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hardware acceleration on Nvidia grid vgpu not functioning with included docker-compose.yml, had to change /etc/docker/daemon.json and docker compose yaml
Im using a gtx1650 with vgpu unlock
Nvidia-smi does not funtion under docker container and does not use gpu
Failed to initialize NVML: Unknown Error
The OS that Immich Server is running on
Ubuntu 20.04
Version of Immich Server
v1.101.0
Version of Immich Mobile App
n/a
Platform with the issue
Server
Web
Mobile
Your docker-compose.yml content
## WARNING: Make sure to use the docker-compose.yml of the current release:## https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml## The compose file on main may not be compatible with the latest release.#name: immichservices:
immich-server:
container_name: immich_serverimage: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}command: ['start.sh', 'immich']volumes:
- ${UPLOAD_LOCATION}:/usr/src/app/upload
- /etc/localtime:/etc/localtime:roenv_file:
- .envports:
- 2283:3001depends_on:
- redis
- databaserestart: alwaysimmich-microservices:
container_name: immich_microservicesimage: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}runtime: nvidiadeploy:
resources:
reservations:
devices:
- capabilities: [gpu]command: ['start.sh', 'microservices']volumes:
- ${UPLOAD_LOCATION}:/usr/src/app/upload
- /etc/localtime:/etc/localtime:roenv_file:
- .envdepends_on:
- redis
- databaserestart: alwaysimmich-machine-learning:
container_name: immich_machine_learning# For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.# Example tag: ${IMMICH_VERSION:-release}-cudaimage: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}-cudaruntime: nvidiadeploy:
resources:
reservations:
devices:
- capabilities: [gpu]volumes:
- model-cache:/cacheenv_file:
- .envrestart: alwaysredis:
container_name: immich_redisimage: registry.hub.docker.com/library/redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5restart: alwaysdatabase:
container_name: immich_postgresimage: registry.hub.docker.com/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0environment:
POSTGRES_PASSWORD: ${DB_PASSWORD}POSTGRES_USER: ${DB_USERNAME}POSTGRES_DB: ${DB_DATABASE_NAME}volumes:
- pgdata:/var/lib/postgresql/datarestart: alwaysvolumes:
pgdata:
model-cache:
Your .env content
# You can find documentation for all the supported env variables at https://immich.app/docs/install/environment-variables# The location where your uploaded files are stored
UPLOAD_LOCATION=./library
# The Immich version to use. You can pin this to a specific version like "v1.71.0"
IMMICH_VERSION=release
# Connection secret for postgres. You should change it to a random password
DB_PASSWORD=postgres
# The values below this line do not need to be changed###################################################################################
DB_HOSTNAME=immich_postgres
DB_USERNAME=postgres
DB_DATABASE_NAME=immich
REDIS_HOSTNAME=immich_redis
LOG_LEVEL=debug
This discussion was converted from issue #8588 on April 07, 2024 07:07.
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The bug
hardware acceleration on Nvidia grid vgpu not functioning with included docker-compose.yml, had to change /etc/docker/daemon.json and docker compose yaml
Im using a gtx1650 with vgpu unlock
Nvidia-smi does not funtion under docker container and does not use gpu
Failed to initialize NVML: Unknown Error
The OS that Immich Server is running on
Ubuntu 20.04
Version of Immich Server
v1.101.0
Version of Immich Mobile App
n/a
Platform with the issue
Your docker-compose.yml content
Your .env content
Reproduction steps
Additional information
fixes:
no-cgroups = false
in /etc/nvidia-container-runtime/config.toml
/etc/docker/daemon.json
{
"default-runtime": "nvidia",
"exec-opts": [
"native.cgroupdriver=cgroupfs"
],
"runtimes": {
"nvidia": {
"args": [],
"path": "nvidia-container-runtime"
}
}
}
and change in docker
deploy: resources: reservations: devices: - driver: nvidia count: 1 capabilities: - gpu - compute - video
TO
runtime: nvidia deploy: resources: reservations: devices: - capabilities: [gpu]
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