MedImages.jl/docker-compose.yml at main · JuliaHealth/MedImages.jl · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
# MedImages.jl Docker Compose Configuration
# Usage:
#   docker compose up medimages    - Interactive Julia REPL with GPU
#   docker compose run test        - Run test suite
#   docker compose run benchmark   - Run GPU benchmarks

services:
  # Interactive development environment with GPU support
  medimages:
    build:
      context: .
      dockerfile: Dockerfile
    image: medimages:latest
    container_name: medimages-dev
    volumes:
      - .:/workspace/MedImages.jl
      - julia-depot:/root/.julia
      - ./test_data:/workspace/MedImages.jl/test_data:ro
    working_dir: /workspace/MedImages.jl
    stdin_open: true
    tty: true
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    environment:
      - JULIA_NUM_THREADS=auto
      - JULIA_CUDA_SOFT_MEMORY_LIMIT=90%
    command: ["julia", "--project=."]

  # Run test suite
  test:
    build:
      context: .
      dockerfile: Dockerfile
    image: medimages:latest
    volumes:
      - .:/workspace/MedImages.jl
      - julia-depot:/root/.julia
      - ./test_data:/workspace/MedImages.jl/test_data:ro
    working_dir: /workspace/MedImages.jl
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    environment:
      - JULIA_NUM_THREADS=auto
    command: ["julia", "--project=.", "-e", "using Pkg; Pkg.test()"]

  # Run GPU benchmarks with synthetic data
  benchmark:
    build:
      context: .
      dockerfile: Dockerfile
    image: medimages:latest
    volumes:
      - .:/workspace/MedImages.jl
      - julia-depot:/root/.julia
      - ./benchmark_results:/workspace/MedImages.jl/benchmark/benchmark_results
      - ./test_data:/workspace/MedImages.jl/test_data:ro
    working_dir: /workspace/MedImages.jl/benchmark
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    environment:
      - JULIA_NUM_THREADS=auto
      - JULIA_CUDA_SOFT_MEMORY_LIMIT=90%
    command: ["julia", "--project=.", "run_gpu_benchmarks.jl", "--synthetic", "--backends", "all"]

  # CPU-only mode (no GPU required)
  medimages-cpu:
    build:
      context: .
      dockerfile: Dockerfile
    image: medimages:latest
    container_name: medimages-cpu
    volumes:
      - .:/workspace/MedImages.jl
      - julia-depot:/root/.julia
      - ./test_data:/workspace/MedImages.jl/test_data:ro
    working_dir: /workspace/MedImages.jl
    stdin_open: true
    tty: true
    environment:
      - JULIA_NUM_THREADS=auto
      - CUDA_VISIBLE_DEVICES=
    command: ["julia", "--project=."]

  # Run CPU-only tests
  test-cpu:
    build:
      context: .
      dockerfile: Dockerfile
    image: medimages:latest
    volumes:
      - .:/workspace/MedImages.jl
      - julia-depot:/root/.julia
      - ./test_data:/workspace/MedImages.jl/test_data:ro
    working_dir: /workspace/MedImages.jl
    environment:
      - JULIA_NUM_THREADS=auto
      - CUDA_VISIBLE_DEVICES=
    command: ["julia", "--project=.", "-e", "using Pkg; Pkg.test()"]

volumes:
  julia-depot:
    name: medimages-julia-depot