A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

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Discovery of 13 New Variable Stars in the Field of the Open Cluster NGC 2168 （M35）

A wide-field time-series CCD photometric survey of variable stars in the field of the open cluster NGC 2168 was carried out using the BATC Schmidt telescope. In total 13 new variable stars are discovered with three W UMa systems, one EA type and two EB type eclipsing binaries (one of them could be a W UMa system), and seven pulsating stars including three candidates of δScuti stars.     

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Mobile Agent技术是一门新兴的技术,具有移动性、智能性和异步计算的特点,已成为计算机网络和分布式系统最具活力的发展方向.现对Mobile Agent的概念、系统结构及其关键技术进行了分析和探讨.     

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