Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects
Summary: NVLink 2.0-based interconnect eliminates CPU-GPU transfer bottlenecks, enabling large-scale in-memory processing on GPUs. Demonstrates scalable no-partitioning hash join beyond GPU memory with up to 18x speedup vs PCIe 3.0 and 7.3x vs optimized CPU. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Clemens Lutz (German National Research Center for Information Technology)
- 2. Sebastian Breß (Technical University of Berlin)
- 3. Steffen Zeuch (German National Research Center for Information Technology)
- 4. Tilmann Rabl (Hasso Plattner Institute)
- 5. Volker Markl (German National Research Center for Information Technology; Technical University of Berlin)
BibTeX Citation
@inproceedings{lutz_sigmod20,
title = {{Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects}},
author = {Lutz, Clemens and Breß, Sebastian and Zeuch, Steffen and Rabl, Tilmann and Markl, Volker},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389705},
url = {https://dl.acm.org/doi/10.1145/3318464.3389705},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 30 of 30 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 31 of 31 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,432 | Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs | 2025 | VLDB |
| 2 | 631 | Relational Joins on Graphics Processors | 2008 | SIGMOD |
| 3 | 3,227 | MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures | 2021 | SIGMOD |
| 4 | 5,587 | Distributed GPU Joins on Fast RDMA-capable Networks | 2023 | SIGMOD |
| 5 | 6,774 | Evaluating Multi-GPU Sorting with Modern Interconnects | 2022 | SIGMOD |
| 6 | 3,134 | Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment | 2021 | VLDB |
| 7 | 10,985 | Scaling GPU-Accelerated Databases beyond GPU Memory Size | 2025 | VLDB |
| 8 | 6,835 | GPU-accelerated data management under the test of time | 2020 | CIDR |
| 9 | 9,333 | Efficiently Joining Large Relations on Multi-GPU Systems | 2025 | VLDB |
| 10 | 4,535 | Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects | 2022 | SIGMOD |