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Xiaohui Zhang 0016

dblp:55/1332-16 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-3471-0038ORCID · verified

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.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 67% Combinatorics and discrete mathematics · 33%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph algorithms and graph theory › graph decomposition
core maintenance
0.712023
Revisiting Core Maintenance for Dynamic Hypergraphs · IEEE Trans. Parallel Distributed Syst. 2023
Graph algorithms and graph theory
graph algorithms
0.712023
Revisiting Core Maintenance for Dynamic Hypergraphs · IEEE Trans. Parallel Distributed Syst. 2023
Combinatorics and discrete mathematics › hypergraph
hypergraph algorithms
0.712023
Revisiting Core Maintenance for Dynamic Hypergraphs · IEEE Trans. Parallel Distributed Syst. 2023
Parallel and multicore computing
parallel graph algorithms
0.212023
Revisiting Core Maintenance for Dynamic Hypergraphs · IEEE Trans. Parallel Distributed Syst. 2023

Methods — techniques the papers use, named apart from their topics

parallel processing · 1.3matching · 1.3
YearPublicationVenuePosition
2023 Revisiting Core Maintenance for Dynamic Hypergraphs
abstract
Core maintenance for dynamic hypergraphs has been receiving an increasing attention. However, existing works mainly focus on the insertion/deletion of hyperedges. This article revisits the problem from the view of vertices change. We study core maintenance when the vertices are inserted/deleted into/from specific hyperedges in the hypergraph, which is a challenging task since the deletion of the vertex may increase the core numbers and the insertion of the vertex may decrease the core numbers. We discuss in detail the possible changes of core numbers in different situations. For the insertion/deletion of vertices contained by a single hyperedge, we design sequential algorithms to discover the vertices whose core numbers have changed. Compared with static recomputation (Leng et al. 2013) and LYCLC (Luo et al. 2021) algorithms, our sequential algorithms can accelerate more than 1,000× and 12× at most in the processing time, respectively. For the insertion/deletion of vertices contained by different hyperedges, we find that core numbers of all vertices change 1 at most if these hyperedges form a matching. We design parallel algorithms that divide a matching into different sets based on their core numbers and allot a thread to each set. Experiments show that our parallel algorithms have good stability, scalability, and parallelism. Compared with the parallel static algorithm (Gabert et al. 2021) and the parallel dynamic algorithm GPC (Gabert et al. 2021), our parallel algorithms with 32 threads can accelerate 33× and 22× at most in the processing time, respectively.
Qiang-Sheng Hua, Xiaohui Zhang 0016, Hai Jin 0001, Hong Huang 0001
IEEE Trans. Parallel Distributed Syst.2