Demo Data from EDBT 2026 / reviewers in the wild / expert
Colin McMurtrie
dblp:207/2306
· 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 |
Cloud and datacenter computing · 77% Performance modeling and evaluation · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management |
0.3 | 1 | 2018 | RM-replay: a high-fidelity tuning, optimization and exploration tool for resource management · SC 2018 |
Performance modeling and evaluation › simulation
simulation-based evaluation |
0.1 | 1 | 2018 | RM-replay: a high-fidelity tuning, optimization and exploration tool for resource management · SC 2018 |
Methods — techniques the papers use, named apart from their topics
replay-based tuning · 0.3optimization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | RM-replay: a high-fidelity tuning, optimization and exploration tool for resource management
Maxime Martinasso, Miguel Gila, Mauro Bianco, Sadaf R. Alam, Colin McMurtrie, Thomas C. Schulthess |
SC | 5 |