highperfocused/ollama
1
0
Fork 0
mirror of https://github.com/ollama/ollama.git synced 2025-04-04 09:58:31 +02:00
Code Issues Packages Projects Releases Wiki Activity

Move cgroups fix out of AMD section. (#9072)

Browse Source 
Co-authored-by: Richard Lyons <frob@cloudstaff.com>
This commit is contained in:
frob 2025-02-25 17:52:50 +01:00 committed by GitHub
parent 348b3e0983
commit 4df98f3eb5
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 4 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
docs/troubleshooting.md
View File

@ -73,6 +73,10 @@ curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.5.7 sh
If your system is configured with the "noexec" flag where Ollama stores its temporary executable files, you can specify an alternate location by setting OLLAMA_TMPDIR to a location writable by the user ollama runs as. For example OLLAMA_TMPDIR=/usr/share/ollama/
## Linux docker
If Ollama initially works on the GPU in a docker container, but then switches to running on CPU after some period of time with errors in the server log reporting GPU discovery failures, this can be resolved by disabling systemd cgroup management in Docker. Edit `/etc/docker/daemon.json` on the host and add `"exec-opts": ["native.cgroupdriver=cgroupfs"]` to the docker configuration.
## NVIDIA GPU Discovery
When Ollama starts up, it takes inventory of the GPUs present in the system to determine compatibility and how much VRAM is available. Sometimes this discovery can fail to find your GPUs. In general, running the latest driver will yield the best results.
@ -100,8 +104,6 @@ On linux, AMD GPU access typically requires `video` and/or `render` group member
When running in a container, in some Linux distributions and container runtimes, the ollama process may be unable to access the GPU. Use `ls -lnd /dev/kfd /dev/dri /dev/dri/*` on the host system to determine the **numeric** group IDs on your system, and pass additional `--group-add ...` arguments to the container so it can access the required devices. For example, in the following output `crw-rw---- 1 0 44 226, 0 Sep 16 16:55 /dev/dri/card0` the group ID column is `44`
If Ollama initially works on the GPU in a docker container, but then switches to running on CPU after some period of time with errors in the server log reporting GPU discovery failures, this can be resolved by disabling systemd cgroup management in Docker. Edit `/etc/docker/daemon.json` on the host and add `"exec-opts": ["native.cgroupdriver=cgroupfs"]` to the docker configuration.
If you are experiencing problems getting Ollama to correctly discover or use your GPU for inference, the following may help isolate the failure.
- `AMD_LOG_LEVEL=3` Enable info log levels in the AMD HIP/ROCm libraries. This can help show more detailed error codes that can help troubleshoot problems
- `OLLAMA_DEBUG=1` During GPU discovery additional information will be reported