new: lithostitched support (dfc opts)

[ebo2022]

This pull request currently adds AST conversion and bytecode/dot/OCL emitters for all Lithostitched dfs except FastNoiseDensityFunction. Eventually, it will also include natives accel for FastNoiseDensityFunction (using the C port of FastNoiseLite) and OpenCL accel support for the region system & biome injectors.

Leaving as a draft while I work on this. Please let me know if I should keep this as a separate addon, or if it's better fit to implement on Lithostitched's side. Otherwise, I'll keep this here for feedback; once done, I'll convert to a regular PR and provide benchmarks + compat tests.

[ishland]

Thanks for the PR. However the project currently don't accept contributions to the OpenCL subproject due to licensing until we figure out how to properly accept contributions to it. And I would like to change how codegen works inside that subproject at some point as well.

Other changes seems good from the first glance. A few problems:

• The new AST nodes shouldn't be guarded behind the availability of the bindings.
• The builtin integrations detection in McToAst doesn't really scale. I'm considering a refactor on that part as well.

I think compatibility with lithostitched should ideally be provided by C2ME, since there's currently no stable API, and providing a stable API for a compiler backend isn't trivial.

[ebo2022]

Thanks for the feedback and update.

Regarding OCL accel: Haven't decided yet, but I'll either keep the changes and wait, or split that subproject into a later PR once licensing is figured out and contributions open.

I'll go ahead and fix the guarding. For integrations handling, I may use a CodeGenRegistry & emitters (slight refactor to generalize the emitters to support dfs -> ast nodes) for now. I won't touch that any further until I see how you refactor it. I don't expect this to be done for quite a while.

[ebo2022]

Narrowing the scope of this PR to non-OpenCL subprojects. At some point, I'll split those changes into another draft PR that can stay open until licensing is figured out.

[ebo2022]

Fast Noise Benchmark Results

CPU: AMD Ryzen 5 3600x
GPU: Nvidia RTX 3060 Ti
16GB DDR4 RAM

Performance impact seems to vary wildly depending on noise type, so the natives accel can be cut if deemed unnecessary

Misc datapacks for parity testing:
c2me-test-perlin-simplex-select-cos.zip
c2me-test-shift.zip
c2me-test-sin-axis-sqrt.zip
c2me-test-fastnoise-cellular.zip

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[ishland]

Generally looks good. A few problems: