Journal article
A vision for GPU-accelerated parallel computation on geo-spatial datasets
SIGSPATIAL Special, Vol.6(3), pp.19-26
04/22/2015
DOI: 10.1145/2766196.2766200
Abstract
We summarize the need and present our vision for accelerating geo-spatial computations and analytics using a combination of shared and distributed memory parallel platforms, with general-purpose Graphics Processing Units (GPUs) with 100s to 1000s of processing cores in a single chip forming a key architecture to parallelize over. A GPU can yield one-to-two orders of magnitude speedups and will become increasingly more affordable and energy efficient due to mass marketing for gaming. We also survey the current landscape of representative geo-spatial problems and their parallel, GPU-based solutions.
Details
- Title: Subtitle
- A vision for GPU-accelerated parallel computation on geo-spatial datasets
- Creators
- Sushil K. Prasad - Georgia State UniversityMichael McDermott - Georgia State UniversitySatish Puri - Georgia State UniversityDhara Shah - Georgia State UniversityDanial Aghajarian - Georgia State UniversityShashi Shekhar - University of MinnesotaXun Zhou - University of Iowa
- Resource Type
- Journal article
- Publication Details
- SIGSPATIAL Special, Vol.6(3), pp.19-26
- DOI
- 10.1145/2766196.2766200
- ISSN
- 1946-7729
- eISSN
- 1946-7729
- Language
- English
- Date published
- 04/22/2015
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380742902771
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