Demo Data from EDBT 2026 / reviewers in the wild / expert
T. H. Liang
dblp:230/7063
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1991
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, 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 |
Parallel and multicore computing · 44% High-performance computing · 44% Performance modeling and evaluation · 13% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot dynamics
inertia matrix computation |
0.0 | 1 | 1991 | Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991 |
Robotics › Motion planning and robot control
robot dynamics |
0.0 | 1 | 1991 | Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991 |
Parallel and multicore computing
parallel algorithms |
0.0 | 1 | 1991 | Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991 |
High-performance computing › parallel numerical algorithms
parallel robot dynamics computation |
0.0 | 1 | 1991 | Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991 |
Methods — techniques the papers use, named apart from their topics
decoupled parallel computation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1991 | Decoupled parallel algorithm for robot inertia matrix computationabstractThe common characteristic of existing parallel algorithms for evaluation of the robot inertia matrix on multiprocessor architectures is strict synchronization of processors, which limit the degree of the inherent parallelism. Such algorithms can, in the best case, deliver a time complexity of O(N), even with O(N/sup 2/) processors. Consideration is given to an approximate method in which all processors are decoupled, i.e., the processor synchronization, which handles the proper values of the propagated variables, is completely abandoned. Such a scheme drops the time complexity to O(N) for O(N) processors, and to O(1) for O(N/sup 2/) processors. Experimentation on the KUMARAN2 multiprocessor system based on MC68030/68882 processors, has shown surprisingly small approximation errors, which on average are below 1%. An analytical study of the approximation error is presented.> Marko Vuskovic, T. H. Liang |
ICRA | 2 |