Demo Data from EDBT 2026 / reviewers in the wild / expert
Kumaraguru Palaniswamy
dblp:304/0186
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Energy-efficient computing · 67% Processor architecture and microarchitecture · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture
microprocessor design |
0.5 | 1 | 2021 | APOLLO: An Automated Power Modeling Framework for Runtime Power Introspection in High-Volume Commercial Microprocessors · MICRO 2021 |
Energy-efficient computing
power management |
0.5 | 1 | 2021 | APOLLO: An Automated Power Modeling Framework for Runtime Power Introspection in High-Volume Commercial Microprocessors · MICRO 2021 |
Energy-efficient computing
power modeling |
0.5 | 1 | 2021 | APOLLO: An Automated Power Modeling Framework for Runtime Power Introspection in High-Volume Commercial Microprocessors · MICRO 2021 |
Methods — techniques the papers use, named apart from their topics
automated power modeling · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | APOLLO: An Automated Power Modeling Framework for Runtime Power Introspection in High-Volume Commercial MicroprocessorsabstractAccurate power modeling is crucial for energy-efficient CPU design and runtime management. An ideal power modeling framework needs to be accurate yet fast, achieve high temporal resolution (ideally cycle-accurate) yet with low runtime computational overheads, and easily extensible to diverse designs through automation. Simultaneously satisfying such conflicting objectives is challenging and largely unattained despite significant prior research. Zhiyao Xie, Matt Walker, Joshua Knebel, Kumaraguru Palaniswamy, Nicolas Hebert, Jiang Hu 0001, Huanrui Yang, Yiran Chen 0001, Shidhartha Das |
MICRO | 5 |