A bridging model for parallel computation
Communications of the ACM
ACM Computing Surveys (CSUR)
Near Neighbor Search in Large Metric Spaces
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Searching in metric spaces by spatial approximation
The VLDB Journal — The International Journal on Very Large Data Bases
A compact space decomposition for effective metric indexing
Pattern Recognition Letters
High-performance distributed inverted files
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Spatial Selection of Sparse Pivots for Similarity Search in Metric Spaces
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Searching and Updating Metric Space Databases Using the Parallel EGNAT
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Efficient parallelization of spatial approximation trees
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
(Sync|Async)+ MPI search engines
PVM/MPI'07 Proceedings of the 14th European conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
kNN query processing in metric spaces using GPUs
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Range query processing on single and multi GPU environments
Computers and Electrical Engineering
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We present a distributed index data structure and algorithms devised to support parallel query processing of multimedia content in search engines. We present a comparative study with a number of data structures used as indexes for metric space databases. Our optimization criteria are based on requirements for high-performance search engines. The main advantages of our proposal are efficient performance with respect to other approaches (sequentially and in parallel), suitable treatment of secondary memory, and support for OpenMP multithreading. We presents experiments for the asynchronous (MPI) and bulk-synchronous (BSP) message passing models of parallel computing showing that in both models our approach outperforms others consistently.