conquer3d 0.1.9

Geometric Cuda Tool Box

Conquer3D

Setup

Build from source

git clone https://github.com/KhoiDOO/geocutool.git
pip install pybind11-stubgen 

# then
cd geocutool
pip install -e . --no-build-isolation

# or 
pip install pybind11-stubgen
pip install git+https://github.com/KhoiDOO/geocutool.git --no-build-isolation

To run notebooks in examples

conda create -c conda-forge -n geocutool python=3.10 gxx_linux-64=13 gcc_linux-64=13 -y
conda activate geocutool

conda install nvidia::cuda-toolkit==12.8.2 -y

pip install torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0 --index-url https://download.pytorch.org/whl/cu128

pip install pybind11-stubgen
pip install git+https://github.com/KhoiDOO/geocutool.git --no-build-isolation

pip install plotly open3d jupyter trimesh

Development

pip install build twine
python -m build --sdist
twine upload dist/*

Reference

Research Paper

@inproceedings{2383795.2383801,
author = {Karras, Tero},
title = {Maximizing parallelism in the construction of BVHs, octrees, and k-d trees},
year = {2012},
isbn = {9783905674415},
publisher = {Eurographics Association},
address = {Goslar, DEU},
booktitle = {Proceedings of the Fourth ACM SIGGRAPH / Eurographics Conference on High-Performance Graphics},
pages = {33–37},
numpages = {5},
location = {Paris, France},
series = {EGGH-HPG'12}
}

Blog Post

• Thinking Parallel, Part I: Collision Detection on the GPU
• Thinking Parallel, Part II: Tree Traversal on the GPU
• Thinking Parallel, Part III: Tree Construction on the GPU

Repository

• cuBQL
• cudaKDTree
• [Kaolin] (https://github.com/NVIDIAGameWorks/kaolin)
• [Pytorch3D] (https://github.com/facebookresearch/pytorch3d)