Demo Data from EDBT 2026 / reviewers in the wild / expert
Zhao Yong
dblp:68/3064
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—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 |
Reconfigurable computing and FPGAs · 62% Electronic design automation · 38% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Reconfigurable computing and FPGAs
FPGA accelerator |
0.1 | 1 | 2005 | Configurable hardware solutions for computing autocorrelation coefficients: a case study (abstract only) · FPGA 2005 |
Electronic design automation › logic synthesis
boolean function realization |
0.0 | 1 | 2005 | Configurable hardware solutions for computing autocorrelation coefficients: a case study (abstract only) · FPGA 2005 |
Electronic design automation
logic synthesis |
0.0 | 1 | 2005 | Configurable hardware solutions for computing autocorrelation coefficients: a case study (abstract only) · FPGA 2005 |
Methods — techniques the papers use, named apart from their topics
configurable hardware encoding · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Configurable hardware solutions for computing autocorrelation coefficients: a case study (abstract only)abstractThere are many computationally intensive problems in the area of digital design and logic synthesis. Some of these have no "good" solution; that is, simply by their definition they have exponential run-times. In order to overcome this, we examine the possibility of a configurable hardware solution to speed up one such problem. The computation of the problem is carried out on a Field Programmable Gate Array (FPGA), where the problem is encoded in such a way that within certain parameters, the design of the solution need not be changed for working with a variety of benchmark circuits. This saves considerably on compilation and configuration times. The use of configurable hardware, however, still allows for reconfiguration in situations where the parameters change significantly enough to require an altered approach. We examine two implementations of the problem, which in this case consists of computing the autocorrelation coefficients for a Boolean function. Jacqueline E. Rice, Kenneth B. Kent, Troy Ronda, Zhao Yong |
FPGA | 4 |