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L3: A GPU-Native Co-Designed Data Format for Learned Lossless Lightweight Compression

Summary: L3 co-designs a GPU-native learned lossless codec around SLAP’s lane-major residual layout, warp-cooperative decoding, and fully on-device compression. It delivers TB/s decompression, 1.2–2.6B random accesses/s, and strong compression, outperforming GPU baselines. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
7451
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,260 | 29.61%
DOI
10.1145/3802078

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Authors

BibTeX Citation

@inproceedings{xia_sigmod26,
        title = {{L3: A GPU-Native Co-Designed Data Format for Learned Lossless Lightweight Compression}},
        author = {Xia, Youyang and Zhang, Feng and Pan, Junda and Liu, Yihao and Guan, Jiawei and Zhang, Huanchen and Du, Xiaoyong},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3802078},
        url = {https://dl.acm.org/doi/10.1145/3802078},
        year = {2026}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 cited papers.

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

Rank Cited Paper Year Venue Pagerank
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
60 Integrating Compression and Execution in Column-Oriented Database Systems 2006 SIGMOD 0.0003955489
447 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018322593
477 The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds 2020 VLDB 0.00017851226
823 The Yin and Yang of Processing Data Warehousing Queries on GPU Devices 2013 VLDB 0.00013792901
912 Hardware-Oblivious Parallelism for In-Memory Column-Stores 2013 VLDB 0.00013269804
1,466 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.0001068941
1,574 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010321274
1,666 HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics 2016 VLDB 0.00010068964
2,232 Database Compression on Graphics Processors 2010 VLDB 8.8970926e-05
2,566 Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects 2020 SIGMOD 8.4116562e-05
3,092 DeepSqueeze: Deep Semantic Compression for Tabular Data 2020 SIGMOD 7.7679406e-05
3,173 Why You Should Run TPC-DS:A Workload Analysis 2007 VLDB 7.6664516e-05
3,592 The FastLanes Compression Layout: Decoding >100 Billion Integers per Second with Scalar Code 2023 VLDB 7.2774889e-05
3,729 CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithm 2022 VLDB 7.1683974e-05
4,065 LeCo: Lightweight Compression via Learning Serial Correlations 2024 SIGMOD 6.930275e-05
4,144 Tile-based Lightweight Integer Compression in GPU 2022 SIGMOD 6.8744592e-05
4,416 Query Optimization in Oracle 12c Database In-Memory 2015 VLDB 6.7150543e-05
4,679 Efficient Document Analytics on Compressed Data: Method, Challenges, Algorithms, Insights 2018 VLDB 6.5683136e-05
5,285 Order-Preserving Key Compression for In-Memory Search Trees 2020 SIGMOD 6.2821588e-05
5,348 Crystal: A Unified Cache Storage System for Analytical Databases 2021 VLDB 6.2562688e-05
5,622 Good to the Last Bit: Data-Driven Encoding with CodecDB 2021 SIGMOD 6.1461066e-05
6,665 MorphStore: Analytical Query Engine with a Holistic Compression-Enabled Processing Model 2020 VLDB 5.8089595e-05
7,173 CompressDB: Enabling Efficient Compressed Data Direct Processing for Various Databases 2022 SIGMOD 5.6830655e-05
7,890 FCBench: Cross-Domain Benchmarking of Lossless Compression for Floating-Point Data 2024 VLDB 5.521314e-05
9,038 The FastLanes File Format 2025 VLDB 5.3270943e-05
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