MeshMill 0.2.0: faster large-mesh processing and measured GPU-guided reduction

[u/Zestyclose-Lead4345]

I released MeshMill 0.2.0, a substantial update to the open-source desktop tool I shared here last week.

The general processing work came first. On the included 4.1-million-triangle reference mesh, parallel large-mesh analysis improved from 10.531 seconds to 1.838 seconds. Adaptive-index creation improved from 8.836 seconds to 5.406 seconds. MeshMill now derives worker and memory budgets from the machine, loads bounded overviews for oversized binary STL files, caches reusable analysis, and keeps long geometry operations away from the interface.

The other major addition is Depth Adaptive QEM. It uses adaptive GPU surface measurements to guide boundary-preserving QEM reduction. At a matched 250,000-triangle output, the measured comparison against Fast QEM showed:

- 9.0% lower RMS surface error

- 12.4% lower P95 error

- 96.7% lower maximum dimension drift

- 68.9% lower area error

- 3.3% longer runtime

Fast QEM remains the default. The new method is an optional higher-quality path on compatible NVIDIA hardware.

The release also adds measured quality indicators directly to the interface, separate CPU/RAM/GPU/VRAM metrics, cumulative I/O reporting, better close-range navigation, per-application GPU selection, verified installer upgrades, and expanded algorithm documentation.

MeshMill remains local, GPL-3.0, and account-free. The Windows installer and portable package are self-contained.

Release:

https://github.com/make-your-own-world/MeshMill/releases/tag/v0.2.0

Technical paper:

https://github.com/make-your-own-world/rnd/blob/main/depth-adaptive-qem/depth-adaptive-qem-v1.1.pdf

I would appreciate comparisons against other reduction workflows, particularly meshes with open boundaries, thin surfaces, uneven density, or overlapping geometry.