# This is a sample build configuration for C++ – Make.
# Check our guides at https://confluence.atlassian.com/x/5Q4SMw for more examples.
# Only use spaces to indent your .yml configuration.
# -----
# You can specify a custom docker image from Docker Hub as your build environment.
image: nvidia/cuda

# JP notes:
# 1) We need a sufficiently recent GPU to run the code (needs to support CUDA 10 + NVIDIA drivers 418)
# 2) The default CUDA driver loaded with the docker image is too old
# => Either Bitbucket offers no NVIDIA GPUs at all, the GPUs are very old, or then we have to update the drivers  by ourselves
# ==> Updating the kernel drivers by ourselves probably requires creating our own docker image.
# ===> Which might not even work since I don't know what kind of hardware we're running on (lspci was not available)

pipelines:
  # default: # Default is run at every push but we have only 500 build minutes / month so that probably wouldn't work out
  custom: # Manual/scheduled building only
    scheduled:
    - step:
        script: # Modify the commands below to build your repository.
          - mkdir -p build && cd build
          - apt-get update
          - apt-get install -y cmake flex bison openmpi-bin libopenmpi-dev
          - cmake -DDSL_MODULE_DIR="acc/mhd_solver" -DBUILD_STANDALONE=ON -DBUILD_UTILS=ON -DBUILD_RT_VISUALIZATION=OFF -DBUILD_SAMPLES=ON -DDOUBLE_PRECISION=OFF -DMULTIGPU_ENABLED=ON -DMPI_ENABLED=OFF .. # Single precision
          - make -j
          - rm -rf *
          - cmake -DCMAKE_CXX_COMPILER=$(which mpicxx) -DDSL_MODULE_DIR="acc/mhd_solver" -DBUILD_STANDALONE=ON -DBUILD_UTILS=ON -DBUILD_RT_VISUALIZATION=OFF -DBUILD_SAMPLES=ON -DDOUBLE_PRECISION=ON -DMULTIGPU_ENABLED=ON -DMPI_ENABLED=ON .. # Double precision
          - make -j
          # - ./ac_run -t