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AMD 7900 XT GPU Stops Working in Ollama + Stuck at 100% Usage After Use

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Hi everyone,

I’ve been running Ollama in a Docker container on Unraid (version 6.12.15) using my AMD 7900 XT GPU, but I’m encountering a frustrating issue. Initially, the GPU works fine and is recognized by Ollama. However, after some time (or after processing a certain amount of data), the GPU experiences a hard crash and Ollama defaults back to CPU usage. Additionally, after running an AI model, the GPU usage remains at 100% indefinitely, even when no processes are running.

 

My Setup:

Unraid Version: 6.12.15

Motherboard: MSI PRO Z790-P WIFI DDR4

CPU: Intel Core i7-12700K

Primary GPU: AMD 7900 XT (also tested with 7800 XT, same issue)

Docker Container:

Ollama (ollama/ollama:rocm)

AMD Vendor Reset Plugin Installed

Docker Extra Parameters:

--device=/dev/kfd

 

What’s Happening:

When I first start the container, the GPU works fine, and it’s recognized properly. Models load and process on the GPU as expected.

After some time (or after processing a heavy model), the GPU crashes, and the container switches to CPU processing.

The syslog shows errors like:

[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3 [drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue amdgpu 0000:03:00.0: amdgpu: GPU mode1 reset amdgpu 0000:03:00.0: amdgpu: VRAM is lost due to GPU reset!

After the crash, the GPU usage stays at 100% indefinitely, even when the container is stopped.

I have the AMD Vendor Reset Plugin installed, but it doesn’t seem to resolve the high usage issue or prevent the crashes.

Restarting the container does not fix the issue — I have to either reboot Unraid or physically remove power from the system to reset the GPU.

 

What I’ve Tried:

Passed the GPU to the container using:

--device=/dev/kfd

Added the --runtime=rocm flag to ensure ROCm support.

Tried switching to an AMD 7800 XT to test if it was a hardware issue — same results.

Attempted to use the AMD Vendor Reset Plugin, but the GPU still locks at 100% usage until I physically power off the machine.

Manually stopped the container after heavy processing, but the GPU remains locked at 100% utilization.

 

Additional Notes:

This behavior happens regardless of the AI model being used in Ollama.

Even after stopping the container, the GPU remains locked at 100% usage until a full system reboot.

I’m wondering if this is a ROCm driver issue or something related to Unraid’s power management.

 

My Questions:

Has anyone else experienced GPU resets with AMD cards while using Ollama or other AI workloads in Docker?

Is there a way to force the GPU to reset using the AMD Vendor Reset Plugin without rebooting Unraid?

Is there a known fix for the GPU staying at 100% usage indefinitely after use?

Should I consider switching to a different container or driver to avoid these constant crashes?

 

I’m hoping someone here has a solution since my goal was to use the 7900 XT for heavy AI workloads, but it’s practically unusable in its current state. Any help would be greatly appreciated!

syslog.txt

  • 3 months later...

Hello,

Did you find a solution to this topic?

I'm having the exact same issue you're having.

In the Ollama logs, there is a GPU Hang message prior to this.

  • 1 month later...

I have also experienced the same problem but I am unsure of why this is happening too.

I am on Unraid 7.1 and still having this problem.

I have tried a bunch of different parameters in ollama and thats not helping at all.

Im considering a rollback of ollama version to see if that will help? It used to work fine.

  • 3 months later...

Any progress on this?

Same problem here, GPU is detected, models load and start, but ends up with

HW Exception by GPU node-1 (Agent handle: 0x560fbac744f0) reason :GPU Hang

  • 2 months later...

Same issue on a RX580. Ollama can detect it, but will enter hang state with the first prompt. Not sure what logs I could share, but happy to help troubleshoot the problem if anyone knows how to go about it.

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