SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra
Summary: Converts large-scale linear algebra to relational algebra and optimizes via complete equality saturation. SPORES uses rule sampling to explore expression spaces and a solver to pick the optimal plan; integrated with SystemML, it yields up to 10× speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yisu Remy Wang (University of Washington)
- 2. Shana Hutchison (University of Washington)
- 3. Jonathan Leang (University of Washington)
- 4. Bill Howe (University of Washington)
- 5. Dan Suciu (University of Washington)
BibTeX Citation
@article{wang_vldb20,
title = {{SPORES: Sum-Product Optimization via Relational Equality Saturation for Large Scale Linear Algebra}},
author = {Wang, Yisu Remy and Hutchison, Shana and Leang, Jonathan and Howe, Bill and Suciu, Dan},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {11},
pages = {1919--1932},
doi = {10.14778/3407790.3407799},
url = {https://doi.org/10.14778/3407790.3407799},
year = {2020}
}
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