# enjiushi/VulkanLearn

<https://repo.masters-masters.com/en/repos/enjiushi/VulkanLearn>

[Home](https://repo.masters-masters.com/en) › [enjiushi](https://repo.masters-masters.com/en/owners/enjiushi) › [VulkanLearn](https://repo.masters-masters.com/en/repos/enjiushi/VulkanLearn)

enjiushi/VulkanLearn has 296 stars on GitHub. Its RepoMasters card: Alpha tier. Render lab built on top of vulkan, aiming to create a real time planet scale…

| Field | Value |
| --- | --- |
| Owner | [enjiushi](https://repo.masters-masters.com/en/owners/enjiushi) |
| Stars | 296 |
| Forks | 16 |
| Language | [C++](https://repo.masters-masters.com/en/languages/c-plus-plus) |
| License | MIT |
| Created | 2017 |
| Topics | vulkan-demos, vulkan-engine, vulkan-compute-shaders, game-engine, atmosphere-scattering, planet-renderer |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [enjiushi/VulkanLearn](https://github.com/enjiushi/VulkanLearn) |

## Repository

Render lab built on top of vulkan, aiming to create a real time planet scale large scene. Also some widely adopted techs are implemented, such as deferred rendering, physical based rendering, bloom, screen space ambient occlusion, screen space reflection, depth of field, skeleton animation, etc

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.