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Fast Optimal Group Steiner Tree Search using GPUs

Summary: First GPU-tailored optimal GST solver: breaks traditional bottom-up DP into a parallel-friendly order and adds GST-specific load balancing (kernel fusion, global-memory coalescing) plus parallel-safe pruning to achieve 48–2390× speedups. Also introduces a GPU DP for diameter-bounded GSTs. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7388
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,079 | 29.89%
DOI
10.1145/3769792

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Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,641 GPU-Accelerated Subgraph Enumeration on Partitioned Graphs 2020 SIGMOD 6.8884895e-05
4,168 Accelerating Triangle Counting on GPU 2021 SIGMOD 6.391271e-05
4,522 GPU-based Graph Traversal on Compressed Graphs 2019 SIGMOD 6.1146374e-05
5,474 Efficient Load-Balanced Butterfly Counting on GPU 2022 VLDB 5.4881807e-05
5,683 Efficient and Progressive Group Steiner Tree Search 2016 SIGMOD 5.3723969e-05
7,225 Self-adaptive Graph Traversal on GPUs 2021 SIGMOD 4.7956162e-05
11,264 Approximating Probabilistic Group Steiner Trees in Graphs 2023 VLDB 4.1945683e-05
11,493 Finding Group Steiner Trees in Graphs with both Vertex and Edge Weights 2021 VLDB 4.1945683e-05
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