Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/m-schuetz/compute_rasterizer

Rendering Point Clouds with Compute Shaders
https://github.com/m-schuetz/compute_rasterizer

Last synced: about 1 month ago
JSON representation

Rendering Point Clouds with Compute Shaders

Awesome Lists containing this project

README 

        






# About



This repository contains the source code for our papers about real-time software rasterization of point clouds, which can be 10 to 100 times faster than GL_POINTS. This is possible because GL_POINTS is built upon the triangle-oriented rendering pipeline that is not optimal for pixel-sized points.



The basic idea is to spawn a compute shader that transforms points to screen space, encodes depth and color into a single 64 bit integer, and uses atomicMin to compute the closest point for each pixel. The color value is then extracted from the interleaved depth+color buffer and converted into a regular OpenGL texture for display. 



The latest improvement also groups about 10k points into batches, and each compute workgroup(128 threads) renders a batch(10k points), i.e., each thread renders about 80 points. This allows several batch-level optimizations such as frustum culling, LOD rendering, and adaptive precision. Adaptive precision picks a sufficient coordinate precision (typically just 10 bit per axis) depending on the projected batch size, which boosts brute-force performance due to lower memory bandwidth requirements.



The main branch is a slightly more user friendly version that allows loading LAS files via drag&drop. Other branches contain snapshots of the code made after evaluations for specific paper submissions:



* ["Software Rasterization of 2 Billion Points in Real-Time"](https://www.cg.tuwien.ac.at/research/publications/2022/SCHUETZ-2022-PCC/) 


In branch [compute_rasterizer_2022](https://github.com/m-schuetz/compute_rasterizer/tree/compute_rasterizer_2022)


[paper](https://www.cg.tuwien.ac.at/research/publications/2022/SCHUETZ-2022-PCC/) - video



* ["Rendering Point Clouds with Compute Shaders and Vertex Order Optimization"](https://www.cg.tuwien.ac.at/research/publications/2021/SCHUETZ-2021-PCC/)


In branch [compute_rasterizer_2021](https://github.com/m-schuetz/compute_rasterizer/tree/compute_rasterizer_2021)



# Features and Limitations



* Renders up to one billion points in about 8 milliseconds (hence 2 billion points in real-time, 60fps) on an RTX 3090.

* You need to make sure not to load more than your GPU memory can handle. You'll need about 1.6GB for every 100 million points, plus 1GB or 2GB overhead. 

* Drag & Drop a LAS or LAZ files into the window to load it. Only RGB attributes are displayed.

* Requires Windows and NVIDIA GPUs. Pull requests for AMD support are welcome.



# Building



* Clone the repository

* Compile build/ComputeRasterizer.sln with Visual Studio 2022.

* Run (ctrl + f5)



	

		Method

		Location

		

	

	

		basic

		./modules/compute_loop_las

		

	

	

		prefetch

		./modules/compute_loop_las2

		fastest, each thread fetches 4 points at a time

	

	

		hqs

		./modules/compute_loop_las_hqs

		High-Quality Shading

	

	

		LOD

		./modules/compute_loop_nodes

		Support for the Potree LOD format

	

	

		LOD hqs

		./modules/compute_loop_nodes_hqs

	



# Citing


@article{SCHUETZ-2022-PCC,

  title =      "Software Rasterization of 2 Billion Points in Real Time",

  author =     "Markus Sch\"{u}tz and Bernhard Kerbl and Michael Wimmer",

  year =       "2022",

  month =      jul,

  journal =    "Proc. ACM Comput. Graph. Interact. Tech.",

  volume =     "5",

  pages =      "1--16",

  URL =        "https://www.cg.tuwien.ac.at/research/publications/2022/SCHUETZ-2022-PCC/",

}



@article{SCHUETZ-2021-PCC,

  title =      "Rendering Point Clouds with Compute Shaders and Vertex Order Optimization",

  author =     "Markus Sch\"{u}tz and Bernhard Kerbl and Michael Wimmer",

  year =       "2021",

  month =      jul,

  doi =        "10.1111/cgf.14345",

  journal =    "Computer Graphics Forum",

  number =     "4",

  volume =     "40",

  pages =      "115--126",

  keywords =   "point-based rendering, compute shader, real-time rendering",

  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/SCHUETZ-2021-PCC/",

}