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nvidia adds eight-node cluster support for dgx spark ai models

Nvidia announced official support for eight-node DGX Spark clusters, scaling unified memory to 1 TB for local AI models.

nvidia adds eight-node cluster support for dgx spark ai models — image from NVIDIA
Image: NVIDIA

Summary

Nvidia announced official support for eight-node DGX Spark clusters, scaling unified memory to 1 TB for local AI workloads. The update includes the RoCEnante collective backend to reduce latency and NeMo Switchyard orchestration to route requests.

What changed

  • Nvidia added official support for eight-node DGX Spark clusters scaling unified memory to 1 TB.
  • A Spark-optimized collective backend called RoCEnante reduces all-reduce latency for tensor-parallel decode.
  • Nvidia NeMo Switchyard routes requests between model pools on a shared eight-node cluster.

Availability

Announced — not available yet

“Support for eight-node clusters in NVIDIA Sync is coming by the end of the year.”

Founder takeaway

Review the multi-node setup documentation if you plan to link multiple DGX Spark units for local AI workloads.

Source

NVIDIARunning Frontier-Class AI Models Across 8 NVIDIA DGX Spark Nodes | NVIDIA Technical Blog

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