An Architecture for Parallel Topic Models
Summary: Parallel topic-model sampling on a workstation cluster; scales to hundreds of millions of documents and thousands of topics. Distributed key-value state sharing removes separate sync phases; disk, CPU, and network work in parallel; extendable to n-grams and hierarchies. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Alexander Smola (Australian National University; Yahoo)
- 2. Shravan Narayanamurthy (Yahoo)
BibTeX Citation
@article{smola_vldb10,
title = {{An Architecture for Parallel Topic Models}},
author = {Smola, Alexander and Narayanamurthy, Shravan},
journal = {PVLDB},
series = {{VLDB} '10},
volume = {3},
number = {1},
pages = {703--710},
doi = {10.14778/1920841.1920931},
url = {https://doi.org/10.14778/1920841.1920931},
year = {2010}
}
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