- Title
- Computing large-scale distance matrices on GPU
- Creator
- Arefin, Ahmed Shamsul; Riveros, Carlos; Berretta, Regina; Moscato, Pablo
- Relation
- 7th International Conference on Computer Science & Education (ICCSE 2012). Proceedings of 2012 7th International Conference on Computer Science & Education (Melbourne 14-17 July, 2012) p. 576-580
- Publisher Link
- http://dx.doi.org/10.1109/ICCSE.2012.6295141
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2012
- Description
- A distance matrix is simply an nxn two-dimensional array that contains pairwise distances of a set of n points in a metric space. It has a wide range of usage in several fields of scientific research e.g., data clustering, machine learning, pattern recognition, image analysis, information retrieval, signal processing, bioinformatics etc. However, as the size of n increases, the computation of distance matrix becomes very slow or incomputable on traditional general purpose computers. In this paper, we propose an inexpensive and scalable data-parallel solution to this problem by dividing the computational tasks and data on GPUs. We demonstrate the performance of our method on a set of real-world biological networks constructed from a renowned breast cancer study.
- Subject
- graphics processing units; distance matrix; computational methods
- Identifier
- http://hdl.handle.net/1959.13/1057517
- Identifier
- uon:16197
- Identifier
- ISBN:9781467302425
- Language
- eng
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