Redundancy Elimination in Distributed Matrix Computation

Summary: ReMac: automatic and adaptive redundancy elimination for distributed matrix computation. It uses block-wise search to rapidly uncover common subexpressions and a DP-based cost model to generate efficient plans while preserving operator order; implemented on SystemDS with orders-of-magnitude gains over prior solutions. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h30583c8711f89376
Venue: SIGMOD
Year: 2022
Pagerank: 4.9605343e-05
Overall Rank: 11,896 | 20.26%
DOI: 10.1145/3514221.3517877

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Zihao Chen (East China Normal University)
2. Baokun Han (East China Normal University)
3. Chen Xu (East China Normal University)
4. Weining Qian (East China Normal University)
5. Aoying Zhou (East China Normal University)

BibTeX Citation

@inproceedings{chen_sigmod22,
        title = {{Redundancy Elimination in Distributed Matrix Computation}},
        author = {Chen, Zihao and Han, Baokun and Xu, Chen and Qian, Weining and Zhou, Aoying},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517877},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517877},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,525	EncoderForge: Generating Efficient SQL for Encoders in Machine Learning Inference Pipelines	2026	SIGMOD	4.9605343e-05
11,958	ReMac: A Matrix Computation System with Redundancy Elimination	2022	VLDB	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 17 of 17 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
247	Overview of SciDB: Large Scale Array Storage, Processing and Analysis	2010	SIGMOD	0.00023119762
415	SystemML: Declarative Machine Learning on Spark	2016	VLDB	0.00018619173
1,154	Cerebro: A Data System for Optimized Deep Learning Model Selection	2020	VLDB	0.00011762688
1,226	Data Management in Machine Learning: Challenges, Techniques, and Systems	2017	SIGMOD	0.00011432354
1,616	SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle	2020	CIDR	0.00010048776
2,025	Query Optimization in Microsoft SQL Server PDW	2012	SIGMOD	9.1520946e-05
2,122	Enhanced Subquery Optimizations in Oracle	2009	VLDB	8.9938885e-05
2,278	An Intermediate Representation for Optimizing Machine Learning Pipelines	2019	VLDB	8.6993865e-05
2,720	Exploiting Matrix Dependency for Efficient Distributed Matrix Computation	2015	SIGMOD	8.0778267e-05
3,104	On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML	2018	VLDB	7.6281929e-05
3,331	SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning	2017	CIDR	7.4065701e-05
3,528	A Comparative Evaluation of Systems for Scalable Linear Algebra-based Analytics	2018	VLDB	7.2134232e-05
4,329	MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions	2019	SIGMOD	6.64569e-05
4,354	LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems	2021	SIGMOD	6.6318545e-05
4,505	SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra	2020	VLDB	6.5561966e-05
6,733	DistME: A Fast and Elastic Distributed Matrix Computation Engine using GPUs	2019	SIGMOD	5.6788432e-05
8,678	Optimization of Common Table Expressions in MPP Database Systems	2015	VLDB	5.2744774e-05

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