# CUDA-kdtree

**Repository Path**: master/CUDA-kdtree

## Basic Information

- **Project Name**: CUDA-kdtree
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-01-24
- **Last Updated**: 2024-01-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# CUDA-kdtree

## Table of Contents
- [Introduction](#introduction)
- [Dependencies](#dependencies)
- [Installation](#installation)
- [Documentation](#documentation)

## Introduction

CUDA-kdtree, as the project name implies, implements GPU-based KD-tree algorithm, which is described
in this paper: [Real-Time KD-Tree Construction on Graphics Hardware. K. Zhou, Q. Hou, R. Wang, B. Guo](http://www.cad.zju.edu.cn/home/rwang/publication/08kdtree.pdf).

## Dependencies
 - [CMake > v3.17]()
 - [GLEW](http://glew.sourceforge.net/)
 - [GLFW](https://www.glfw.org/](https://www.glfw.org/))
 - [GLM > 0.9.2](https://glm.g-truc.net/0.9.9/index.html)
 - [Doxygen](https://www.doxygen.nl/index.html)
 - [CUDA Toolkit](https://docs.nvidia.com/cuda/index.html)
 
## Optional dependencies

## Installation

### Linux

Tested on Ubuntu 20.04

 1. Navigate to the directory where you want the repository to be installed using the command line
 2. ```git clone https://github.com/ChinYing-Li/ClusterEngine.git```
 3. ```cd ClusterEngine```
 4. ```mkdir build```
 5. ```cd build```
 6. ```cmake ..```
 7. ```make```

### Windows 

Tested on Windows 10

TO BE UPDATED


## Documentation

TO BE UPDATED