Should I struggle through constant crashes to get my 7900gre with 16gb of vram working, possibly through the headache of ONNX? Can anyone report their own success or offer advice? AMD on linux is generally lovely, SD with AMD on linux, not so much. It was much better with my RTX2080 on linux but gaming was horrible with NVIDIA drivers. I feel I could do more with the 16GB AMD card if stability wasn’t so bad. I currently have both cards running to the horror of my PSU. A1111 does NOT want to see the NVIDIA card, only the AMD. Something about the version of pytorch? More work to be done there.

  • Having a much better time back on Cinnamon default instead of Wayland. Oops!

** It heard me. Crashed again on an x/y plot but due to being away from Wayland I was able to see the terminal dump: amdgpu thermal overload! shutdown initiated! That’ll do it! Finally something easy to fix. Wonder why thermal throttling isn’t kicking in to control runaway? Will stress it once more and clock the temps this time.

Temps were exceeding 115C, phew! No idea why the default amdgpu driver has no fan control but they’re ripping like they should now. Monitoring temps has restored system stability. Using multiple amd/nvidia dedicated venv folders and careful driver choice/installation were the keys to multigpu success.

    • abcdqfr@lemmy.worldOP
      2·
      27 days ago

      I might take the docker route for the ease of troubleshooting if nothing else. So very sick of hard system freezes/crashes while kludging through the troubleshooting process. Any words of wisdom?

      • electricprism@lemmy.ml
        2·
        26 days ago

        Assume I’m an amature and bad at this ;P

        In any case you might try a docker-compose.yml

        version: "3.8"
# Compose file build variables set in .env
services:
  supervisor:
    platform: linux/amd64
    build:
      context: ./build
      args:
        PYTHON_VERSION: ${PYTHON_VERSION:-3.10}
        PYTORCH_VERSION: ${PYTORCH_VERSION:-2.2.2}
        WEBUI_TAG: ${WEBUI_TAG:-}
        IMAGE_BASE: ${IMAGE_BASE:-ghcr.io/ai-dock/python:${PYTHON_VERSION:-3.10}-cuda-11.8.0-base-22.04}
      tags:
        - "ghcr.io/ai-dock/stable-diffusion-webui:${IMAGE_TAG:-cuda-11.8.0-base-22.04}"
        
    image: ghcr.io/ai-dock/stable-diffusion-webui:${IMAGE_TAG:-cuda-11.8.0-base-22.04}
    
    devices:
      - "/dev/dri:/dev/dri"
      # For AMD GPU
      #- "/dev/kfd:/dev/kfd"
    
    volumes:
      # Workspace
      - ./workspace:${WORKSPACE:-/workspace/}:rshared
      # You can share /workspace/storage with other non-WEBUI containers. See README
      #- /path/to/common_storage:${WORKSPACE:-/workspace/}storage/:rshared
      # Will echo to root-owned authorized_keys file;
      # Avoids changing local file owner
      - ./config/authorized_keys:/root/.ssh/authorized_keys_mount
      - ./config/provisioning/default.sh:/opt/ai-dock/bin/provisioning.sh
    
    ports:
        # SSH available on host machine port 2222 to avoid conflict. Change to suit
        - ${SSH_PORT_HOST:-2222}:${SSH_PORT_LOCAL:-22}
        # Caddy port for service portal
        - ${SERVICEPORTAL_PORT_HOST:-1111}:${SERVICEPORTAL_PORT_HOST:-1111}
        # WEBUI web interface
        - ${WEBUI_PORT_HOST:-7860}:${WEBUI_PORT_HOST:-7860}
        # Jupyter server
        - ${JUPYTER_PORT_HOST:-8888}:${JUPYTER_PORT_HOST:-8888}
        # Syncthing
        - ${SYNCTHING_UI_PORT_HOST:-8384}:${SYNCTHING_UI_PORT_HOST:-8384}
        - ${SYNCTHING_TRANSPORT_PORT_HOST:-22999}:${SYNCTHING_TRANSPORT_PORT_HOST:-22999}
   
    environment:
        # Don't enclose values in quotes
        - DIRECT_ADDRESS=${DIRECT_ADDRESS:-127.0.0.1}
        - DIRECT_ADDRESS_GET_WAN=${DIRECT_ADDRESS_GET_WAN:-false}
        - WORKSPACE=${WORKSPACE:-/workspace}
        - WORKSPACE_SYNC=${WORKSPACE_SYNC:-false}
        - CF_TUNNEL_TOKEN=${CF_TUNNEL_TOKEN:-}
        - CF_QUICK_TUNNELS=${CF_QUICK_TUNNELS:-true}
        - WEB_ENABLE_AUTH=${WEB_ENABLE_AUTH:-true}
        - WEB_USER=${WEB_USER:-user}
        - WEB_PASSWORD=${WEB_PASSWORD:-password}
        - SSH_PORT_HOST=${SSH_PORT_HOST:-2222}
        - SSH_PORT_LOCAL=${SSH_PORT_LOCAL:-22}
        - SERVICEPORTAL_PORT_HOST=${SERVICEPORTAL_PORT_HOST:-1111}
        - SERVICEPORTAL_METRICS_PORT=${SERVICEPORTAL_METRICS_PORT:-21111}
        - SERVICEPORTAL_URL=${SERVICEPORTAL_URL:-}
        - WEBUI_BRANCH=${WEBUI_BRANCH:-}
        - WEBUI_FLAGS=${WEBUI_FLAGS:-}
        - WEBUI_PORT_HOST=${WEBUI_PORT_HOST:-7860}
        - WEBUI_PORT_LOCAL=${WEBUI_PORT_LOCAL:-17860}
        - WEBUI_METRICS_PORT=${WEBUI_METRICS_PORT:-27860}
        - WEBUI_URL=${WEBUI_URL:-}
        - JUPYTER_PORT_HOST=${JUPYTER_PORT_HOST:-8888}
        - JUPYTER_METRICS_PORT=${JUPYTER_METRICS_PORT:-28888}
        - JUPYTER_URL=${JUPYTER_URL:-}
        - SERVERLESS=${SERVERLESS:-false}
        - SYNCTHING_UI_PORT_HOST=${SYNCTHING_UI_PORT_HOST:-8384}
        - SYNCTHING_TRANSPORT_PORT_HOST=${SYNCTHING_TRANSPORT_PORT_HOST:-22999}
        - SYNCTHING_URL=${SYNCTHING_URL:-}
        #- PROVISIONING_SCRIPT=${PROVISIONING_SCRIPT:-}

        install.sh

        sudo pacman -S docker
sudo pacman -S docker-compose

        update.sh

        #!/bin/bash
# https://stackoverflow.com/questions/49316462/how-to-update-existing-images-with-docker-compose

sudo docker-compose pull
sudo docker-compose up --force-recreate --build -d
sudo docker image prune -f

        start.sh

        #!/bin/bash
sudo docker-compose down --remove-orphans && sudo docker-compose up
        • abcdqfr@lemmy.worldOP
          2·
          26 days ago

          What a treat! I just got done setting up a second venv within the sd folder. one called amd-venv the other nvidia-venv. Copied the webui.sh and webui-user.sh scripts and made separate flavors of those as well to point to the respective venv. Now If I just had my nvidia drivers working I could probably set my power supply on fire running them in parallel.

          • electricprism@lemmy.ml
            1·
            25 days ago

            Excellent, did my test config last month for a friend, I was having trouble on bare metal even though I typically prefer, and in this sense it was nice to have a image I could turn on and off as needed easily.

  • j4k3@lemmy.worldEnglish
    2·
    27 days ago

    There are likely automatic checks in the startup script. I don’t use A1111 any more in favor of Comfy and I only have a 3080Ti with 16 GB (mobile version). I can run within issues. The only time I have issues with anything AI related is when I need Nvidia’s proprietary compiler nvcc. I need nvcc to hack around with things like llama.cpp. With nvcc, it can have issues with the open source driver

  • OmegaLemmy@discuss.online
    1·
    23 days ago

    Anything with. Nvidia will actually be a better experience outside of Wayland on Linux, most people don’t want to acknowledge it but it really is the case

  • abcdqfr@lemmy.worldOP
    1·
    27 days ago

    Well I finally got the nvidia card working to some extent. On the recommended driver it only works in lowvram. medvram maxes vram too easily on this driver/cuda version for whatever reason. Does anyone know the current best nvidia driver for sd on linux? Perhaps 470, the other provided by the LM driver manager…?

  • just_another_person@lemmy.world
    11·
    27 days ago

    If you don’t understand how models use host caching, start there.

    Outside of that, you’re asking people to simplify everything into a quick answer, and there is none.

    ONNX is the “universal” standard, ensure you didn’t accidentally convert the input model into something else by accident, but more importantly, ensure when you run it and automatically convert, that the works are actually done on the GPU. ONNX defaults to CPU.