【问题标题】:docker-compose can't found nvidia dirverdocker-compose 找不到 nvidia 驱动程序
【发布时间】:2021-08-24 09:06:42
【问题描述】:

我正在尝试运行clara train example,但是当我执行startClaraTrainNoteBooks.sh 时,容器找不到nvidia 驱动程序。 我已经知道脚本执行docker-compose.yml。于是我测试了docker-compose是否能找到nvidia驱动:

services:
  test:
    image: nvidia/cuda:10.2-base
    command: nvidia-smi
    deploy:
      resources:
        reservations:
          devices:
          - driver: nvidia
            capabilities: [gpu]
            device_ids: ['0']

输出:

USER@test:~$ docker-compose up
WARNING: Found orphan containers (hp_nvsmi_1) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up.
Starting hp_test_1 ... done
Attaching to hp_test_1
test_1  | Mon Jun  7 09:01:44 2021
test_1  | +-----------------------------------------------------------------------------+
test_1  | | NVIDIA-SMI 460.27.04    Driver Version: 460.27.04    CUDA Version: 11.2     |
test_1  | |-------------------------------+----------------------+----------------------+
test_1  | | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
test_1  | | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
test_1  | |                               |                      |               MIG M. |
test_1  | |===============================+======================+======================|
test_1  | |   0  GeForce RTX 206...  Off  | 00000000:01:00.0 Off |                  N/A |
test_1  | |  0%   34C    P8    17W / 215W |    100MiB /  7979MiB |      0%      Default |
test_1  | |                               |                      |                  N/A |
test_1  | +-------------------------------+----------------------+----------------------+
test_1  |
test_1  | +-----------------------------------------------------------------------------+
test_1  | | Processes:                                                                  |
test_1  | |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
test_1  | |        ID   ID                                                   Usage      |
test_1  | |=============================================================================|
test_1  | +-----------------------------------------------------------------------------+
hp_test_1 exited with code 0

但是startClaraTrainNoteBooks.sh cna 找不到它。

root@claratrain:/claraDevDay# nvidia-smi 
root@claratrain:/claraDevDay# 

其实startDocker.sh可以找到驱动。

root@c7c2d5597eb8:/claraDevDay# nvidia-smi 
Mon Jun  7 09:11:43 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.27.04    Driver Version: 460.27.04    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce RTX 206...  Off  | 00000000:01:00.0 Off |                  N/A |
|  0%   35C    P8    17W / 215W |    100MiB /  7979MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+
root@c7c2d5597eb8:/claraDevDay# 

我该怎么办?

【问题讨论】:

    标签: docker docker-compose nvidia nvidia-docker


    【解决方案1】:

    docker-compose.yml 脚本需要像这样重写并正常工作:

    # SPDX-License-Identifier: Apache-2.0
    
    version: "3.8"
    services:
      claratrain:
        container_name: claradevday-pt
        hostname: claratrain
        ##### use vanilla clara train docker
        #image: nvcr.io/nvidia/clara-train-sdk:v4.0
        ##### to build image with GPU dashboard inside jupyter lab
        build:
          context: ./dockerWGPUDashboardPlugin/    # Project root
          dockerfile: ./Dockerfile                 # Relative to context
        image: clara-train-nvdashboard:v4.0
        depends_on:
          - tritonserver
        ports:
          - "3030:8888"  # Jupyter lab port
          - "3031:5000"  # AIAA port
        ipc: host
        volumes:
          - ${TRAIN_DEV_DAY_ROOT}:/claraDevDay/
          - /raid/users/aharouni/data:/data/
        command: "jupyter lab /claraDevDay --ip 0.0.0.0 --allow-root --no-browser --config /claraDevDay/scripts/jupyter_notebook_config.py"
    #    command: tail -f /dev/null
    #    tty: true
        deploy:
          resources:
            reservations:
              devices:
                - driver: nvidia
                  capabilities: [ gpu ]
                  # To specify certain GPU uncomment line below
                  #device_ids: ['0,3']
    #############################################################
      tritonserver:
        image: nvcr.io/nvidia/tritonserver:21.02-py3
        container_name: aiaa-triton
        hostname: tritonserver
        restart: unless-stopped
        command: >
          sh -c "chmod 777 /triton_models &&
            /opt/tritonserver/bin/tritonserver \
              --model-store /triton_models \
              --model-control-mode="poll" \
              --repository-poll-secs=5 \
              --log-verbose ${TRITON_VERBOSE}"
        volumes:
          - ${TRAIN_DEV_DAY_ROOT}/AIAA/workspace/triton_models:/triton_models
    #    shm_size: 1gb
    #    ulimits:
    #      memlock: -1
    #      stack: 67108864
    #    logging:
    #      driver: json-file
    

    【讨论】:

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