Demo Data from EDBT 2026 / reviewers in the wild / expert
Waion Wong
dblp:153/3723
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 · 50% High-performance computing · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › parallel numerical algorithms
parallel monte carlo |
0.0 | 1 | 2002 | Parallel computing for lattice Monte Carlo simulation of large-scale thin film growth · Sci. China Ser. F Inf. Sci. 2002 |
Parallel and multicore computing › parallel computing
parallel scientific computing |
0.0 | 1 | 2002 | Parallel computing for lattice Monte Carlo simulation of large-scale thin film growth · Sci. China Ser. F Inf. Sci. 2002 |
Methods — techniques the papers use, named apart from their topics
domain decomposition · 0.1asynchronous communication · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Parallel computing for lattice Monte Carlo simulation of large-scale thin film growthabstractThis paper proposes two viable computing strategies for distributed parallel systems: domain division with sub-domain overlapping and asynchronous communication. We have implemented a parallel computing procedure for simulation of Ti thin film growing process of a system with 1000 × 1000 atoms by means of the Monte Carlo (MC) method. This approach greatly reduces the computation time for simulation of large-scale thin film growth under realistic deposition rates. The multi-lattice MC model of deposition comprises two basic events: deposition, and surface diffusion. Since diffusion constitutes more than 90% of the total simulation time of the whole deposition process at high temperature, we concentrated on implementing a new parallel diffusion simulation that reduces communication time during simulation. Asynchronous communication and domain overlapping techniques are used to reduce the waiting time and communication time among parallel processors. The parallel algorithms we propose can simulate the thin film growth of a system with many more particles than before under realistic deposition rates, and can provide a more efficient means for computer simulation of thin film growth. Jiwu Shu, Han-Chen Huang, Waion Wong |
Sci. China Ser. F Inf. Sci. | 5 |