ZipFlow: a Compiler-based Framework to Unleash Compressed Data Movement for Modern GPUs
Summary: ZipFlow compiler-optimizes compression, PCIe transfer, and GPU decompression holistically, classifying codecs by parallelism and applying architecture-aware scheduling. It achieves 2.08× lower latency than nvCOMP and up to 3.14× over CPU engines. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Gwangoo Yeo (Korea Advanced Institute of Science and Technology)
- 2. Zhiyang Shen (Tsinghua University)
- 3. Wei Cui (Microsoft)
- 4. Matteo Interlandi (Microsoft)
- 5. Rathijit Sen (Microsoft)
- 6. Bailu Ding (Microsoft)
- 7. Qi Chen (Microsoft)
- 8. Minsoo Rhu (Korea Advanced Institute of Science and Technology)
BibTeX Citation
@article{yeo_vldb26,
title = {{ZipFlow: a Compiler-based Framework to Unleash Compressed Data Movement for Modern GPUs}},
author = {Yeo, Gwangoo and Shen, Zhiyang and Cui, Wei and Interlandi, Matteo and Sen, Rathijit and Ding, Bailu and Chen, Qi and Rhu, Minsoo},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {3888--3901},
doi = {10.14778/3827998.3828003},
url = {https://doi.org/10.14778/3827998.3828003},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,923 | TQP++: Bridging ML Compilers and Analytical Query Processing on GPUs | 2026 | VLDB | 4.9793485e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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