Kiln is an end-to-end system for rendering large volumetric datasets in the browser using WebGPU.
It covers the full pipeline: data preprocessing, HTTP streaming, decompression, memory virtualization, and rendering — making multi-gigabyte CT scans and scientific volumes interactive in a standard browser tab using a contemporary tech stack.
The source code and docs are available here: https://github.com/MPanknin/kiln-render
m_panknin•2h ago
WebGPU volume rendering examples do exist, but they all assume fully GPU-resident datasets — the entire volume is uploaded to VRAM upfront, which caps practical dataset sizes at a few hundred megabytes at best.
Kiln overcomes this limitation: it treats GPU memory as a fixed-size cache and streams only the bricks the current view actually needs, making gigabyte-scale datasets viable in the browser.
Virtual texturing and out-of-core streaming are well-established in native graphics, but there is almost no prior WebGPU-native implementation of these techniques applied to volumetric data.
WDYT?