An important goal is to make the simulator user-friendly through a modern user interface and a playful approach.
Note: This branch contains ongoing work for the next major release. For the latest stable version, please visit the master branch.
- Particles for simulating soft body mechanics, heat dissipation, bondings, damages, phase transitions, etc.
- Real-time user interactions with running simulations
- Simulation runs entirely on GPU via CUDA
- Rendering and post-processing via OpenGL using CUDA-OpenGL interoperability
- Programmable particle actions for simulating digital organisms and studying evolution
- Information and energy transportation layer between connected particles
- Built-in graph editor and scripting environment for designing customized machines and worlds
The simulation code is written entirely in CUDA and highly optimized for large-scale real-time simulations of millions of bodies and particles. The development is driven by the desire to better understand the conditions for (pre-)biotic evolution and the growing complexity of biological systems.
- A first attempt to answer: Feed your curiosity by watching evolution at work! As soon as self-replicating machines come into play and mutations are turned on, the simulation itself does everything.
- Perhaps the most honest answer: Fun! It is almost like a game with a pretty fast and realistic physics engine. You can make hundreds of thousands of machines accelerate and destroy with the mouse cursor. It feels like playing god in your own universe with your own rules. Different render styles and a visual editor offer fascinating insights into the events. There are a lot of videos on the YouTube channel for illustration.
- A more academic answer: A tool to tackle fundamental questions of how complexity or life-like structure may arise from simple components. How do entire ecosystems adapt to environmental changes and find a new equilibrium? How to find conditions that allow open-ended evolution?
Further information and artworks
An Nvidia graphics card with compute capability 6.0 or higher is needed. Please check https://en.wikipedia.org/wiki/CUDA#GPUs_supported.
The build process is mostly automated using the cross-platform CMake build system and the vcpkg package manager, which is included as a Git submodule.
To obtain the sources, please open a command prompt in a suitable directory (which should not contain whitespace characters) and enter the following command:
git clone --recursive https://github.com/chrxh/alien.git
Note: The --recursive parameter is necessary to check out the vcpkg submodule as well. Besides that, submodules are not normally updated by the standard git pull command. Instead, you need to write git pull --recurse-submodules.
Prerequisites: CUDA Toolkit 11.2+ and Visual Studio 2019 (or an alternative tool chain)
Build steps:
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
cmake --build . --config Release
If the compilation was successful, the alien executable is located in:
.\Release\alien.exe
Prerequisites: CUDA Toolkit 11.2+ and GCC 9.x+
Build steps:
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j8
If everything goes well, the alien executable can be found under the build directory:
./alien
An installer for 64-bit binaries is provided for Windows 10: download link.
In the case that the program crashes for an unknown reason, please refer to the troubleshooting section in alien-project.org/downloads.html.
Please visit alien-project.org for a documentation of the program and the underlying model. It contains many brief tutorials that guide the reader into the program in small portions.
alien is licensed under the GPLv3.