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HomeHardware TutorialHardware NewsNVIDIA launches next-generation X800 series network switches supporting 800Gb/s ultra-high-end end-to-end throughput

NVIDIA launches next-generation X800 series network switches supporting 800Gb/s ultra-high-end end-to-end throughput

Mar 20, 2024 pm 04:06 PM
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According to IT House reports, at today’s GTC Developer Conference, NVIDIA launched a new generation of X800 network switch platform. These platforms are the first in the industry to achieve 800Gb/s end-to-end throughput, further pushing the limits of network performance for artificial intelligence and computing workloads.

英伟达推出新一代 X800 系列网络交换机,支持 800Gb / s 超高端到端吞吐量

Specifically, the X800 series includes two platforms: Quantum-X800 for InfiniBand and Spectrum-X800 for standard Ethernet.

The Quantum-X800 platform is designed to provide the highest performance for artificial intelligence infrastructure, including the NVIDIA Quantum Q3400 switch (IT House Note: can provide 144 800Gbps ports) and the ConnectX-8 SuperNIC device-side smart network card.

Compared with the previous generation product, the total bandwidth of Quantum-X800 has increased by 5 times, and the in-network computing power using NVIDIA SHARPv4x protocol has also increased by 9 times, reaching 14.4 Tflops.

Spectrum-X800, on the other hand, targets artificial intelligence, cloud and enterprise infrastructure scenarios, and includes Spectrum SN5600 switches that provide 64 800Gbps ports and BlueField -3 SuperNIC device-side high-performance network cards.

NVIDIA claims that Spectrum-X800 accelerates the running of artificial intelligence workloads and is designed for cloud computing multi-tenant environments, ensuring performance isolation between each tenant's AI workloads to maintain optimal and consistent performance performance level, improving cloud service quality and customer satisfaction.

NVIDIA also provides a complete set of software support that can improve the communication efficiency of GPU parallel computing and facilitate customers to optimize the performance of large models with trillions of parameters.

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