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A GPU Engine for Sparse Matrix-Vector Products on $k^2$-Tree-Compressed Graphs

Nov 2, 2026 Source ↗

Key Insights

The $k^2$-tree is a compact representation of Boolean matrices: it stores the recursive hierarchy of their non-empty submatrices, with neither values nor coordinates, and serves rows and columns alike.

Cite this synthesis DOI: 10.48550/arXiv.2611.03610 ↗

Show formatted citation

@misc{ acaciadata-research-a-gpu-engine-for-sparse-matrix-vector-products-on-k-2-tree-c,
  title = { A GPU Engine for Sparse Matrix-Vector Products on $k^2$-Tree-Compressed Graphs },
  author = { Leszek },
  year = { 2026 },
  doi = { 10.48550/arXiv.2611.03610 },
  url = { http://arxiv.org/abs/2611.03610v1 },
  note = {Summarized and classified by AcaciaFund}
}

TY  - GEN
TI  - A GPU Engine for Sparse Matrix-Vector Products on $k^2$-Tree-Compressed Graphs
AU  - Leszek
PY  - 2026
DO  - 10.48550/arXiv.2611.03610
UR  - http://arxiv.org/abs/2611.03610v1
ER  -

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Overview

The $k^2$-tree is a compact representation of Boolean matrices: it stores the recursive hierarchy of their non-empty submatrices, with neither values nor coordinates, and serves rows and columns alike

Key Topics

Database Systems: A theme covered by this item within the data engineering context.
Distributed Computing: A theme covered by this item within the data engineering context.

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Article Metadata

Evergreen Synthesized

distributed-computing dataops database-systems vector-search

DataOps Distributed Systems for Data

SQI 0.750