IEEE VIS 2024 Content: “Nanomatrix: Scalable Construction of Crowded Biological Environments”

“Nanomatrix: Scalable Construction of Crowded Biological Environments”

Ruwayda Alharbi -

Ondˇrej Strnad -

Tobias Klein -

Ivan Viola -

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Room: Bayshore I

2024-10-16T14:27:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T14:27:00Z
Exemplar figure, described by caption below
Several populated SARS-CoV-2 virions over Red blood cell particles. The fully textured proxy geometries with partially populated atomistic details are presented in the top-left part, whereas the bottom-right part showcases the continuous Wang tiling used for placement of atomistic details.
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Keywords

Interactive rendering, view-guided scene construction, biological data, hardware ray tracing

Abstract

We present a novel method for the interactive construction and rendering of extremely large molecular scenes, capable of representing multiple biological cells in atomistic detail. Our method is tailored for scenes, which are procedurally constructed, based on a given set of building rules. Rendering of large scenes normally requires the entire scene available in-core, or alternatively, it requires out-of-core management to load data into the memory hierarchy as a part of the rendering loop. Instead of out-of-core memory management, we propose to procedurally generate the scene on-demand on the fly. The key idea is a positional- and view-dependent procedural scene-construction strategy, where only a fraction of the atomistic scene around the camera is available in the GPU memory at any given time. The atomistic detail is populated into a uniform-space partitioning using a grid that covers the entire scene. Most of the grid cells are not filled with geometry, only those are populated that are potentially seen by the camera. The atomistic detail is populated in a compute shader and its representation is connected with acceleration data structures for hardware ray-tracing of modern GPUs. Objects which are far away, where atomistic detail is not perceivable from a given viewpoint, are represented by a triangle mesh mapped with a seamless texture, generated from the rendering of geometry from atomistic detail. The algorithm consists of two pipelines, the construction-compute pipeline, and the rendering pipeline, which work together to render molecular scenes at an atomistic resolution far beyond the limit of the GPU memory containing trillions of atoms. We demonstrate our technique on multiple models of SARS-CoV-2 and the red blood cell.