Tag: Blackwell Architecture

  • NVIDIA Targets Tesla with Thor Chip and 4D Driving Simulator

    NVIDIA Targets Tesla with Thor Chip and 4D Driving Simulator

    NVIDIA revealed a brand new automotive chip called Thor during its CES 2025 keynote presentation. This chip is built on the Blackwell platform and boasts 20 times more processing power compared to the current generation of automotive chips. It is designed to aid in virtual simulations for autonomous vehicles.

    New Approach to Autonomous Driving

    Rather than relying on logging millions of miles like Tesla does with its Full Self-Driving (FSD) feature, NVIDIA is investing in a synthetic world simulator named Cosmos. This innovative tool will complement the three chips that are essential for AI in autonomous vehicles.

    The Cosmos platform comprises cutting-edge generative world foundation models, tokenizers, guardrails, and a speedy video processing pipeline. These components aim to enhance the creation of physical AI systems, including autonomous vehicles and robots, according to NVIDIA.

    Upgraded AI Processing Power

    In addition to the new simulator, NVIDIA has upgraded its AI processing chips with the Thor automotive chip, which is the successor to the Orin line. The Thor chip features the Blackwell architecture, similar to the recently launched GeForce RTX 5070 gaming card, which NVIDIA claims can match the performance of an RTX 4090 at a price of $549.

    Thor provides 1,000 TFLOPS of powerful AI computing and offers roughly 20 times the AI capability of its predecessor. Its efficiency is crucial as it helps reduce the overall costs of System on Chip (SoC) in vehicles that integrate both autonomous driving and infotainment systems.

    Flexible Architecture for Car Manufacturers

    Automakers and developers of autonomous vehicle solutions can allocate the 1,000 TFLOPS of computing power between self-driving tasks and infotainment systems, making the architecture highly adaptable. According to ARM, "When used in level 3 or higher autonomous driving scenarios, a single Nvidia DRIVE AGX Thor can replicate the functionality of multiple advanced devices currently found in vehicles, leading to considerable advantages in performance for car manufacturers."

    NVIDIA also highlighted multiple safety and security certifications for its new Thor-based Drive AGX platform, including recognition from the ANSI National Accreditation Board and TÜV Rheinland.

    Partnerships and Innovative Simulation Features

    NVIDIA has already partnered with various automakers and autonomous driving solution providers such as Mercedes and Nuro. They are utilizing NVIDIA’s self-driving chips and Cosmos simulation software, which includes features like OmniMap that combines mapping and satellite imagery to create 3D environments that are drivable. The Neural Reconstruction Engine generates high-fidelity 4D simulation environments from AV sensor data. Additionally, Edify 3DS can search for existing scenes or create 3D objects based on text or image prompts, transforming scenes in NVIDIA Omniverse that are grounded in 4D. Finally, Cosmos is capable of generating countless variations of driving scenarios using simple text prompts.

    However, it is yet to be determined if the Cosmos simulator will enable traditional automakers and electric vehicle startups to bridge the gap with Tesla’s FSD solution, which relies on extensive real-world driving data to enhance its AI algorithms.

    Source: Link

  • Nvidia Developing AI GPU with 144GB HBM3E Memory

    Nvidia Developing AI GPU with 144GB HBM3E Memory

    Nvidia is gearing up for the release of its next-generation B100 and B200 GPUs, which are built on the Blackwell architecture, as reported by TrendForce. These advanced GPUs are slated to launch in the latter half of this year and will cater primarily to Cloud Service Providers (CSPs) for their cloud computing needs. Additionally, Nvidia plans to introduce a simplified version, the B200A, aimed at OEM enterprise customers with edge AI requirements.

    Tight Packaging Capacity

    TSMC’s CoWoS-L packaging capacity, utilized by the B200 series, remains limited. The B200A will transition to the more straightforward CoWoS-S packaging technology to better meet the needs of Cloud Service Providers.

    B200A Technical Specifications

    Although the full technical specifications of the B200A are not yet detailed, it is confirmed that the HBM3E memory capacity will be reduced from 192GB to 144GB. Additionally, the number of memory chip layers will be cut from eight to four, although the capacity of each individual chip will increase from 24GB to 36GB.


    Nvidia Developing AI GPU with 144GB HBM3E Memory

    Power Consumption and Cooling

    The B200A will consume less power than the B200 GPUs and will not require liquid cooling, making it easier to install with an air cooling system. This new GPU model is expected to be available to OEM manufacturers by the second quarter of next year.

    Supply chain surveys indicate that Nvidia’s primary high-end GPU shipments in 2024 will be based on the Hopper platform, with H100 and H200 targeting the North American market and H20 for the Chinese market. Since the B200A will be released around the second quarter of 2025, it is anticipated not to overlap with the H200, which is scheduled to arrive on or after the third quarter.

    (Source: TrendForce)