EDBT 2026 Demo / reviewers in the wild / expert
Ankur Mahesh
dblp:228/6700
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Environmental and earth informatics · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing
large-scale training |
0.3 | 1 | 2018 | Exascale deep learning for climate analytics · SC 2018 |
Environmental and earth informatics › climate science
climate data analysis |
0.1 | 1 | 2018 | Exascale deep learning for climate analytics · SC 2018 |
Methods — techniques the papers use, named apart from their topics
distributed training · 0.7deep learning · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Exascale deep learning for climate analytics
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston |
SC | 7 |