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juliusikkala committed Oct 10, 2022
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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -10,12 +10,12 @@ portability and low latency. It uses C++17 and Vulkan, primarily relying on the
extension, but comes with a fallback rasterization mode that can be used on devices that
do not have that extension.

Tauray is developed by the [VGA research group](https://webpages.tuni.fi/vga/)
Tauray development is led by the [VGA research group](https://webpages.tuni.fi/vga/)
in Tampere University. The project is described in a conference publication ([DOI link](https://doi.org/10.1145/3550340.3564225)),
which includes performance benchmarks and more information on Tauray.
[A pre-print is available.](https://webpages.tuni.fi/vga/publications/Tauray2022.pdf)

measurements in the publication are done with the [v1.0.0 release](https://github.com/vga-group/tauray/releases/tag/v1.0.0).
Measurements in the publication are done with the [v1.0.0 release](https://github.com/vga-group/tauray/releases/tag/v1.0.0).
For practical purposes however, we recommend always using the latest available
release instead, as there are bug fixes and additional features included.

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33 changes: 33 additions & 0 deletions docs/notes-1.0.txt
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Tauray v1.0 release
---------------------

Tauray is a real-time rendering framework, with a focus on distributed
computing, scalability, portability and low latency. It uses C++17 and Vulkan,
primarily relying on the cross-vendor ray tracing extensions, but comes with a
fallback rasterization mode that can be used on devices that do not have that
extension.

Tauray development is led by the [VGA research group](https://webpages.tuni.fi/vga/)
in Tampere University. The project is described in a conference publication ([DOI link](https://doi.org/10.1145/3550340.3564225)),
which includes performance benchmarks and more information on Tauray.
[A pre-print is available.](https://webpages.tuni.fi/vga/publications/Tauray2022.pdf)

Release Highlights
------------------

* Initial release in the state it was used in the conference publication
* Headless rendering for dataset generation
* Real-time rendering for interactive viewing
* Path tracing renderer
* Real-time Looking Glass Portrait display support
* OpenXR support for VR rendering
* Denoising filters (BMFR, SVGF)
* Multi-GPU support (Linux only)
* DDISH-GI renderer (client + server supported)

Acknowledgements
----------------

This work was supported by European Union’s Horizon 2020 research and innovation
programme under Grant Agreement No 871738 (CPSoSaware) and by the Academy of
Finland under Grant 325530.

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