A Fast Similarity Join Algorithm Using Graphics Processing Units

  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},
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
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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
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5 Excerpts

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