifies vehicle-design development, resulting in significantly lower cost, less weight and fewer cables.

DRIVE Thor is the first AV platform to incorporate an inference transformer engine, a new component of the Tensor Cores within NVIDIA GPUs. With this engine, DRIVE Thor can accelerate inference performance of transformer deep neural networks by up to 9x, which is paramount for supporting the massive and complex AI workloads associated with self driving.

Another advantage of DRIVE Thor is its 8-bit floating point (FP8) capability. Typically, developers lose neural-network accuracy when moving from 32-bit FP data to 8-bit integer format. DRIVE Thor features 2,000 teraflops of FP8 precision, allowing the transition to 8-bit without sacrificing accuracy.

The new superchip also uses the latest NVLink-C2C chip interconnect technology, while running multiple operating systems. The advantage of the NVLink-C2C is its ability to share, schedule and distribute work across the link with minimal overhead. This equips automakers with the compute headroom and flexibility to build software-defined vehicles that are continuously upgradeable through secure, over-the-air software updates.

DRIVE Thor is designed for the highest levels of functional safety. NVIDIA has invested more than 15,000 engineering years into safety across its full stack. NVIDIA says it is the only company with a unified safety approach across its entire system, from the data center to the fleet.

The DRIVE Thor SoC and AGX board are developed to comply with ISO 26262 standards. The software stack is designed for both ISO 26262 and ASPICE compliance. The Thor SoC and software are also designed and produced in alignment with ISO 21434, which provides the pathway for compliance with regulatory security such as UNECE Regulation 155.

Existing DRIVE Orin customers can take advantage of the platform’s scalable architecture to transition current development efforts to DRIVE Thor. Developers can reap the benefits of their software investments across multiple product generations as they design for future production roadmaps.

Posted on 21 September 2022 in AI, Autonomous driving, Market Background, Microprocessors and controls | Permalink | Comments (1)

Perhaps FSD AI software and hardware design is more important than outright TOPS, FLOPS etc. But it's interesting to compare this race in raw compute power: https://cleantechnica.com/2019/06/15/teslas-new-hw3-self-driving-computer-its-a-beast-cleantechnica-deep-dive/

Posted by: GdB | 23 September 2022 at 01:15 PM

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