Demo Data from EDBT 2026 / reviewers in the wild / expert
Peter E. Vincent
dblp:01/9486
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-1314-8827ORCID · reported
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 · 1 since 2021
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
1 paper |
Visualization and visual analytics · 50% Geometric modeling and processing · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 91% GPUs and heterogeneous computing · 9% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › topological data analysis
contour tree |
0.6 | 1 | 2022 | Identification and Classification of Off-Vertex Critical Points for Contour Tree Construction on Unstructured Meshes of Hexahedra · IEEE Trans. Vis. Comput. Graph. 2022 |
Geometric modeling and processing › mesh generation
hexahedral mesh |
0.6 | 1 | 2022 | Identification and Classification of Off-Vertex Critical Points for Contour Tree Construction on Unstructured Meshes of Hexahedra · IEEE Trans. Vis. Comput. Graph. 2022 |
Geometric modeling and processing
mesh processing |
0.6 | 1 | 2022 | Identification and Classification of Off-Vertex Critical Points for Contour Tree Construction on Unstructured Meshes of Hexahedra · IEEE Trans. Vis. Comput. Graph. 2022 |
Visualization and visual analytics
topological data analysis |
0.6 | 1 | 2022 | Identification and Classification of Off-Vertex Critical Points for Contour Tree Construction on Unstructured Meshes of Hexahedra · IEEE Trans. Vis. Comput. Graph. 2022 |
Computational science and engineering › computational fluid dynamics
turbulence simulation |
0.2 | 1 | 2016 | Towards green aviation with python at petascale · SC 2016 |
High-performance computing › scientific computing systems
computational fluid dynamics |
0.2 | 1 | 2016 | Towards green aviation with python at petascale · SC 2016 |
High-performance computing › large-scale simulation
petascale simulation |
0.2 | 1 | 2016 | Towards green aviation with python at petascale · SC 2016 |
High-performance computing
unstructured mesh computation |
0.2 | 1 | 2016 | Towards green aviation with python at petascale · SC 2016 |
Methods — techniques the papers use, named apart from their topics
gradient analysis · 0.6asymptotic decider · 0.6runtime code generation · 0.5python-based solver · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Identification and Classification of Off-Vertex Critical Points for Contour Tree Construction on Unstructured Meshes of HexahedraabstractThe topology of isosurfaces changes at isovalues of critical points, making such points an important feature when building contour trees or Morse-Smale complexes. Hexahedral elements with linear interpolants can contain additional off-vertex critical points in element bodies and on element faces. Moreover, a point on the face of a hexahedron which is critical in the element-local context is not necessarily critical in the global context. Weber et al. (2002) introduce a method to determine whether critical points on faces are also critical in the global context, based on the gradient of the asymptotic decider (G. M. Nielson and B. Hamann) (1991) in each element that shares the face. However, as defined, the method of Weber et al. contains an error, and can lead to incorrect results. In this work we correct the error. Marius K. Koch, Paul H. J. Kelly, Peter E. Vincent |
IEEE Trans. Vis. Comput. Graph. | 3 |
| 2016 | Towards green aviation with python at petascaleabstractAccurate simulation of unsteady turbulent flow is critical for improved design of greener aircraft that are quieter and more fuel-efficient. We demonstrate application of PyFR, a Python based computational fluid dynamics solver, to petascale simulation of such flow problems. Rationale behind algorithmic choices, which offer increased levels of accuracy and enable sustained computation at up to 58% of peak DP-FLOP/s on unstructured grids, will be discussed in the context of modern hardware. A range of software innovations will also be detailed, including use of runtime code generation, which enables PyFR to efficiently target multiple platforms, including heterogeneous systems, via a single implementation. Finally, results will be presented from a fullscale simulation of flow over a low-pressure turbine blade cascade, along with weak/strong scaling statistics from the Piz Daint and Titan supercomputers, and performance data demonstrating sustained computation at up to 13.7 DP-PFLOP/s. Peter E. Vincent, Freddie D. Witherden, Brian C. Vermeire, Jin Seok Park, Arvind Iyer |
SC | 1 |