Vulkan-Samples VS flash-attention-minimal

Vulcan is a driver-level API. It competes with DirectX and OpenGL.

CUDA is a language you write kernels. It competes with OpenAI's Triton language.

Here's what CUDA looks like: https://github.com/tspeterkim/flash-attention-minimal/blob/m...

This is what Triton looks like: https://triton-lang.org/main/getting-started/tutorials/06-fu...

By contrast Vulcan looks like this: https://github.com/KhronosGroup/Vulkan-Samples/blob/main/sam...

(It's true to some extent that maybe you could use Vulcan shaders to write deep learning kernels, maybe? I'm not aware of anyone doing it though)

Hi, i'm looking into descriptor indexing and was looking at the Vulkan-Samples repo. I finally thought i understood how the set binding invalidation works (like a stack?). In the code below both the non_uniform_indexing pipeline and the update_after_bind pipeline use the immutable sampler descriptor in their fragment shader. But since the descriptor set = 0 is rebound, won't the immutable sampler in set = 1 from the "non_uniform_indexing" pipeline be "disturbed" and have to be rebound?

and see if it works.

[1] https://github.com/KhronosGroup/Vulkan-Samples/blob/main/sam...

In this new sample, we see how to incorporate the Vulkan extension VK_EXT_mesh_shader and introduce per primitive culling in a mesh shader. https://github.com/KhronosGroup/Vulkan-Samples/tree/main/samples/extensions/mesh_shader_culling

Also beginner here, I think you can learn other's codes to get a better understanding of the API by learning how others can abstract these concept into higher level. They're many great projects out there like Google's pbr renderer filament https://github.com/google/filament, AMD's gltf sample https://github.com/GPUOpen-LibrariesAndSDKs/glTFSample and also as many suggested, the Sascha Willems's repos https://github.com/SaschaWillems and the official sample https://github.com/KhronosGroup/Vulkan-Samples

Another way I saw some projects start was by using example base classes (either Sascha Willems' implementations or the framework used by Khronos Samples).

Vulcan is a driver-level API. It competes with DirectX and OpenGL.

CUDA is a language you write kernels. It competes with OpenAI's Triton language.

Here's what CUDA looks like: https://github.com/tspeterkim/flash-attention-minimal/blob/m...

This is what Triton looks like: https://triton-lang.org/main/getting-started/tutorials/06-fu...

By contrast Vulcan looks like this: https://github.com/KhronosGroup/Vulkan-Samples/blob/main/sam...

(It's true to some extent that maybe you could use Vulcan shaders to write deep learning kernels, maybe? I'm not aware of anyone doing it though)