SwiftSpatial: Spatial Joins on Modern Hardware
Spatial joins are among the most time-consuming spatial queries, remaining costly even in parallel and distributed systems. In this paper, we explore hardware acceleration for spatial joins by proposing SwiftSpatial, an FPGA-based accelerator that can be deployed in data centers and at the edge. SwiftSpatial contains multiple high-performance join units with innovative hybrid parallelism, several efficient memory management units, and an extensible on-chip join scheduler that supports the popular R-tree synchronous traversal and partition-based spatial-merge (PBSM) algorithms. Benchmarked against various CPU and GPU-based spatial data processing systems, SwiftSpatial demonstrates a latency reduction of up to 41.03x relative to the best-performing baseline, while requiring 6.16x less power. The performance and energy efficiency of SwiftSpatial demonstrate its potential to be used in a variety of configurations (e.g., as an accelerator, near storage, in-network) as well as on different devices (e.g., data centers where FPGAs are widely available or mobile devices, which also contain FPGAs for specialized processing).
Authors
- Wenqi Jiang (ORCID: https://orcid.org/0000-0003-3895-7943)
- Martin Parvanov
- Gustavo Alonso (ORCID: https://orcid.org/0000-0002-4396-6695)
- عبدالله باقر بوكلاه
Institutions
- ETH Zurich (CH)
Publication Details
- Journal
- Proceedings of the ACM on Management of Data
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1145/3725361
- Citations
- 1
- Primary Topic
- Data Management and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 1.49