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QPET: A Versatile and Portable Quantity-of-Interest-Preservation Framework for Error-Bounded Lossy Compression
Summary: QPET: a portable numerical framework that enforces QoI (quantity‑of‑interest) preservation for error‑bounded lossy compressors and plugs into many existing compressors. Supports differentiable uni/multivariate QoIs and yields 2×–10× speedups and up to 10× compression‑ratio gains in experiments.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13891
- Venue
- VLDB
- Year
- 2025
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,614 | 26.17%
- DOI
-
10.14778/3742728.3742739
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| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 210 |
Gorilla: A Fast, Scalable, In-Memory Time Series Database |
2015 |
VLDB |
0.0003404384 |
| 1,100 |
Query Optimization In Compressed Database Systems |
2001 |
SIGMOD |
0.00014072277 |
| 2,064 |
Chimp: Efficient Lossless Floating Point Compression for Time Series Databases |
2022 |
VLDB |
9.6418929e-05 |
| 2,140 |
Online Piece-wise Linear Approximation of Numerical Streams with Precision Guarantees* |
2009 |
VLDB |
9.4626098e-05 |
| 2,267 |
ModelarDB: Modular Model-Based Time Series Management with Spark and Cassandra |
2018 |
VLDB |
9.1519895e-05 |
| 2,613 |
Decomposed Bounded Floats for Fast Compression and Queries |
2021 |
VLDB |
8.4503824e-05 |
| 4,531 |
Efficient Document Analytics on Compressed Data: Method, Challenges, Algorithms, Insights |
2018 |
VLDB |
6.1073703e-05 |
| 9,445 |
Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data |
2023 |
VLDB |
4.3404859e-05 |
| 10,937 |
High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation |
2024 |
SIGMOD |
4.1945683e-05 |
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