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Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Summary: Generalizes BSP for data science to agent simulations with local sync via partitions, preserving correctness. CloudCity, distributed engine exploiting partitions to boost compute and synchronization; evaluated against BSP-like systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6716
Venue
SIGMOD
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,400 | 21.79%
DOI
10.1145/3589296

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Authors

BibTeX Citation

@inproceedings{tian_sigmod23,
        title = {{Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations}},
        author = {Tian, Zilu and Lindner, Peter and Nissl, Markus and Koch, Christoph and Tannen, Val},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589296},
        url = {https://dl.acm.org/doi/10.1145/3589296},
        year = {2023}
}

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

Rank Cited Paper Year Venue Pagerank
3 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0012250108
389 One Trillion Edges: Graph Processing at Facebook-Scale 2015 VLDB 0.00019386526
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