Tianpeng Gao

dblp:317/0866 · DBLP profile ↗
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5ranked-venue papers
3as first author
5since 2021 · last 2024
0000-0002-1542-5322ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 4 · 2 first-author · 4 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2024 Approximate sorting and its applications in I/O model
Tianpeng Gao, Jianzhong Li 0001
Theor. Comput. Sci.1
2024 Turing machines with two-level memory: New computational models for analyzing the input/output complexity
Hengzhao Ma, Jianzhong Li 0001, Tianpeng Gao
Theor. Comput. Sci.3
2023 A New Approach for Semi-External Topological Sorting on Big Graphs
abstract
This paper presents a new approach for semi-external topological sorting algorithm on big directed acyclic graph(DAG). Topological sorting aims to find an ordering of each node in DAG, which satisfies$u$precedes$v$in the ordering for each edge$(u,v)$in DAG. Topological sorting is an important subroutine for scheduling and other external graph algorithms. But, the internal topological sorting algorithm cannot handle big DAGs and the I/O complexity of total external topological sorting is too high for practical applications. Therefore, we pay attention to the semi-external topological sorting for big DAGs in this paper. We find that the existing semi-external topological sorting algorithm is mainly based on constructing a DFS-Tree in internal memory. However, this DFS-based algorithm is natively more difficult than topological sorting, because DFS-Tree determines a strict total order, while topological order is only a partial order. Therefore, a partial orderlevel orderis proposed in this paper. Based on thelevel order, we propose a new semi-external topological sorting algorithm. Next, two optimizations,NodeRemoveandEdgeRemove, are proposed to reduce the CPU and I/O cost. In addition, we also propose a batch algorithm. Finally, we perform experimental studies using real and synthetic datasets to confirm the efficiency of our approach. According to the experimental results, our algorithms are better than the previous DFS-based algorithms.
Tianpeng Gao, Jianzhong Li 0001, Hengzhao Ma
IEEE Trans. Knowl. Data Eng.1
2022 Analysis of Approximate Sorting in I/O Model
Tianpeng Gao, Jianzhong Li 0001
COCOON1
2022 Turing Machines with Two-Level Memory: A Deep Look into the Input/Output Complexity
Hengzhao Ma, Jianzhong Li 0001, Tianpeng Gao
COCOON4