Conference proceeding
SPATIOTEMPORAL DOMAIN DECOMPOSITION FOR MASSIVE PARALLEL COMPUTATION OF SPACE-TIME KERNEL DENSITY
ISPRS International Workshop on Spatiotemporal Computing, v 2(4), pp 7-11
10 Jul 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.
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Details
- Title
- SPATIOTEMPORAL DOMAIN DECOMPOSITION FOR MASSIVE PARALLEL COMPUTATION OF SPACE-TIME KERNEL DENSITY
- Creators
- Alexander Hohl - University of North Carolina at CharlotteEric M. Delmelle - University of North Carolina at CharlotteWenwu Tang - University of North Carolina at Charlotte
- Contributors
- C Yang (Editor)K Clarke (Editor)M Yuan (Editor)M Yu (Editor)M Li (Editor)W Guan (Editor)M Sun (Editor)B Huang (Editor)
- Publication Details
- ISPRS International Workshop on Spatiotemporal Computing, v 2(4), pp 7-11
- Publisher
- Copernicus Gesellschaft Mbh
- Number of pages
- 5
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Urban Health Collaborative
- Web of Science ID
- WOS:000380547600030
- Scopus ID
- 2-s2.0-84994202586
- Other Identifier
- 991021874422704721
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- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Geography, Physical
- Imaging Science & Photographic Technology
- Remote Sensing