ReMac: A Matrix Computation System with Redundancy Elimination
Summary: ReMac: distributed matrix computation with redundancy elimination. Automatic elimination uses block-wise search exploiting matrix structure for speed; adaptive elimination uses a cost model and dynamic programming to yield efficient, side-effect-safe plans. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Zihao Chen (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
- 2. Zhizhen Xu (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
- 3. Baokun Han (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
- 4. Chen Xu (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
- 5. Weining Qian (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
- 6. Aoying Zhou (East China Normal University; Shanghai Engineering Research Center of Big Data Management)
BibTeX Citation
@article{chen_vldb22,
title = {{ReMac: A Matrix Computation System with Redundancy Elimination}},
author = {Chen, Zihao and Xu, Zhizhen and Han, Baokun and Xu, Chen and Qian, Weining and Zhou, Aoying},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {12},
pages = {3674--3677},
doi = {10.14778/3554821.3554872},
url = {https://doi.org/10.14778/3554821.3554872},
year = {2022}
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 239 | Overview of SciDB: Large Scale Array Storage, Processing and Analysis | 2010 | SIGMOD | 0.00023674329 |
| 1,756 | SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle | 2020 | CIDR | 9.8172465e-05 |
| 11,537 | Redundancy Elimination in Distributed Matrix Computation | 2022 | SIGMOD | 5.093636e-05 |
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