EDBT 2026 Demo / reviewers in the wild / expert
Glenn Lupton
dblp:51/3913
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
2 papers |
Rendering · 89% Visualization and visual analytics · 11% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
GPUs and heterogeneous computing · 67% High-performance computing · 33% |
Topics — the 9 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering
global illumination |
0.1 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
Rendering › volume rendering
heterogeneous participating media |
0.1 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
Rendering › participating media rendering
multiple scattering |
0.1 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
Rendering
radiative transfer |
0.1 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
Visualization and visual analytics › scientific visualization
parallel visualization |
0.1 | 1 | 2006 | Visualization - Visualization using Linux clusters · SC 2006 |
GPUs and heterogeneous computing › multi-GPU computing
GPU cluster |
0.0 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
GPUs and heterogeneous computing
GPU computing |
0.0 | 1 | 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with Bootstrapping · IEEE Trans. Vis. Comput. Graph. 2011 |
High-performance computing › scientific visualization
large-scale data visualization |
0.0 | 1 | 2006 | Visualization - Visualization using Linux clusters · SC 2006 |
High-performance computing
scientific computing systems |
0.0 | 1 | 2006 | Visualization - Visualization using Linux clusters · SC 2006 |
Methods — techniques the papers use, named apart from their topics
iterative refinement · 0.2face-centered cubic grid · 0.2bootstrapping · 0.2CUDA · 0.2multi-tile display · 0.1distributed rendering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Parallel Iteration to the Radiative Transport in Inhomogeneous Media with BootstrappingabstractThis paper presents a fast parallel method to solve the radiative transport equation in inhomogeneous participating media. We apply a novel approximation scheme to find a good initial guess for both the direct and scattered components. Then, the initial approximation is used to bootstrap an iterative multiple scattering solver, i.e., we let the iteration concentrate just on the residual problem. This kind of bootstrapping makes the volumetric source approximation more uniform, thus it helps to reduce the discretization artifacts and improves the efficiency of the parallel implementation. The iterative refinement is executed on a face-centered cubic grid. The implementation is based on CUDA and runs on the GPU. For large volumes that do not fit into the GPU memory, we also consider the implementation on a GPU cluster, where the volume is decomposed to blocks according to the available GPU nodes. We show how the communication bottleneck can be avoided in the cluster implementation by not exchanging the boundary conditions in every iteration step. In addition to light photons, we also discuss the generalization of the method to γ-photons that are relevant in medical simulation. László Szirmay-Kalos, Gabor Liktor, Tamás Umenhoffer, Balázs Tóth, Shree Kumar, Glenn Lupton |
IEEE Trans. Vis. Comput. Graph. | 6 |
| 2006 | Visualization - Visualization using Linux clustersabstractClusters of commodity Linux systems are being used to scale-up image resolution and data set capacity to meet the needs for visualizing the vast amounts of data generated by high-performance computing systems. As with computational problems, visualization problems can be distributed so that multiple processors and graphics cards can work on them in parallel. Clusters ranging from a handful of nodes to well over a hundred are being used to drive multi-tile displays with tens of millions of pixels and to apply many nodes to each tile of a display. The decreasing cost and increasing performance of graphics cards and commodity networking make this an attractive approach with much promise.This BOF will have some short presentations describing approaches to scalable visualization being used by applications and software packages, followed by an open discussion of these topics. Glenn Lupton |
SC | 1 |