Solutions

ZCube networking designs based on cluster hardware

For different build stages and cluster forms, we combine ZCube, YCOS, XOPS, and engineering services into clear, verifiable solutions.

AI cluster networking solution in a data center

Solution catalog

ZCube networking design and hardware selection

ZCube networking solutions based on cluster scale, NIC form, and switch specification.

[Dual-port NICs, 16,384 GPUs]

Dual-port ZCube @ 16,384 GPUs

A scalable ZCube architecture designed for dual-port NICs such as CX7 and CX8.

Intended audience: Dual-port NICs, or single-port NICs that support port split
Maximum scale: 51.2T switches can interconnect 16,384 GPUs
Solution details: See details
Expected value: Fewer network devices

View solution details

[Single-port NICs, 8,192 GPUs]

Single-port ZCube @ 8,192 GPUs

A scalable ZCube architecture designed for single-port NICs that can form an equivalent dual-NIC pair.

Intended audience: PCIe topology that meets affinity requirements and can form an equivalent dual-NIC pair
Maximum scale: 51.2T switches can interconnect 8,192 GPUs
Solution details: See details
Expected value: Fewer network devices and stronger fault tolerance

View solution details

[B300, 16,384 GPUs]

B300 ZCube @ 16,384 GPUs

A scalable ZCube architecture designed for B300 clusters.

Intended audience: B300 GPUs with 2x400G NICs
Maximum scale: 102.4T switches can interconnect 16,384 GPUs
Solution details: See details
Expected value: Fewer network devices

View solution details

[Multi-port NICs, 100,000 GPUs]

Multi-plane ZCube @ 100,000 GPUs

Multi-port NICs (4 ports or more) can form a multi-plane ZCube architecture and raise scalability.

Intended audience: Multi-port NICs (4 ports or more)
Maximum scale: More than 16,384 GPUs
Solution details: See details
Expected value: Fewer network devices, with stronger ZCube architecture scalability

View solution details

Start with the network

Make the next AIDC more efficient, starting with the network

Whether you are building a new cluster, upgrading an existing network, tuning performance, or deploying intelligent NetOps, we can assess how the network can unlock more effective compute power.