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Compilation

This page describes how to build HASEonGPU manually from source.

For most users, manual compilation is only required when using the standalone binary directly or when adjusting build options. For general setup and dependency information, see Getting Started.

Basic Build

Clone the repository and build HASEonGPU with CMake:

git clone https://github.com/computationalradiationphysics/haseongpu.git
cd haseongpu
mkdir build
cd build
cmake ..
cmake --build .

After compilation, the calcPhiASE binary is available under:

./build/calcPhiASE

When Python bindings are enabled, they are built alongside the C++ backend.

Typical Build Variants

Minimal default build:

cmake ..
cmake --build .

Build with MPI support:

cmake .. -DDISABLE_MPI=OFF
cmake --build .

CMake Options

The following CMake variables control important build options.

DISABLE_MPI

  • Default: AUTO

  • Description: Enabling allows compilation without requiring MPI or BoostMPI as a dependency.

  • Values:

    • AUTO: CMAKE tries to detect whether MPI exists and sets this knob in correspondence

    • OFF: MPI support remains - dependencies are required

    • ON: MPI support is disabled

HASE_CUDA_ARCHITECTURES

  • Default: native

  • Description: Selects the CUDA target architecture used for compilation.

  • Typical values:

    • native: detect the local GPU architecture automatically

    • explicit CUDA architectures such as 75, 80, 86

Using native is convenient for local builds. For reproducible and performance on different systems, specifying the CUDA architecture is recommended.

HASE_ENABLE_PYTHON

  • Default: ON

  • Description:

    If python as a dependency is missing on your system this knob can be turned off in order to use HASEonGPU from the command-line only. For normal Python installation and usage, please refer to Python Interface Guide.

  • Values:

    • OFF: build only the C++ project and binary interface

    • ON: build the Python interface

HASE_BUILD_RELEASE

  • Default: ON

  • Description: Controls whether HASEonGPU applies its release build configuration. When enabled, CMake forces CMAKE_BUILD_TYPE=Release and enables the release optimization options used by the project, including native host compiler tuning flags and CUDA/HIP fast-math related flags where applicable.

    Important: HASE_BUILD_RELEASE=ON overwrites user-provided CMAKE_BUILD_TYPE values and related optimization settings during configuration. Set HASE_BUILD_RELEASE=OFF if you need a custom build type, debug flags, or manually controlled compiler optimization options.

  • Values:

    • OFF: keep user-provided build type and optimization settings

    • ON: force the project release configuration

HASE_SELECT_BACKEND_ALPAKA

  • Default: OFF

  • Description: Controls whether HASEonGPU selects available alpaka backends automatically or whether backend selection is delegated to alpaka’s CMake options.

    For general information about backend names and runtime backend selection, see Backend Selection.

  • Values:

    • OFF: HASEonGPU automatically searches for supported backend dependencies such as CUDA, HIP, and TBB and enables the corresponding alpaka backends when possible.

      If both HIP and CUDA are installed on the same system, automatic detection may cause configuration issues in alpaka. In that case, manual backend selection should be used to explicitly disable one of the conflicting backends.

    • ON: Enables manual backend selection using alpaka’s existing CMake options.

      The relevant alpaka CMake options are documented in the alpaka CMake argument documentation.

      Example: configure HASEonGPU only for an NVIDIA GPU backend:

      cmake -S . -B build \
  -DHASE_SELECT_BACKEND_ALPAKA=ON \
  -Dalpaka_DEP_CUDA=ON \
  -Dalpaka_DEP_HIP=OFF \
  -Dalpaka_DEP_TBB=OFF \
  -Dalpaka_EXEC_CpuSerial=OFF

HASE_TESTING

  • Default: OFF

  • Description: Enables the test suite during configuration and build.

  • Values:

    • OFF: tests are not built

    • ON: test targets are enabled

This option is primarily useful for development and validation work.

Notes

Manual compilation is usually not required for every workflow.

For example, when using the Python interface, the backend may be built as part of the Python installation process. However, a manual build can be useful for adjusting CMake options, debugging, or working directly with the standalone binary.