Efficient GPU-Accelerated Adaptive Minimum Cost Seed Selection
Summary: GAAS accelerates adaptive minimum-cost seed selection on GPUs via GmRR, a contention-avoiding circular mRR-set layout and balanced kernels. Reusing and theoretically updating mRR-sets yields up to 68.9× speedups with competitive seed costs. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Gongyao Guo (Hong Kong Polytechnic University)
- 2. Chen Feng (Hong Kong Polytechnic University)
- 3. Yiran Li (University of Toronto)
- 4. Jieming Shi (Hong Kong Polytechnic University)
BibTeX Citation
@article{guo_vldb26,
title = {{Efficient GPU-Accelerated Adaptive Minimum Cost Seed Selection}},
author = {Guo, Gongyao and Feng, Chen and Li, Yiran and Shi, Jieming},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {11},
pages = {3427--3439},
doi = {10.14778/3836663.3836699},
url = {https://doi.org/10.14778/3836663.3836699},
year = {2026}
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