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Home / Technology / Broadcom Unveils Powerful AI Chip to Challenge Nvidia's Dominance

Broadcom Unveils Powerful AI Chip to Challenge Nvidia's Dominance

15 Jul

•

Summary

  • Broadcom's new Tomahawk Ultra chip aims to speed up AI data processing
  • Chip can connect four times more chips than Nvidia's NVLink Switch
  • Chip uses boosted Ethernet instead of proprietary protocol
Broadcom Unveils Powerful AI Chip to Challenge Nvidia's Dominance

Broadcom's chip division has unveiled a new networking processor called the Tomahawk Ultra, which is designed to speed up artificial intelligence data processing. The chip acts as a traffic controller, allowing data to move quickly between dozens or hundreds of chips within a data center. The Tomahawk Ultra aims to compete with Nvidia's NVLink Switch chip, which serves a similar purpose. However, Broadcom's chip can connect four times the number of chips as Nvidia's offering. Additionally, the Tomahawk Ultra uses a boosted version of Ethernet, rather than a proprietary protocol, to move data between the connected chips. Both Broadcom and Nvidia's chips help data center operators and others tie together as many chips as possible within a small physical space, a technique known as "scale-up" computing. This allows software developers to access the immense computing power needed for advanced AI applications. The Tomahawk Ultra is now shipping, having been developed by Broadcom's engineering teams over the past three years.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.

FAQ

The Tomahawk Ultra is Broadcom's new networking processor designed to speed up artificial intelligence data processing.
The Tomahawk Ultra can connect four times more chips than Nvidia's rival product, and it uses a boosted Ethernet protocol instead of a proprietary one.
Both companies' chips help data center operators and others tie together as many chips as possible within a small physical space, a technique known as "scale-up" computing, to provide the immense computing power needed for advanced AI applications.

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