Demo Data from EDBT 2026 / reviewers in the wild / expert
Seong-Wan Kim
dblp:145/3933
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 |
Integrated circuit design · 70% Emerging computing paradigms · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Integrated circuit design
digital circuit design |
0.2 | 1 | 2014 | Design of Goldschmidt Dividers with Quantum-Dot Cellular Automata · IEEE Trans. Computers 2014 |
Integrated circuit design › digital arithmetic circuits › division and square root
goldschmidt divider |
0.2 | 1 | 2014 | Design of Goldschmidt Dividers with Quantum-Dot Cellular Automata · IEEE Trans. Computers 2014 |
Emerging computing paradigms › field-coupled nanocomputing
quantum-dot cellular automata |
0.2 | 1 | 2014 | Design of Goldschmidt Dividers with Quantum-Dot Cellular Automata · IEEE Trans. Computers 2014 |
Integrated circuit design › digital circuit design
arithmetic circuit design |
0.1 | 1 | 2014 | Design of Goldschmidt Dividers with Quantum-Dot Cellular Automata · IEEE Trans. Computers 2014 |
Methods — techniques the papers use, named apart from their topics
pipelining · 0.2data tag method · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Design of Goldschmidt Dividers with Quantum-Dot Cellular AutomataabstractA Goldschmidt divider implemented with semiconductor quantum-dot cellular automata (QCA) is described. Most Goldschmidt dividers use a state machine for control, but state machines are difficult to implement in QCAs due to the long delays between the state machines and the computational circuits to be controlled. To resolve this problem, a data tag method is used. The data tags travel with the data and local tag decoders generate control signals. Since each datum has a tag, pipelining can be employed to increase the throughput. Using the new architecture, fixed-point Goldschmidt dividers are implemented with QCA technology. Inwook Kong, Seong-Wan Kim, Earl E. Swartzlander Jr. |
IEEE Trans. Computers | 2 |