ACM Computing Surveys (CSUR)
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Hardware acceleration for spatial selections and joins
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Fast computation of database operations using graphics processors
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Hardware acceleration in commercial databases: a case study of spatial operations
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A translation system for enabling data mining applications on GPUs
Proceedings of the 23rd international conference on Supercomputing
GPU-Accelerated Nearest Neighbor Search for 3D Registration
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
A GPU-Based Implementation for Range Queries on Spaghettis Data Structure
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
kNN query processing in metric spaces using GPUs
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Combining CPU and GPU architectures for fast similarity search
Distributed and Parallel Databases
Learning hash codes for efficient content reuse detection
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
kANN on the GPU with shifted sorting
EGGH-HPG'12 Proceedings of the Fourth ACM SIGGRAPH / Eurographics conference on High-Performance Graphics
Hi-index | 0.00 |
We present a GPU algorithm for the nearest neighbor search, an important database problem. The search is completely performed using the GPU: No further post-processing using the CPU is needed. Our experimental results, using large synthetic and real-world data sets, showed that our GPU algorithm is several times faster than its CPU version.