A Fast Similarity Join Algorithm Using Graphics Processing Units

@article{Lieberman2008AFS,
  title={A Fast Similarity Join Algorithm Using Graphics Processing Units},
  author={Michael D. Lieberman and Jagan Sankaranarayanan and Hanan Samet},
  journal={2008 IEEE 24th International Conference on Data Engineering},
  year={2008},
  pages={1111-1120}
}
A similarity join operation A BOWTIEepsiv B takes two sets of points A, B and a value epsiv isin Ropf, and outputs pairs of points p isin A,q isin B, such that the distance D(p, q) les epsiv. Similarity joins find use in a variety of fields, such as clustering, text mining, and multimedia databases. A novel similarity join algorithm called LSS is presented that executes on a graphics processing unit (GPU), exploiting its parallelism and high data throughput. As GPUs only allow simple data… CONTINUE READING
Highly Cited
This paper has 105 citations. REVIEW CITATIONS
66 Citations
30 References
Similar Papers

Citations

Publications citing this paper.

105 Citations

0102030'09'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 105 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 30 references

NVIDIA CUDA Compute Unified Devic e Architecture programming guide

  • NVIDIA Corporation
  • http://developer.nvidia .com/cuda.
Highly Influential
5 Excerpts

Multidimensional and Metric Data Structure s

  • H. Samet, Foundations
  • San Francisco, CA: Morgan-Kaufmann,
  • 2006
Highly Influential
5 Excerpts

Similar Papers

Loading similar papers…