Just Move It! Dynamic Parameter Allocation in Action
Summary: Dynamic parameter allocation in parameter servers enables adaptive resource use for distributed ML. Lapse, an open-source PS with live visualization, demonstrates order-of-magnitude speedups over other PSs and near-linear gains versus single-machine baselines via interactive analysis. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Alexander Renz-Wieland (Technische University Berlin)
- 2. Tobias Drobisch (Technische University Berlin)
- 3. Zoi Kaoudi (Technische University Berlin)
- 4. Rainer Gemulla (University of Mannheim)
- 5. Volker Markl (German National Research Center for Information Technology; Technische University Berlin)
BibTeX Citation
@article{renzwieland_vldb21,
title = {{Just Move It! Dynamic Parameter Allocation in Action}},
author = {Renz-Wieland, Alexander and Drobisch, Tobias and Kaoudi, Zoi and Gemulla, Rainer and Markl, Volker},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2707--2710},
doi = {10.14778/3476311.3476325},
url = {https://doi.org/10.14778/3476311.3476325},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,912 | HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training | 2022 | SIGMOD | 6.4481656e-05 |
| 6,022 | NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access | 2022 | SIGMOD | 6.0046123e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 20 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.00056944564 |
| 452 | An Architecture for Parallel Topic Models | 2010 | VLDB | 0.00018146809 |
| 2,162 | Heterogeneity-aware Distributed Parameter Servers | 2017 | SIGMOD | 9.0581831e-05 |
| 2,615 | NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion | 2014 | VLDB | 8.340186e-05 |
| 2,693 | FlexPS: Flexible Parallelism Control in Parameter Server Architecture | 2018 | VLDB | 8.247004e-05 |
| 5,345 | PS2: Parameter Server on Spark | 2019 | SIGMOD | 6.2586047e-05 |
| 6,519 | Dynamic Parameter Allocation in Parameter Servers | 2020 | VLDB | 5.8536062e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 5,345 | PS2: Parameter Server on Spark | 2019 | SIGMOD |
| 2 | 4,049 | Resource Elasticity for Large-Scale Machine Learning | 2015 | SIGMOD |
| 3 | 8,101 | SDP_PIPE: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training | 2023 | VLDB |
| 4 | 7,190 | PetPS: Supporting Huge Embedding Models with Persistent Memory | 2023 | VLDB |
| 5 | 532 | MLbase: A Distributed Machine-learning System | 2013 | CIDR |
| 6 | 4,956 | Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce | 2021 | SIGMOD |
| 7 | 2,162 | Heterogeneity-aware Distributed Parameter Servers | 2017 | SIGMOD |
| 8 | 2,693 | FlexPS: Flexible Parallelism Control in Parameter Server Architecture | 2018 | VLDB |
| 9 | 6,022 | NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access | 2022 | SIGMOD |
| 10 | 6,519 | Dynamic Parameter Allocation in Parameter Servers | 2020 | VLDB |