Getting Started

This page provides a short guide to setting up HASEonGPU and choosing the interface that best fits your workflow.

HASEonGPU supports multiple usage paths:

Python Interface for direct usage from Python
Binary Interface for command-line execution
MATLAB Interface for integration into existing MATLAB or Octave workflows

Repository Setup

Clone the repository from GitHub:

git clone https://github.com/computationalradiationphysics/haseongpu.git
cd haseongpu

Dependencies

Required software:

cmake >= 3.0.1
gcc >= 11
cuda >= 11.0

Optional software and tools:

OpenMPI >= 4.0
Python >= 3.10
MATLAB or Octave
ParaView for visualization of .vtk output

Hardware requirements:

NVIDIA GPU with CUDA support
For GPU execution, a CUDA-capable device is required

Additional Notes

For Windows-specific installation notes [deprecated], see Windows Notes.

Compilation Notes

A manual compilation step is available, but is not required for every workflow.

For example, when using the Python interface, the C++ backend is built under the hood during installation. For details on manual compilation, see Compilation.

Choose an Interface

Python Interface

The Python interface is the recommended starting point for most new users. It provides a library call that can be easily integrated into custom workflows. Additionally, the provided examples demonstrate this usage.

Continue with Python Interface.

Binary Interface

The binary interface is useful if you want to run HASEonGPU directly from the command line, or use it as an entry point for constructing a custom API call.

Continue with Binary Interface.

MATLAB Interface

The MATLAB-compatible interface is mainly intended for existing MATLAB or Octave workflows. If you are starting a new workflow, the Python interface is usually the better choice.

Continue with MATLAB Interface.

Typical Workflow

A typical HASEonGPU setup consists of the following steps:

Clone the repository
Install the required dependencies
Decide which interface to use
Follow installation steps provided on the page of the chosen interface
In order to verify your current setup run one of the provided interface-specific examples
Use HASEonGPU in your own workflow

Next Step

Proceed to one of the interface pages listed above, depending on how you want to use HASEonGPU.