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Nvidia adds memory-enforced GPU sharing in Kubernetes with CUDA 13.4

Nvidia released CUDA 13.4 with memory-enforced GPU sharing in Kubernetes via the open-source GPU Fractioning Operator and KAI Scheduler.

Nvidia adds memory-enforced GPU sharing in Kubernetes with CUDA 13.4 — image from NVIDIA
Image: NVIDIA

Summary

Nvidia released CUDA 13.4, introducing transparent memory boundary enforcement for shared GPUs in Kubernetes. The update works with the GPU Fractioning Operator and KAI Scheduler to set memory limits, guaranteed minimums, and compute modes.

What changed

  • GPU Fractioning Operator is a new open-source Kubernetes operator hosted under the KAI Scheduler organization on GitHub.
  • CUDA 13.4 introduces a memory boundary enforcement that is transparent to applications, offering exact memory amounts and guaranteed minimums.
  • KAI Scheduler v0.18.0 integrates with GPU Fractioning through its NvFractions GPU-sharing mode using Pod annotations.
  • Administrators can enable NvFractions during KAI Scheduler installation with a Helm flag.

Availability

Available now

“CUDA 13.4 now enforces a memory boundary that is transparent to the application with a new time-sharing mode, alongside the compute sharing mode (sm-sharing) that already existed in MPS.”

Founder takeaway

If you run AI workloads on Kubernetes and want to share GPUs across multiple containers with hard memory limits, test the KAI Scheduler v0.18.0 and GPU Fractioning Operator with CUDA 13.4.

Source

NVIDIAMemory-Enforced GPU Sharing in Kubernetes with NVIDIA CUDA 13.4 | NVIDIA Technical Blog

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