Browsing by Author "Zellmann, S."

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Open Access
Hybrid image-/data-parallel rendering using island parallelism
(Institute of Electrical and Electronics Engineers, 2022-12-06) Zellmann, S.; Wald, I.; Barbosa, J.; Demirci, Serkan; Şahıstan, Alper; Güdükbay, Uğur
In parallel ray tracing, techniques fall into one of two camps: image-parallel techniques aim at increasing frame rate by replicating scene data across nodes and splitting the rendering work across different ranks, and data-parallel techniques aim at increasing the size of the model that can be rendered by splitting the model across multiple ranks, but typically cannot scale much in frame rate. We propose and evaluate a hybrid approach that combines the advantages of both by splitting a set of N x M ranks into M islands of N ranks each and using data-parallel rendering within each island and image parallelism across islands. We discuss the integration of this concept into four wildly different parallel renderers and evaluate the efficacy of this approach based on multiple different data sets.
Open Access
State-of-the-art in large-scale volume visualization beyond structured data
(Eurographics and John Wiley & Sons Ltd., 2023-06-27) Sarton, J.; Zellmann, S.; Demirci, Serkan; Güdükbay, Uğur; Alexandre-Barff, W.; Lucas, L.; Dischler, J. M.; Wesner, S.; Wald, I.; Alliez, Pierre; Wimmer, Michael
Volume data these days is usually massive in terms of its topology, multiple fields, or temporal component. With the gap between compute and memory performance widening, the memory subsystem becomes the primary bottleneck for scientific volume visualization. Simple, structured, regular representations are often infeasible because the buses and interconnects involved need to accommodate the data required for interactive rendering. In this state-of-the-art report, we review works focusing on large-scale volume rendering beyond those typical structured and regular grid representations. We focus primarily on hierarchical and adaptive mesh refinement representations, unstructured meshes, and compressed representations that gained recent popularity. We review works that approach this kind of data using strategies such as out-of-core rendering, massive parallelism, and other strategies to cope with the sheer size of the ever-increasing volume of data produced by today's supercomputers and acquisition devices. We emphasize the data management side of large-scale volume rendering systems and also include a review of tools that support the various volume data types discussed.
Open Access
Visual analysis of large multi-dield AMR data on GPUs using interactive volume lines
(IEEE, 2023-12-20) Zellmann, S.; Demirci, Serkan; Güdükbay, Uğur
To visually compare ensembles of volumes, dynamic volume lines (DVLs) represent each ensemble member as a 1D polyline. To compute these, the volume cells are sorted on a space-filling curve and scaled by the ensemble’s local variation. The resulting 1D plot can augment or serve as an alternative to a 3D volume visualization free of visual clutter and occlusion. Interactively computing DVLs is challenging when the data is large, and the volume grid is not structured/regular, as is often the case with computational fluid dynamics simulations. We extend DVLs to support large-scale, multifield adaptive mesh refinement (AMR) data that can be explored interactively. Our GPU-based system updates the DVL representation whenever the data or the alpha transfer function changes. We demonstrate and evaluate our interactive prototype using large AMR volumes from astrophysics simulations.