EDBT 2026 Demo / reviewers in the wild / expert
Huu Tan Nguyen
dblp:194/7115
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-4009-1659ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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 · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › software visualization
performance visualization |
0.5 | 1 | 2021 | Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow · IEEE Trans. Vis. Comput. Graph. 2021 |
Parallel and multicore computing › parallel computing › parallel application performance
parallel program performance analysis |
0.1 | 1 | 2021 | Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow · IEEE Trans. Vis. Comput. Graph. 2021 |
Methods — techniques the papers use, named apart from their topics
flow-based visual metaphor · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlowabstractCalling context trees (CCTs) couple performance metrics with call paths, helping understand the execution and performance of parallel programs. To identify performance bottlenecks, programmers and performance analysts visually explore CCTs to form and validate hypotheses regarding degraded performance. However, due to the complexity of parallel programs, existing visual representations do not scale to applications running on a large number of processors. We present CallFlow, an interactive visual analysis tool that provides a high-level overview of CCTs together with semantic refinement operations to progressively explore CCTs. Using a flow-based metaphor, we visualize a CCT by treating execution time as a resource spent during the call chain, and demonstrate the effectiveness of our design with case studies on large-scale, production simulation codes. Huu Tan Nguyen, Abhinav Bhatele, Suraj P. Kesavan, Harsh Bhatia, Todd Gamblin, Kwan-Liu Ma, Peer-Timo Bremer |
IEEE Trans. Vis. Comput. Graph. | 1 |