This is the implementation of the GPU-parallel marching cubes algorithm for block-compressed data sets described in "Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?" by Will Usher and Valerio Pascucci appearing at LDAV 2020. Please see the paper and the supplemental video for more details.
This code got blocked by the missing GPULimits
API for WebGPU, Chrome Canary recently started
enforcing the minimum spec limits on storage buffers that this code exceeds, but didn't add
the API to request higher limits (which are available on desktop and laptop hardware).
Please see https://bugs.chromium.org/p/dawn/issues/detail?id=519 for some additional
information.
Note: I think this is now resolved, however the application also makes use of dynamic storage buffers which are also now temporarily disabled in Chrome. See issue 429
A live demo will be put online along with final code polish and updates done once this issue is resolved.
The data sets shown are available on the Open SciVis Data Sets page.