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T. H. Liang

dblp:230/7063 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot dynamics
inertia matrix computation
0.011991
Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991
Robotics › Motion planning and robot control
robot dynamics
0.011991
Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991
Parallel and multicore computing
parallel algorithms
0.011991
Decoupled parallel algorithm for robot inertia matrix computation · ICRA 1991
High-performance computing › parallel numerical algorithms
parallel robot dynamics computation
0.011991
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
YearPublicationVenuePosition
1991 Decoupled parallel algorithm for robot inertia matrix computation
abstract
The 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
ICRA2