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CUDA based Pathtracing Offline and Realtime Renderer

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Luminary

CUDA Pathtracing Renderer

AboutUsageBuildingLicencesLiterature

Daxx Example

Todano Example

Aranos Example

Aranos Example

About

Luminary is a renderer using pathtracing. It aims at rendering high quality images while maintaining usable performance in realtime mode. Usage is supposed to be non-artist friendly, that is, the input consists of only meshes with albedo, material, illuminance and normal textures. All other effects come parameterized. This project is for fun and to learn more about rendering.

The goal is to use as few libraries as feasible. Currently, the following libraries are used: SDL2, zlib, qoi, OptiX and Ceb.

Meshes and textures in the example images are taken from the Ratchet and Clank HD Trilogy and were exported using Replanetizer.

Usage

The scene is described through the Luminary Scene Description format (*.lum). The format is documented in the Luminary File Documentations. It is possible to specify a *.obj file instead of a *.lum file. This will load the mesh and use the default settings. Then one can make changes to the settings and automatically generate a *.lum file.

You can start as:

Luminary [File] [Option]

where File is a relative or absolute path to a *.obj or *.lum file and Option is one or more of:

-o, --offline
        start in offline mode, which renders one image using the specified settings

-t, --timings
        print execution times of some CPU functions

-l, --logs
        write a log file at the end of execution

-s, --samples
        set custom sample count for offline rendering (overrides value set by input file)

-w, --width
        set custom width (overrides value set by input file)

-h, --height
        set custom height (overrides value set by input file)

-p, --post-menu
        open post process menu after rendering an image in offline mode

-u, --unittest
        run a test suite, no rendering is done

-v, --version
        print build information and exit

    --force-displacement
        turn on displacement map usage on Ampere and Turing architecture GPUs

    --no-omm
        turn off opacity micromap usage

    --aov-mode
        generate and output additional variables like albedo, normal, direct lighting and indirect lighting

    --qoi
        set output image format to QOI

    --png
        set output image format to PNG

    --optix-validation
        enables OptiX validation for debugging

Realtime Mode

UI Example

In realtime mode, which is used by default, you can control the camera through WASD, LCTRL, SPACE and the mouse. The sun can be controlled with the arrow keys. A snapshot can be made by pressing [F12]. You can open a user interface with [E] in which you can change most parameters.

📝 In a UI panel, if the number is colored when hovering, you can change the value by holding the left mouse button and moving the mouse left/right.

Building

Requirements:

  • CUDA Toolkit 12.1
  • Optix 8.0 SDK
  • SDL2 and SDL2_ttf
  • Modern CMake
  • Make or Ninja
  • SSE 4.1 compatible CPU
  • Supported Nvidia GPU (Pascal or later)

📝 The use of opacity micromaps and displacement micromaps at the same time is only possible on Ada Lovelace Arch GPUs. (This seems to not be documented anywhere.)

zlib comes as a submodule and is compiled with Luminary, it is not required to have zlib installed. This is due to the compiler limitations of CUDA on Windows which makes usage of zlib-ng inconvenient.

📝 zlib and qoi come as git submodules. Make sure to clone the submodules by using git submodule update --init after cloning Luminary.

CMake Options

Option Description
-DDEBUG=ON/OFF Enable Debug Mode. Default: OFF
-DNATIVE_CUDA_ARCH=ON/OFF Enable that the CUDA architecture is based on the installed GPU. Default: ON
-DSHOW_KERNEL_STATS=ON/OFF Enable that CUDA kernel stats are printed at compilation. Default: OFF

Linux

You need a nvcc compatible host compiler. Which compilers are supported can be found in the CUDA Installation Guide. In general, any modern GCC, ICC or clang will work. By default, nvcc uses gcc/g++.

mkdir build
cmake -B ./build -S .
cd build
make

If cmake fails to find some packages you will have to specify the directory. For this look at the Windows section.

Windows

Additional requirements:

  • MSVC
  • Windows SDK
  • clang-cl

Clang-cl comes for example with mingw-w64 or Visual Studio. MSVC and Windows SDK come with Visual Studio. However, if at some point it is possible to get them standalone, that would probably also suffice. Note that the paths to the CUDA Toolkit, OptiX, SDL2 and SDL2_ttf must be defined in the PATH environment variable, otherwise they need to be defined in CMake using -D{PACKAGENAME}_ROOT="{PATH}".

Regarding MSVC and Windows SDK paths, there are two possibilities:

Option 1:

call "{VS Path}/VC/Auxiliary/Build/vcvarsall.bat" amd64

This sets the environment variables containing all the paths in this terminal instance.

Option 2: Add the paths of the binaries to the PATH environment variable, they look something like that:

{VS Path}/VC/Tools/MSVC/{Version}/bin/Hostx64/x64
{Windows SDK Path}/10/bin/{Version}/x64

Additionally, you need to pass the path to the libraries to cmake, the paths look like this:

{VS Path}/VC/Tools/MSVC/{Version}/lib/x64
{Windows SDK Path}/10/Lib/{Version}

Regarding SDL2: You need to download SDL2_devel and SDL2_ttf_devel for VC, these are for example available on Github.

You can build using the following commands in the main project directory:

mkdir build
call "{VS Path}/VC/Auxiliary/Build/vcvarsall.bat" amd64
cmake -B ./build -S . -G Ninja -DCMAKE_C_COMPILER="{Path}/clang-cl.exe"
cd build && ninja

or alternatively:

mkdir build
cmake -B ./build -S . -G Ninja -DCMAKE_C_COMPILER="{Path}/clang-cl.exe" -DWIN_LIB_DIR="{Windows SDK Path}/10/Lib/10.0.19041.0" -DMSVC_LIB_DIR="{VS Path}/VC/Tools/MSVC/{Version}/lib/x64"
cd build && ninja

Notes:

  • It is important to use either clang-cl.exe or cl.exe as the C compiler.
  • If you use the first option, run vcvarsall.bat only once per terminal.
  • SDL2.dll and SDL2_ttf.dll are automatically copied into the build dir and always need to reside in the same directory as Luminary.exe.

📝 This is all only necessary because CUDA only supports MSVC as a host compiler on Windows. If this changes in the future then the Windows build will look similar to the Linux build.

Licences

The licence for this code can be found in the LICENCE file.

The default font provided by Luminary is the font Tuffy by Ulrich Thatcher which he placed in the Public Domain.

Literature

This is a list of papers I have used for this project so far. Note that some techniques presented in these papers are not implemented at the moment but their ideas were helpful nonetheless:

  • T. Möller, B. Trumbore, Fast, Minimum Storage Ray-Triangle Intersection, Journal of Graphics Tools, 2, pp. 21-28, 1997.
  • A. Majercik, C. Crassin, P. Shirley, M. McGuire, A Ray-Box Intersection Algorithm and Efficient Dynamic Voxel Rendering, Journal of Computer Graphics Techniques, 7(3), pp. 66-82, 2018
  • K. Booth, J. MacDonald, Heuristics for ray tracing using space subdivision, The Visual Computer, 6, pp. 153-166, 1990.
  • T. Karras, S. Laine, H. Ylitie, Efficient Incoherent Ray Traversal on GPUs Through Compressed Wide BVHs, HPG '17: Proceedings of High Performance Graphics, pp. 1-13, 2017.
  • J. Boksansky, Crash Course in BRDF Implementation, https://boksajak.github.io/blog/BRDF, 2021.
  • S. Lagarde, C. de Rousiers, Moving Frostbite to Physically Based Rendering, 2014.
  • A. Dietrich, H. Friedrich and M. Stich, Spatial splits in bounding volume hierarchies, HPG '09: Proceedings of the Conference on High Performance Graphics 2009, pp. 7-13, 2009.
  • E. Haines, T. Akenine-Möller, "Ray Tracing Gems", Apress, 2019.
  • J. Jimenez, Next Generation Post Processing in Call of Duty: Advanced Warfare, SIGGRAPH 2014.
  • A. Marrs, P. Shirley and I. Wald, "Ray Tracing Gems II", Apress, 2021.
  • A. Kirk and J. O'Brien, Perceptually Based Tone Mapping for Low-Light Conditions, ACM Transactions on Graphics, 30(4), pp. 1-10, 2011.
  • J. Patry, Real-Time Samurai Cinema: Lighting, Atmosphere, and Tonemapping in Ghost of Tsushima, SIGGRAPH 2021.
  • S. Hillaire, Physically Based Sky, Atmosphere & Cloud Rendering in Frostbite, SIGGRAPH 2016.
  • S. Hillaire, A Scalable and Production Ready Sky and Atmosphere Rendering Technique, Computer Graphics Forum, 39(4), pp. 13-22, 2020.
  • A. Wilkie, P. Vevoda, T. Bashford-Rogers, L. Hosek, T. Iser, M. Kolarova, T. Rittig and J. Krivanek, A Fitted Radiance and Attenuation Model for Realistic Atmospheres, Association for Computing Machinery, 40 (4), pp. 1-14, 2021.
  • E. Bruneton, A Qualitative and Quantitative Evaluation of 8 Clear Sky Models, IEEE Transactions on Visualization and Computer Graphics, 23, pp. 2641–2655, 2016.
  • E. Bruneton, Precomputed Atmospheric Scattering, 2017. URL: https://github.com/ebruneton/precomputed_atmospheric_scattering
  • A. Schneider, The Real-time Volumetric Cloudscapes of Horizon: Zero Dawn, SIGGRAPH 2015.
  • A. Schneider, Nubis, Evolved: Real-Time Volumetric Clouds for Skies, Environments, and VFX, SIGGRAPH 2022.
  • B. Bitterli, C. Wyman, M. Pharr, P. Shirley, A. Lefohn, W. Jarosz, Spatiotemporal reservoir resampling for real-time ray tracing with dynamic direct lighting, ACM Transactions on Graphics (Proceedings of SIGGRAPH), 39(4), 2020.
  • C. Wyman, A. Panteleev, "Rearchitecting Spatiotemporal Resampling for Production", High-Performance Graphics - Symposium Papers, pp. 23-41, 2021.
  • T. Duff, J. Burgess, P. Christensen, C. Hery, A. Kensler, M. Liani, R. Villemin, Building an Orthonormal Basis, Revisited, Journal of Computer Graphics Techniques, 6(1), pp. 1-8, 2017.
  • B. Widynski, Squares: A Fast Counter-Based RNG, arXiv preprint, 2020. URL: https://arxiv.org/abs/2004.06278
  • J. Dupuy, A. Benyoub, Sampling Visible GGX Normals with Spherical Caps, 2023. arXiv:2306.05044
  • J. Jendersie and E. d'Eon, An Approximate Mie Scattering Function for Fog and Cloud Rendering, SIGGRAPH 2023 Talks, 2023.
  • M. Droske, J. Hanika, J. Vorba, A. Weidlich, M. Sabbadin, Path Tracing in Production: The Path of Water, ACM SIGGRAPH 2023 Courses, 2023.
  • L. Belcour and E. Heitz, Lessons Learned and Improvements when Building Screen-Space Samplers with Blue-Noise Error Distribution, ACM SIGGRAPH 2021 Talks, pp. 1-2, 2021.
  • K. Eto, Y. Tokuyoshi, Bounded VNDF Sampling for Smith–GGX Reflections, ACM SIGGRAPH Asia 2023 Technical Communications, pp. 1-4, 2023.
  • D. Sforza, F. Pellacini, Enforcing Energy Preservation in Microfacet Models, Smart Tools and Applications in Graphics - Eurographics Italian Chapter Conference, 2022.
  • R. West, I. Georgiev, T. Hachisuka, Marginal Multiple Importance Sampling, SIGGRAPH Asia 2022 Conference Papers, 2022.
  • B. Walter, S. R. Marschner, H. Li, K. E. Torrance, Microfacet models for refraction through rough surfaces, Proceedings of the 18th Eurographics Conference on Rendering Techniques, pp. 195-206, 2007.
  • A. C. Estevez, C. Kulla, Importance Sampling of Many Lights with Adaptive Tree Splitting, Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(2), pp. 1-17, 2018.
  • A. C. Estevez, P. Lecocq, C. Hellmuth, A Resampled Tree for Many Lights Rendering, ACM SIGGRAPH 2024 Talks, 2024.
  • V. Schüßler, J. Hanika, C. Dachsbacher, Bridge Sampling for Connections via Multiple Scattering Events, Computer Graphics Forum (Proceedings of Eurographics Symposium on Rendering, 43(4), 2024.