Latest / Big Iron Radio / Homelab Brief - Offloading Immich Machine Learning to a GPU Box
Transcript
- 0:02Welcome to the Homelab Brief from Big Iron.
- 0:06Today, moving Imich's machine learning work,
- 0:09clip search, and face recognition off your main server
- 0:13onto a dedicated GPU box.
- 0:16Quick note, this is an AI voice
- 0:18drawn from a Big Iron guide.
- 0:20Links below.
- 0:22The good news is how easy this is.
- 0:24You split the Imich machine learning container
- 0:27onto a separate GPU box and point Imich at it
- 0:30with one environment variable Imich machine learning URL.
- 0:34It's officially supported, it's a single setting,
- 0:37and honestly most installs never bother
- 0:40so this is a quiet, big win.
- 0:43Now the gotcha that surprises people.
- 0:45On a single small GPU, set machine learning workers to one.
- 0:50It feels wrong more workers should mean more parallelism,
- 0:53but instead each worker tries to load its own duplicate copy
- 0:56of the model into VRAM, and they OOM each other.
- 1:00One worker, one model, no crash.
- 1:03Tune the model time to live for your situation.
- 1:06If the GPU box is dedicated to Imich,
- 1:09set machine learning model TTL high, or to zero,
- 1:13and just keep the model resident.
- 1:15If the box is shared with other inference workloads,
- 1:18set it low a few hundred seconds,
- 1:20so the model unloads and frees VRAM between bursts.
- 1:24On networking, resist the urge to get fancy.
- 1:27Plain bridge networking with a published port is the right default.
- 1:31Skip Maclin, skip host networking unless you already have a specific reason they
- 1:36add failure modes you don't need here.
- 1:39And one operational sharp edge to know.
- 1:41If that GPU box goes to sleep,
- 1:44queued jobs fail and just sit there in a failed state.
- 1:47There's no automatic fallback and no re-queue.
- 1:50So keep the ML box awake or plan to re-trigger.
- 1:54The full setup's in the show notes.
- 1:56That's your brief.
- 1:57That's your brief.
- 1:57That's your brief.