%0 Conference Paper %1 Becher2022 %A Becher, Michael %A Heinemann, Moritz %A Marmann, Thomas %A Reina, Guido %A Weiskopf, Daniel %A Ertl, Thomas %B Proceedings of the 15th International Symposium on Visual Information Communication and Interaction %C New York, NY, USA %D 2022 %I Association for Computing Machinery %K myown vis(us) visus:reina %P 1–8 %R 10.1145/3554944.3554947 %T Accelerating GPU Rendering of 2D Visualizations Using Resolution Scaling and Temporal Reconstruction %U https://doi.org/10.1145/3554944.3554947 %X Data visualization relies on efficient rendering to allow users to interactively explore and understand their data. However, achieving interactive frame rates is often challenging, especially for high-resolution displays or large datasets. In computer graphics, several methods temporally reconstruct full-resolution images from multiple consecutive lower-resolution frames. Besides providing temporal image stability, they amortize the rendering costs over multiple frames and thus improve the minimum frame rate. We present a method that adopts this idea to accelerate 2D information visualization, without requiring any changes to the rendering itself. By exploiting properties of orthographic projection, our method significantly improves rendering performance while minimizing the loss of image quality during camera manipulation. For static scenes, it quickly converges to the full-resolution image. We discuss the characteristics of our method concerning rendering performance and image quality and the corresponding trade-offs. Finally, we present extensive rendering benchmarks to examine real-world performance for examples of parallel coordinates and scatterplot matrix visualizations, and discuss appropriate application scenarios and contraindications for usage. %@ 9781450398060

@inproceedings{Becher2022, abstract = {Data visualization relies on efficient rendering to allow users to interactively explore and understand their data. However, achieving interactive frame rates is often challenging, especially for high-resolution displays or large datasets. In computer graphics, several methods temporally reconstruct full-resolution images from multiple consecutive lower-resolution frames. Besides providing temporal image stability, they amortize the rendering costs over multiple frames and thus improve the minimum frame rate. We present a method that adopts this idea to accelerate 2D information visualization, without requiring any changes to the rendering itself. By exploiting properties of orthographic projection, our method significantly improves rendering performance while minimizing the loss of image quality during camera manipulation. For static scenes, it quickly converges to the full-resolution image. We discuss the characteristics of our method concerning rendering performance and image quality and the corresponding trade-offs. Finally, we present extensive rendering benchmarks to examine real-world performance for examples of parallel coordinates and scatterplot matrix visualizations, and discuss appropriate application scenarios and contraindications for usage.}, added-at = {2023-02-24T16:07:49.000+0100}, address = {New York, NY, USA}, author = {Becher, Michael and Heinemann, Moritz and Marmann, Thomas and Reina, Guido and Weiskopf, Daniel and Ertl, Thomas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/267ea4d16ac43769531e3e63891c3f056/guidoreina}, booktitle = {Proceedings of the 15th International Symposium on Visual Information Communication and Interaction}, day = 31, doi = {10.1145/3554944.3554947}, interhash = {f4fbf2567210e57a25cee2f47fb4918c}, intrahash = {67ea4d16ac43769531e3e63891c3f056}, isbn = {9781450398060}, keywords = {myown vis(us) visus:reina}, location = {Chur, Switzerland}, month = {10}, pages = {1–8}, publisher = {Association for Computing Machinery}, series = {VINCI '22}, timestamp = {2023-02-24T16:07:49.000+0100}, title = {Accelerating GPU Rendering of 2D Visualizations Using Resolution Scaling and Temporal Reconstruction}, url = {https://doi.org/10.1145/3554944.3554947}, year = 2022 }