EDBT 2026 Demo / reviewers in the wild / expert
David Guibert
dblp:83/9591
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-5533-8867ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
interactive visualization |
0.1 | 1 | 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared Memory · IEEE Trans. Vis. Comput. Graph. 2012 |
Visualization and visual analytics
scientific visualization |
0.1 | 1 | 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared Memory · IEEE Trans. Vis. Comput. Graph. 2012 |
High-performance computing
computational steering |
0.1 | 1 | 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared Memory · IEEE Trans. Vis. Comput. Graph. 2012 |
High-performance computing › scientific visualization
in situ visualization and analysis |
0.1 | 1 | 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared Memory · IEEE Trans. Vis. Comput. Graph. 2012 |
High-performance computing
parallel i/o |
0.0 | 1 | 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared Memory · IEEE Trans. Vis. Comput. Graph. 2012 |
Methods — techniques the papers use, named apart from their topics
distributed shared memory · 0.3MPI · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Fast Sky to Sky Interpolation for Radio Interferometric ImagingabstractReconstruction of radio interferometric images re-quires the processing of data in Fourier space that dot not have regular coordinates, preventing direct use of the Fast Fourier Transform. The most common solution is to rely on interpolation algorithms, called gridding, that are computationally expensive. In this paper, we propose an algorithmic reinterpretation, named sky to sky method, to reduce the computation cost of the gridding operation and its adjoint, the degridding, when used successively. We analyze the impact of interpolation step size regarding the computation cost and the reconstruction error. We also illustrate this optimization on a full reconstruction with gradient descent and CLEAN algorithm. Finally, we obtain acceleration factors between 1.2 and 16.4 without additional approximation. Nicolas Monnier, François Orieux, Nicolas Gac, Cyril Tasse, Erwan Raffin, David Guibert |
ICIP | 6 |
| 2012 | Parallel Computational Steering for HPC Applications Using HDF5 Files in Distributed Shared MemoryabstractInterfacing a GUI driven visualization/analysis package to an HPC application enables a supercomputer to be used as an interactive instrument. We achieve this by replacing the IO layer in the HDF5 library with a custom driver which transfers data in parallel between simulation and analysis. Our implementation using ParaView as the interface, allows a flexible combination of parallel simulation, concurrent parallel analysis, and GUI client, either on the same or separate machines. Each MPI job may use different core counts or hardware configurations, allowing fine tuning of the amount of resources dedicated to each part of the workload. By making use of a distributed shared memory file, one may read data from the simulation, modify it using ParaView pipelines, write it back, to be reused by the simulation (or vice versa). This allows not only simple parameter changes, but complete remeshing of grids, or operations involving regeneration of field values over the entire domain. To avoid the problem of manually customizing the GUI for each application that is to be steered, we make use of XML templates that describe outputs from the simulation (and inputs back to it) to automatically generate GUI controls for manipulation of the simulation. John Biddiscombe, Jérome Soumagne, Guillaume Oger, David Guibert, Jean-Guillaume Piccinali |
IEEE Trans. Vis. Comput. Graph. | 4 |