Visualization of large Non-trivially partitioned unstructured data with native distribution on high-performance computing systems
buir.contributor.author | Demirci, Serkan | |
buir.contributor.author | Güdükbay, Uğur | |
buir.contributor.orcid | Demirci, Serkan|0000-0001-8805-5310 | |
buir.contributor.orcid | Güdükbay, Uğur|0000-0003-2462-6959 | |
dc.citation.epage | 14 | |
dc.citation.spage | 1 | |
dc.contributor.author | Sahistan, Alper | |
dc.contributor.author | Demirci, Serkan | |
dc.contributor.author | Wald, Ingo | |
dc.contributor.author | Zellmann, Stefan | |
dc.contributor.author | Barbosa, João | |
dc.contributor.author | Morrical, Nate | |
dc.contributor.author | Güdükbay, Uğur | |
dc.date.accessioned | 2025-02-27T07:52:29Z | |
dc.date.available | 2025-02-27T07:52:29Z | |
dc.date.issued | 2024-01-15 | |
dc.department | Department of Computer Engineering | |
dc.description.abstract | Interactively visualizing large finite element simulation data on High-Performance Computing (HPC) systems poses several difficulties. Some of these relate to unstructured data, which, even on a single node, is much more expensive to render compared to structured volume data. Worse yet, in the data parallel rendering context, such data with highly non-convex spatial domain boundaries will cause rays along its silhouette to enter and leave a given rank's domains at different distances. This straddling, in turn, poses challenges for both ray marching, which usually assumes successive elements to share a face, and compositing, which usually assumes a single fragment per pixel per rank. We holistically address these issues using a combination of three inter-operating techniques: first, we use a highly optimized GPU ray marching technique that, given an entry point, can march a ray to its exit point with highperformance by exploiting an exclusive-or (XOR) based compaction scheme. Second, we use hardware-accelerated ray tracing to efficiently find the proper entry points for these marching operations. Third, we use a “deep” compositing scheme to properly handle cases where different ranks' ray segments interleave in depth. We use GPU-to-GPU remote direct memory access (RDMA) to achieve interactive frame rates of 10-15 frames per second and higher for our motivating use case, the Fun3D NASA Mars Lander. | |
dc.identifier.doi | 10.1109/TVCG.2024.3427335 | |
dc.identifier.eissn | 1941-0506 | |
dc.identifier.issn | 1077-2626 | |
dc.identifier.uri | https://hdl.handle.net/11693/116903 | |
dc.language.iso | English | |
dc.publisher | IEEE | |
dc.relation.isversionof | https://dx.doi.org/10.1109/TVCG.2024.3427335 | |
dc.rights | CC BY 4.0 DEED (Attribution 4.0 International) | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source.title | IEEE Transactions on Visualization and Computer Graphics | |
dc.subject | Ray-marching | |
dc.subject | Volume rendering | |
dc.subject | Scientific visualization | |
dc.subject | Unstructured volumetric mesh | |
dc.subject | Deep compositing | |
dc.subject | Sort-last compositing | |
dc.title | Visualization of large Non-trivially partitioned unstructured data with native distribution on high-performance computing systems | |
dc.type | Article |
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