Accurate and Memory-Efficient GPU Ray-Casting Algorithm for Volume Rendering Unstructured Grid Data
| dc.contributor.author | Gu, Gibeom | en_US |
| dc.contributor.author | Kim, Duksu | en_US |
| dc.contributor.editor | Madeiras Pereira, João and Raidou, Renata Georgia | en_US |
| dc.date.accessioned | 2019-06-02T18:21:28Z | |
| dc.date.available | 2019-06-02T18:21:28Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | We present a novel GPU ray-casting algorithm for volume rendering unstructured grid data. We employ the per-pixel intersection list to guarantee accurate results for non-convex meshes. For efficient memory access for the lists on the GPU, we represent the intersection lists for all faces as an array. To increase ray-coherency in a thread block and improve memory access efficiency, we propose an image-tile based ray distribution method. Also, we found that a prior approach using a per-thread local buffer to reduce redundant computation is not proper for recent GPUs. Instead, we use an on-demand calculation strategy that achieves much better performance even when it allows duplicate computation. With a GPU, our method achieved up to 36.5 times higher performance for the ray-casting process, and 18.1 times higher performance for the entire volume rendering, compared with the Bunyk algorithm using a CPU core. Also, our approach showed up to 8.2 times higher performance than a GPU-based cell projection method while generating more accurate rendering results. | en_US |
| dc.description.sectionheaders | Posters | |
| dc.description.seriesinformation | EuroVis 2019 - Posters | |
| dc.identifier.doi | 10.2312/eurp.20191150 | |
| dc.identifier.isbn | 978-3-03868-088-8 | |
| dc.identifier.pages | 77-79 | |
| dc.identifier.uri | https://doi.org/10.2312/eurp.20191150 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurp20191150 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Accurate and Memory-Efficient GPU Ray-Casting Algorithm for Volume Rendering Unstructured Grid Data | en_US |
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