Molecular docking using shape descriptors
Journal of Computational Chemistry
Parallel and distributed computing handbook
Parallel and distributed computing handbook
Parallel processing of nearest neighbor queries in declustered spatial data
GIS '96 Proceedings of the 4th ACM international workshop on Advances in geographic information systems
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
RECOMB '99 Proceedings of the third annual international conference on Computational molecular biology
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Efficient Search for Approximate Nearest Neighbor in High Dimensional Spaces
SIAM Journal on Computing
Introduction to Parallel Computing
Introduction to Parallel Computing
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Modular Reconfigurable Robots in Space Applications
Autonomous Robots
Multiple Similarity Queries: A Basic DBMS Operation for Mining in Metric Databases
IEEE Transactions on Knowledge and Data Engineering
On the 'Dimensionality Curse' and the 'Self-Similarity Blessing'
IEEE Transactions on Knowledge and Data Engineering
Near Neighbor Search in Large Metric Spaces
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Data mining tasks and methods: Classification: nearest-neighbor approaches
Handbook of data mining and knowledge discovery
Contorting high dimensional data for efficient main memory KNN processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
(Almost) Optimal parallel block access for range queries
Information Sciences—Informatics and Computer Science: An International Journal
QSIC '04 Proceedings of the Quality Software, Fourth International Conference
On efficiently processing nearest neighbor queries in a loosely coupled set of data sources
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Fast range query estimation by N-level tree histograms
Data & Knowledge Engineering
Nearest Neighbor Search: A Database Perspective
Nearest Neighbor Search: A Database Perspective
IEEE Transactions on Knowledge and Data Engineering
The PN-tree: a parallel and distributed multidimensional index
Distributed and Parallel Databases
iDistance: An adaptive B+-tree based indexing method for nearest neighbor search
ACM Transactions on Database Systems (TODS)
Exploring bit-difference for approximate KNN search in high-dimensional databases
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Adaptive nearest neighbor queries in travel time networks
Proceedings of the 13th annual ACM international workshop on Geographic information systems
The Journal of Supercomputing
Optimal parallel all-nearest-neighbors using the well-separated pair decomposition
SFCS '93 Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science
Sampling-Based Roadmap of Trees for Parallel Motion Planning
IEEE Transactions on Robotics
Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection
The Journal of Machine Learning Research
Efficient parallel kNN joins for large data in MapReduce
Proceedings of the 15th International Conference on Extending Database Technology
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High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) graphs. The knn graph of a data set is obtained by connecting each point to its k closest points. As the research in the above-mentioned fields progressively addresses problems of unprecedented complexity, the demand for computing knn graphs based on arbitrary distance metrics and large high-dimensional data sets increases, exceeding resources available to a single machine. In this work we efficiently distribute the computation of knn graphs for clusters of processors with message passing. Extensions to our distributed framework include the computation of graphs based on other proximity queries, such as approximate knn or range queries. Our experiments show nearly linear speedup with over 100 processors and indicate that similar speedup can be obtained with several hundred processors.