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Towards High-Throughput Gibbs Sampling at Scale: A Study across Storage Managers

Summary: Investigates high-throughput Gibbs sampling for large factor graphs, showing materialization, page layout, and buffer choices must be redesigned for beyond-memory workloads. On HBase and Unix-file backends, a simple prototype achieves competitive throughput for graphs larger than memory, outperforming baselines by up to 100x. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4635
Venue
SIGMOD
Year
2013
Pagerank
6.4678697e-05
Overall Rank
4,077 | 71.64%
DOI
-

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