main.yml

name: build

on:
  push:
    branches: [ "main" ]
  pull_request:
    branches: [ "main" ]

env:
  # Customize the CMake build type here (Release, Debug, RelWithDebInfo, etc.)
  BUILD_TYPE: Release
  LLVM_COMMIT: "6146a88f60492b520a36f8f8f3231e15f3cc6082"
  CCACHE_DIR: "${{ github.workspace }}/.ccache"
  CCACHE_COMPRESS: "true"
  CCACHE_MAXSIZE: "1G"

jobs:
  build:
    # The CMake configure and build commands are platform agnostic and should work equally well on Windows or Mac.
    # You can convert this to a matrix build if you need cross-platform coverage.
    # See: https://docs.github.com/en/free-pro-team@latest/actions/learn-github-actions/managing-complex-workflows#using-a-build-matrix
    runs-on: ubuntu-22.04
    strategy:
      fail-fast: false
      matrix:
        python-version: ["3.11.13"]

    steps:
    - uses: actions/checkout@v3
      with:
        submodules: true

    # Update references
    - name: Git Submodule Update
      run: |
        git submodule update --init --recursive

    # install ninja
    - name: install ninja for LLVM build
      run: sudo apt-get install ninja-build

    # install ccache
    - name: install ccache & lld
      run: |
        sudo apt-get install ccache
        sudo apt-get install lld

    # Restores ccache directory.
    - name: ccache cache
      uses: actions/cache@v4
      with:
        path: ${{ env.CCACHE_DIR }}
        key: ${{ runner.os }}-ccache-llvm-${{ env.LLVM_COMMIT }}-${{ github.sha }}
        # Restores from the last successful build of this LLVM version.
        restore-keys: |
          ${{ runner.os }}-ccache-llvm-${{ env.LLVM_COMMIT }}-

    # install graphviz
    - name: install graphviz
      run: sudo apt-get install graphviz

    # setup LLVM
    - name: install a specific version of LLVM
      working-directory: ${{github.workspace}}
      run: |
        mkdir -p ${{ env.CCACHE_DIR }}
        git --version
        git clone --depth 1 --filter=blob:none --revision=${{ env.LLVM_COMMIT }} https://github.com/llvm/llvm-project.git
        cd llvm-project
        mkdir build && cd build
        cmake -G Ninja ../llvm \
          -DLLVM_ENABLE_PROJECTS="mlir;clang" \
          -DLLVM_BUILD_EXAMPLES=OFF \
          -DLLVM_TARGETS_TO_BUILD="Native" \
          -DCMAKE_BUILD_TYPE=Release \
          -DLLVM_ENABLE_ASSERTIONS=ON \
          -DCMAKE_C_COMPILER=clang \
          -DCMAKE_CXX_COMPILER=clang++ \
          -DCMAKE_CXX_STANDARD=17 \
          -DCMAKE_CXX_FLAGS="-std=c++17 -frtti" \
          -DLLVM_ENABLE_LLD=ON \
          -DMLIR_INSTALL_AGGREGATE_OBJECTS=ON \
          -DLLVM_ENABLE_RTTI=ON \
          -DLLVM_CCACHE_BUILD=ON \
          -DCMAKE_C_COMPILER_LAUNCHER=ccache \
          -DCMAKE_CXX_COMPILER_LAUNCHER=ccache

        echo "CCache Status before build:"
        ccache -s

        cmake --build .

        echo "CCache Status after build:"
        ccache -s

        # Add LLVM tools to PATH
        echo "${{github.workspace}}/llvm-project/build/bin" >> $GITHUB_PATH
    # setup mlir-cgra
    - name: setup dataflow tool-chain
      working-directory: ${{github.workspace}}
      run: |
        mkdir build && cd build
        cmake -G Ninja .. \
          -DLLVM_DIR=${{github.workspace}}/llvm-project/build/lib/cmake/llvm \
          -DMLIR_DIR=${{github.workspace}}/llvm-project/build/lib/cmake/mlir \
          -DMLIR_SOURCE_DIR=${{github.workspace}}/llvm-project/mlir \
          -DMLIR_BINARY_DIR=${{github.workspace}}/llvm-project/build \
          -DCMAKE_CXX_FLAGS="-std=c++17"

        ninja

        # # install clang-12/opt-12
        # - name: install LLVM and Clang for scripts/experiment
        #   uses: egor-tensin/setup-clang@v1
        #   with:
        #     version: 12
        #     platform: x64

        # # add path
        # - name: add paths
        #   working-directory: ${{github.workspace}}
        #   run: |
        #     echo "${{github.workspace}}/llvm-project/build/bin" >> $GITHUB_PATH
        #     echo "${{github.workspace}}/build/bin" >> $GITHUB_PATH

        # # run demo baseline
        # - name: run demo baseline
        #   working-directory: ${{github.workspace}}
        #   run: |
        #     cd ./experiments/demo/baseline
        #     sh script.sh
        #     ./simulate

    # Sets up Python environment for torch-mlir
    - name: Set up Python ${{ matrix.python-version }}
      uses: actions/setup-python@v4
      with:
        python-version: ${{ matrix.python-version }}
    # Installs NumPy 1.x first (compatable with torch-mlir)
    - name: Install NumPy 1.x
      run: pip install "numpy<2.0"
    - name: Install PyTorch
      run: |
        wget https://github.com/llvm/torch-mlir/releases/download/snapshot-20231229.1067/torch-2.2.0.dev20231204+cpu-cp311-cp311-linux_x86_64.whl
        pip install torch-2.2.0.dev20231204+cpu-cp311-cp311-linux_x86_64.whl
    - name: Install torch-mlir
      run: |
        wget https://github.com/llvm/torch-mlir/releases/download/snapshot-20231229.1067/torch_mlir-20231229.1067-cp311-cp311-linux_x86_64.whl
        pip install torch_mlir-20231229.1067-cp311-cp311-linux_x86_64.whl

    # shows ccache stats to verify it's working.
    - name: ccache stats
      run: ccache -s

    # run demo cgra
    - name: run test
      working-directory: ${{github.workspace}}
      run: |
        cd ${{github.workspace}}/test
        ${{github.workspace}}/llvm-project/build/bin/llvm-lit . -v