Could Nvidia’s Thor chip rule automotive AI?



Nvidia has announced its DRIVE Thor platform for autonomous vehicles at its GTC 2022 conference. The platform is intended to provide a platform that can support self-driving capabilities, vehicle operations such as parking assist, and in-vehicle entertainment. Nvidia expects the technology will begin to show up in automakers 2025 vehicle models. “Autonomous vehicles are one of the most complex computing challenges of our time,” said Danny Shapiro, Vice President of Automotive at Nvidia


Nvidiaは、GTC 2022会議で自動運転車用のドライブトールプラットフォームを発表しました。このプラットフォームは、自動運転機能、駐車アシストなどの車両運用、車両内エンターテイメントをサポートできるプラットフォームを提供することを目的としています。Nvidiaは、このテクノロジーが自動車メーカー2025車両モデルに登場することを期待しています。「自動運転車は、私たちの時代の最も複雑なコンピューティングの課題の1つです」と、NvidiaのAutomotiveの副社長であるDanny Shapiro氏は述べています。


As cars get increasingly smarter and self-driving autonomous vehicles continue to be developed there is an obvious need for more computing power.


Maybe even the power of a Norse god of thunder.


At the Nvidia GTC conference today, the company announced its new DRIVE Thor platform for automotive.

本日、NVIDIA GTC会議で、同社は自動車用の新しいドライブトールプラットフォームを発表しました。

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.

Drive Thorは、自動運転機能、駐車場などの車両運用、および車両内エンターテイメントをサポートできるプラットフォームを提供することを目的としています。

The system benefits from the Nvidia Grace CPU and GPU capabilities that come from Hopper architecture.

このシステムは、ホッパーアーキテクチャから生じるNVIDIA Grace CPUおよびGPU機能の恩恵を受けています。

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.

Drive Thorプラットフォームは、2021年4月に発表されたAtlanシステムに取って代わります。Nvidiaは、新しいドライブThorテクノロジーが自動車メーカー2025車両モデルに登場し始めると予想しています。

“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.

「自動運転車は、私たちの時代の最も複雑なコンピューティングの課題の1つです」と、Nvidiaの自動車担当副社長であるDanny Shapiroは、記者会見の中で述べています。

“To achieve the highest possible level of safety, we need diverse and redundant sensors and algorithms, which require massive compute.” [Follow along with VB’s ongoing Nvidia GTC 2022 coverage »] MetaBeat 2022 MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.

「可能な限り最高レベルの安全性を達成するには、多様で冗長なセンサーとアルゴリズムが必要です。これには、大規模な計算が必要です。」[VBの進行中のNVIDIA GTC 2022カバレッジに従ってください»] Metabeat 2022 Metabeatは、10月4日にカリフォルニア州サンフランシスコで、すべての業界がコミュニケーションとビジネスを行う方法をメタバーステクノロジーがどのように変換するかについてガイダンスを提供するために、Sound Leadleを集めます。

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.

「Drive Thorは、製造業者がこれらの機能を効率的に単一のシステムに統合し、システム全体のコストを削減できるようになります。」Drive Thorの目標は、自動車メーカーにコンピューティングヘッドルームと柔軟性を提供することです。これは、Secure Over Air Updatesを通じて継続的にアップグレード可能なソフトウェア定義の自動運転車を構築することです。

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.


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.

新しいドライブトールシステムは、Nvidiaの全体的な自動車の取り組みの一部です。もう1つの重要な部分は、Thorチップの恩恵を受ける自動運転車の訓練に役立つDrive SIMテクノロジーです。

Shapiro explained that Drive Sim uses a neural engine that can recreate and replay road situations in a digital twin model.

Shapiroは、Drive Simは、デジタルツインモデルで道路の状況を再現および再生できるニューラルエンジンを使用すると説明しました。

“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.” VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.