Demo Data from VLDB 2026 / reviewers in the wild / expert
Junben Weng
dblp:340/0308
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021
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 |
High-performance computing · 50% Processor architecture and microarchitecture · 25% Memory systems · 25% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Memory systems
data locality |
0.7 | 1 | 2023 | Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight Supercomputer · IEEE Trans. Parallel Distributed Syst. 2023 |
Processor architecture and microarchitecture
many-core architecture |
0.7 | 1 | 2023 | Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight Supercomputer · IEEE Trans. Parallel Distributed Syst. 2023 |
High-performance computing › scientific computing systems
molecular dynamics simulation |
0.7 | 1 | 2023 | Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight Supercomputer · IEEE Trans. Parallel Distributed Syst. 2023 |
High-performance computing
scientific computing |
0.7 | 1 | 2023 | Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight Supercomputer · IEEE Trans. Parallel Distributed Syst. 2023 |
Methods — techniques the papers use, named apart from their topics
cell list data structure · 0.7bond lists · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Bio-ESMD: A Data Centric Implementation for Large-Scale Biological System Simulation on Sunway TaihuLight SupercomputerabstractMolecular dynamics (MD) simulations of biological systems are playing an increasingly important role in the research of pathogens and drugs. Most MD methods for biological simulations rely on the listed bonds which interact among specific groups of atoms identified by atom tags (unique atom tags regardless the storage location). However, efficient mapping of tags to atom locations is often challenging on modern many-core processors because data locality can not always be guaranteed for large-scale systems. In this paper, we present Bio-ESMD, a new MD implementation supporting listed bonds. Bio-ESMD is designed and developed based on our previously designed ESMD framework for many-core processors. In Bio-ESMD, we have introduced a data-centric approach for refactoring MD algorithms by reorganizing the cell list data structure to adopt bond lists with guaranteed data locality. Our implementation achieves speedups of over two compared to SW_GROMACS on Sunway TaihuLight. Furthermore, Bio-ESMD can simulate a system of 308.8 million atoms at 1.33 ns/day or 14.44 million atoms at 17.28 ns/day with linear weak scaling efficiency. Xiaohui Duan, Junben Weng, Bertil Schmidt, Lin Gan 0001, Haohuan Fu, Wei Xue 0003, Guangwen Yang 0002 |
IEEE Trans. Parallel Distributed Syst. | 3 |