2014 Sixth International Symposium on Parallel Architectures, Algorithms and Programming (PAAP) (2014)
July 13, 2014 to July 15, 2014
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PAAP.2014.54
Metric-space indexing, also known as distance-based indexing, is a universal indexing to support similarity queries. It only requires that the similarity of data be defined by a metric distance function. To achieve the great universalness, metric-space indexing does not take use of the domain information of data, and is thus outperformed by many domain-specific methods. In this paper, to speed up metric-space similarity query, we first assign one thread for each query in the multi-query case to increase the throughput. Then, for a single query, we assign one thread for each search path from the root of the index tree to decrease the responding time. Last but not least, we implement an in-memory buffer to break the bottleneck of the disk access to the index file. Experimental results show that our efforts result in good speed up and parallel efficiency.
Instruction sets, Extraterrestrial measurements, Search problems, Indexing
F. Lei et al., "Speed Up Distance-Based Similarity Query Using Multiple Threads," 2014 Sixth International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), Beijing, China, 2014, pp. 215-219.