Browsing by Author "Reina, Guido"
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Item Efficient Sphere Rendering Revisited(The Eurographics Association, 2023) Gralka, Patrick; Reina, Guido; Ertl, Thomas; Bujack, Roxana; Pugmire, David; Reina, GuidoGlyphs are an intuitive way of displaying the results of atomistic simulations, usually as spheres. Raycasting of camera-aligned billboards is considered the state-of-the-art technique to render large sets of spheres in a rasterization-based pipeline since the approach was first proposed by Gumhold. Over time various acceleration techniques have been proposed, such as the rendering of point primitives as billboards, which are trivial to rasterize and avoid a high workload in the vertex pipeline. Other techniques attempt to optimize data upload and access patterns in shader programs, both relevant aspects for dynamic data. Recent advances in graphics hardware raise the question of whether these optimizations are still valid. We evaluate several rendering and data access scheme combinations on real-world datasets and derive recommendations for efficient rasterization-based sphere rendering.Item Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces(The Eurographics Association, 2019) Rau, Tobias; Zahn, Sebastian; Krone, Michael; Reina, Guido; Ertl, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata GeorgiaDepictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule's potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible.Item Parallel Compositing of Volumetric Depth Images for Interactive Visualization of Distributed Volumes at High Frame Rates(The Eurographics Association, 2023) Gupta, Aryaman; Incardona, Pietro; Brock, Anton; Reina, Guido; Frey, Steffen; Gumhold, Stefan; Günther, Ulrik; Sbalzarini, Ivo F.; Bujack, Roxana; Pugmire, David; Reina, GuidoWe present a parallel compositing algorithm for Volumetric Depth Images (VDIs) of large three-dimensional volume data. Large distributed volume data are routinely produced in both numerical simulations and experiments, yet it remains challenging to visualize them at smooth, interactive frame rates. VDIs are view-dependent piecewise constant representations of volume data that offer a potential solution. They are more compact and less expensive to render than the original data. So far, however, there is no method for generating VDIs from distributed data. We propose an algorithm that enables this by sort-last parallel generation and compositing of VDIs with automatically chosen content-adaptive parameters. The resulting composited VDI can then be streamed for remote display, providing responsive visualization of large, distributed volume data.Item PGV 2023: Frontmatter(The Eurographics Association, 2023) Bujack, Roxana; Pugmire, David; Reina, Guido; Bujack, Roxana; Pugmire, David; Reina, GuidoItem VisGap 2021: Frontmatter(The Eurographics Association, 2021) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, ThomasItem VisGap 2023: Frontmatter(The Eurographics Association, 2023) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, ThomasItem Visual Analysis of Two‐Phase Flow Displacement Processes in Porous Media(© 2022 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2022) Frey, Steffen; Scheller, Stefan; Karadimitriou, Nikolaos; Lee, Dongwon; Reina, Guido; Steeb, Holger; Ertl, Thomas; Hauser, Helwig and Alliez, PierreWe developed a new visualization approach to gain a better understanding of the displacement of one fluid phase by another in porous media. This is based on a recent experimental parameter study with varying capillary numbers and viscosity ratios. We analyse the temporal evolution of characteristic values in this two‐phase flow scenario and discuss how to directly compare experiments across different temporal scales. To enable spatio‐temporal analysis, we introduce a new abstract visual representation showing which paths through the porous medium were occupied and for how long. These transport networks allow to assess the impact of different acting forces and they are designed to yield expressive comparability and linking to the experimental parameter space both supported by additional visual cues. This joint work of porous media experts and visualization researchers yields new insights regarding two‐phase flow on the microscale, and our visualization approach contributes towards the overarching goal of the domain scientists to characterize porous media flow based on capillary numbers and viscosity ratios.Item Visual Representation of Region Transitions in Multi-dimensional Parameter Spaces(The Eurographics Association, 2019) Fernandes, Oliver; Frey, Steffen; Reina, Guido; Ertl, Thomas; Agus, Marco and Corsini, Massimiliano and Pintus, RuggeroWe propose a novel visual representation of transitions between homogeneous regions in multi-dimensional parameter space. While our approach is generally applicable for the analysis of arbitrary continuous parameter spaces, we particularly focus on scientific applications, like physical variables in simulation ensembles. To generate our representation, we use unsupervised learning to cluster the ensemble members according to their mutual similarity. In doing this, clusters are sorted such that similar clusters are located next to each other. We then further partition the clusters into connected regions with respect to their location in parameter space. In the visualization, the resulting regions are represented as glyphs in a matrix, indicating parameter changes which induce a transition to another region. To unambiguously associate a change of data characteristics to a single parameter, we specifically isolate changes by dimension. With this, our representation provides an intuitive visualization of the parameter transitions that influence the outcome of the underlying simulation or measurement. We demonstrate the generality and utility of our approach on diverse types of data, namely simulations from the field of computational fluid dynamics and thermodynamics, as well as an ensemble of raycasting performance data.