Nvidia's plans for the data processor unit

When Nvidia’s CEO, Jensen Huang, discussed its latest 400-gigabit BlueField-3 data processing unit (DPU) at the company’s 2021 GTC event, he also detailed its successor.

Companies rarely discuss chip specifications two generations ahead; the BlueField-3 only begins sampling next quarter.

BlueField-3 die. Source: Nvidia

The BlueField-4 will advance Nvidia’s DPU family. It will double again the traffic throughput to 800 gigabits-per-second (Gbps) and almost quadruple the BlueField-3’s integer processing performance.

But one metric cited stood out. The BlueField-4 will increase by nearly 1000x the number of terabit operators-per-second (TOPS) performed: 1,000 TOPS compared to the BlueField-3’s 1.5 TOPS.

Huang said artificial intelligence (AI) technologies will be added to the BlueField-4, implying that the massively parallel hardware used for Nvidia’s graphics processor units (GPUs) are to be grafted onto its next-but-one DPU.

Why add AI acceleration? And will it change the DPU, a relatively new processor class?

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Compute vendors set to drive optical I/O innovation

Part 2: Data centre and high-performance computing trends

Professor Vladimir Stojanovic has an engaging mix of roles.

When he is not a professor of electrical engineering and computer science at the University of California, Berkeley, he is the chief architect at optical interconnect start-up, Ayar Labs.

Professor Vladimir Stojanovic

Until recently Stojanovic spent four days each week at Ayar Labs. But last year, more of his week was spent at Berkeley.

Stojanovic is a co-author of a 2015 Nature paper that detailed a monolithic electronic-photonics technology. The paper described a technological first: how a RISC-V processor communicated with the outside world using optical rather than electronic interfaces. 

It is this technology that led to the founding of Ayar Labs.

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