Rendering huge biological scenes with atomistic detail presents a significant challenge in molecular visualization due to the memory limitations inherent in traditional rendering approaches. In this paper, we propose a novel method for the interactive rendering of massive molecular scenes based on hardware-accelerated ray tracing. Our approach circumvents GPU memory constraints by introducing virtual instantiation of full-detail scene elements. Using instancing significantly reduces memory consumption while preserving the full atomistic detail of scenes comprising trillions of atoms, with interactive rendering performance and completely free user exploration. We utilize coarse meshes as proxy geometries to approximate the overall shape of biological compartments, and access all atomistic detail dynamically during ray tracing. We do this via a novel adaptive technique utilizing a volumetric shell layer of prisms extruded around proxy geometry triangles, and a virtual volume grid for the interior of each compartment. Our algorithm scales to enormous molecular scenes with minimal memory consumption and the potential to accommodate even larger scenes. Our method also supports advanced effects such as clipping planes and animations. We demonstrate the efficiency and scalability of our approach by rendering tens of instances of Red Blood Cell and SARS-CoV-2 models theoretically containing more than 20 trillion atoms.

中文翻译：

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纳米宇宙：结构细节的虚拟实例和自适应壳映射

由于传统渲染方法固有的内存限制，渲染具有原子细节的巨大生物场景对分子可视化提出了重大挑战。在本文中，我们提出了一种基于硬件加速光线追踪的大规模分子场景交互式渲染的新方法。我们的方法通过引入全细节场景元素的虚拟实例化来规避 GPU 内存限制。使用实例化可以显着减少内存消耗，同时保留包含数万亿个原子的场景的完整原子细节，并具有交互式渲染性能和完全免费的用户探索。我们利用粗网格作为代理几何形状来近似生物区室的整体形状，并在光线追踪过程中动态访问所有原子细节。我们通过一种新颖的自适应技术来实现这一点，该技术利用围绕代理几何三角形挤压的棱镜体积壳层，以及每个隔间内部的虚拟体积网格。我们的算法可以以最小的内存消耗扩展到巨大的分子场景，并且有可能容纳更大的场景。我们的方法还支持高级效果，例如剪切平面和动画。我们通过渲染数十个理论上包含超过 20 万亿个原子的红细胞和 SARS-CoV-2 模型实例，展示了我们方法的效率和可扩展性。