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|a 10.1109/TVCG.2024.3427335
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|a eng
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| 100 |
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|a Sahistan, Alper
|e verfasserin
|4 aut
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|a Visualization of Large Non-Trivially Partitioned Unstructured Data with Native Distribution on High-Performance Computing Systems
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|c 2024
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|a Text
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|a Date Revised 15.07.2024
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|a published: Print-Electronic
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|a Citation Status Publisher
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|a 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
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|a Journal Article
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|a Demirci, Serkan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wald, Ingo
|e verfasserin
|4 aut
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| 700 |
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|a Zellmann, Stefan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Barbosa, Joao
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Morrical, Nate
|e verfasserin
|4 aut
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| 700 |
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|a Gudukbay, Ugur
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g PP(2024) vom: 15. Juli
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|x 1941-0506
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|u http://dx.doi.org/10.1109/TVCG.2024.3427335
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