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The results demonstrate that substantial reductions in processing times can be achieved using massively parallel architectures: when compared to a superscalar ...
In this paper, a measure of spatial association, G(d), is used to illustrate how a massively parallel computer can be used to address the computational ...
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A measure of spatial association, G(d), is used to illustrate how a massively parallel computer can be used to address the computational requirements of ...
The computational intensity of spatial statistics, including measures of spatial association, has hindered their application to large empirical data sets.
In this article, we present a Spark-based parallel computing approach for the focal algorithms of neighboring analysis.
Oct 22, 2024 · This study presents a massively parallel spatial computing approach that uses general-purpose graphics processing units (GPUs) to accelerate ...
Sep 3, 2015 · In this paper, we provide a systematic evaluation of multiple spatial partitioning methods with a set of different partitioning strategies.
In order to address the challenge of massive spatial data processing, we propose a hypergraph based tasks scheduling strategy on a master-slave platform. Our ...
The paper describes the development of Kohonen-net-based methods suitable for the classification of large spatial datasets suitable for parallel processing.
This paper approaches the pros- pect of GPU computing in geographic information science from a more empirical standpoint and con- tributes a study on the ...