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Pierce: GPU Ray Tracing for Spatial Joins over Complex 3D Data — arXiv:2609.24513

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.24513
License (as archived): CC0-1.0
Archived: 2026-10-09T22:39:58.135Z
SHA-256 of the archived text: 04311095504770d48a823c47b0466ca9ff67c73d045ce9039f17918fd8d0ae77
Stable URL of this page: https://metraipolis.com/documento/dc_f2cfef424674

How to cite

Pierce: GPU Ray Tracing for Spatial Joins over Complex 3D Data — arXiv:2609.24513 — arXiv (en), https://arxiv.org/abs/2609.24513 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_f2cfef424674 (Metraipolis archive dc_f2cfef424674, sha256 04311095504770d48a823c47b0466ca9ff67c73d045ce9039f17918fd8d0ae77)

BibTeX

@misc{dcf2cfef424674,
  title = {Pierce: GPU Ray Tracing for Spatial Joins over Complex 3D Data — arXiv:2609.24513},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.24513},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_f2cfef424674; sha256 04311095504770d48a823c47b0466ca9ff67c73d045ce9039f17918fd8d0ae77},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.24513. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Many emerging applications, from computational biology to digital twins and urban planning, rely heavily on three-dimensional spatial joins over polyhedral meshes. These joins comprise computationally-intensive triangle--triangle intersection tests that pairwise compare the faces of polyhedral meshes. Since each mesh may contain thousands of faces, the resulting cost challenges the responsiveness of spatial data management techniques. Existing techniques follow the filter-and-refine paradigm, accelerating either the filtering step through indexing or the refinement step through progressive mesh compression combined with GPU parallelization of triangle--triangle tests. However, the former neglects the high cost of intra-geometry refinements, whereas the latter lowers this cost but still relies on the same pairwise triangle--triangle tests. In this paper, we introduce Pierce, an approach that reformulates three-dimensional spatial joins over complex polyhedral meshes as ray-tracing operations and leverages the hardware ray-tracing units (RT cores) of modern GPUs to accelerate query execution. Our approach casts rays along the edges of one mesh against a spatial hierarchy built over the other, performing ray--node tests at the internal levels to prune distant geometries and ray--triangle tests at the leaves to identify intersecting meshes, both of which RT cores accelerate in hardware. We evaluated Pierce on real and synthetic data against multiple baselines, demonstrating more than two orders of magnitude speedup on digital pathology data compared to the state-of-the-art approach.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-22 in cs.DB).
Categorie arXiv: Databases (cs.DB).
Pagina del lavoro: https://arxiv.org/abs/2609.24513 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T22:21:29.797Z dalla pagina https://arxiv.org/catchup/cs.DB/2026-09-22?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).