Rework of compute encoder abstraction

The current plan is to more or less follow the wgpu/wgpu-hal approach. In the mux/backend layer (which corresponds fairly strongly to wgpu-hal), there isn't explicit construction of a compute encoder, but there are new methods for beginning and ending a compute pass. At the hub layer (which corresponds to wgpu) there will be a ComputeEncoder object.

That said, there will be some differences. The WebGPU "end" method on a compute encoder is implemented in wgpu as Drop, and that is not ideal. Also, the wgpu-hal approach to timer queries (still based on write_timestamp) is not up to the task of Metal timer queries, where the query offsets have to be specified at compute encoder creation. That's why there are different projects :)

WIP: current state is that stage-style queries work on Apple Silicon, but non-Metal backends are broken, and piet-gpu is not yet updated to use new API.
7 files changed
tree: f409a16a817b5cbc8987527e932317e8843079ae
  1. doc/
  2. piet-gpu/
  3. piet-gpu-derive/
  4. piet-gpu-hal/
  5. piet-gpu-types/
  6. tests/
  7. .gitattributes
  8. .gitignore
  9. Cargo.lock
  10. Cargo.toml


This repo contains the new prototype for a new compute-centric 2D GPU renderer.

It succeeds the previous prototype, piet-metal.


The main goal is to answer research questions about the future of 2D rendering:

  • Is a compute-centered approach better than rasterization (Direct2D)? How much so?

  • To what extent do “advanced” GPU features (subgroups, descriptor arrays) help?

  • Can we improve quality and extend the imaging model in useful ways?

Another goal is to explore a standards-based, portable approach to GPU compute.

Blogs and other writing

Much of the research progress on piet-gpu is documented in blog entries. See doc/ for pointers to those.

There is a much larger and detailed vision that explains the longer-term goals of the project, and how we might get there.

Why not gfx-hal?

It makes a lot of sense to use gfx-hal, as it addresses the ability to write kernel and runtime code once and run it portably. But in exploring it I‘ve found some points of friction, especially in using more “advanced” features. To serve the research goals, I’m enjoying using Vulkan directly, through ash, which I've found does a good job tracking Vulkan releases. One example is experimenting with VK_EXT_subgroup_size_control.

The hal layer in this repo is strongly inspired by gfx-hal, but with some differences. One is that we‘re shooting for a compile-time pipeline to generate GPU IR on DX12 and Metal, while gfx-hal ships SPIRV-Cross in the runtime. To access Shader Model 6, that would also require bundling DXC at runtime, which is not yet implemented (though it’s certainly possible).

Why not wgpu?

The case for wgpu is also strong, but it‘s even less mature. I’d love to see it become a solid foundation, at which point I'd use it as the main integration with Druid.

In short, the goal is to facilitate the research now, collect the data, and then use that to choose a best path for shipping later.

License and contributions.

The piet-gpu project is dual-licensed under both Apache 2.0 and MIT licenses.

In addition, the shaders are provided under the terms of the Unlicense. The intent is for this research to be used in as broad a context as possible.

The dx12 backend was adapted from piet-dx12 by Brian Merchant.

Contributions are welcome by pull request. The Rust code of conduct applies.