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Wu Q.,Anhui Normal University | Tong C.,Ningbo University of Technology | Wang Q.,Hunan City University | Cheng X.,Anhui Key Laboratory of Natural Disaster Process and Prevention
Journal of Networks | Year: 2013

In view of the problem that computing shortest paths in a graph is a complex and time-consuming process, and the traditional algorithm that rely on the CPU as computing unit solely can't meet the demand of real-time processing, in this paper, we present an all-pairs shortest paths algorithm using MPI+CUDA hybrid programming model, which can take use of the overwhelming computing power of the GPU cluster to speed up the processing. This proposed algorithm can combine the advantages of MPI and CUDA programming model, and can realize two-level parallel computing. In the cluster-level, we take use of the MPI programming model to achieve a coarse-grained parallel computing between the computational nodes of the GPU cluster. In the node-level, we take use of the CUDA programming model to achieve a GPU-accelerated fine grit parallel computing in each computational node internal. The experimental results show that the MPI+CUDA-based parallel algorithm can take full advantage of the powerful computing capability of the GPU cluster, and can achieve about hundreds of time speedup; The whole algorithm has good computing performance, reliability and scalability, and it is able to meet the demand of real-time processing of massive spatial shortest path analysis. © 2013 ACADEMY PUBLISHER. Source


Zhang P.-J.,Anhui Key Laboratory of Natural Disaster Process and Prevention | Zhang P.-J.,Anhui Normal University | Zhao Y.-Q.,Anhui Normal University | Men X.-D.,Anhui Normal University
Wetland Science | Year: 2012

Soils from wetlands with different historical land use patterns (hydroponie farming and dry farming) and returning under different restoration modes (low dam and high net for aquaculture, such as Baidang Lake area, and natural ecology restoration of wetland, such as Caizi Lake area) were sampled to reveal changes of soil biochemical properties after returning farmland to lake (RFL) along the Yangtze River in Anqing. The results showed that the amounts of soil microbial biomass carbon and the activities of soil phosphatase and catalase increased, however, the activities of soil saccharase and urease decreased after RFL in Caizi Lake area; no significant difference was found between urease activities in sub-surface soils and catalase activities in surface soils from wetlands with historical hydroponie farming (HHF) and those in wetlands with historical dry framing (HDF) after 18-year RFL, while soil urease activities in surface soils and catalase activities in subsurface soils, amounts of soil microbial biomass carbon, saccharase and phosphstase activities both in surface and sub-surface soils were significantly higher in wetlands with HHF than those in wetlands with HDF after 18-year RFL in Caizi Lake area; the amounts of soil microbial biomass carbon and the activities of soil saccharase, urease and phosphstase decreased, while the activities of soil catalase increased after 18-year RFL in Baidang Lake area; no significant difference was found between microbial biomass carbon amounts both in surface and subsurface soils from wetlands with HHF and those in wetlands with HDF, while urease activities both in surface and subsurface soils, saccharase activities in surface soils, and phosphatase activities in subsurface soils were significantly higher in wetlands with HHF than those in wetlands with HDF after 18-year RFL in Baidang Lake area; saccharase activities in subsurface soils, and phosphatase activities in surface soils, and catalase activities both in surface and subsurface soils were significantly lower in wetlands with HHF thanthose in wetlands with HDF after 18-year RFL in Baidang Lake area; the amounts of soil biomass carbon and the activities of urease, saccharase, and phosphatase in semi-natural wetlands were lower than those in most of other sampling ecotesseras in the same lake area. Source


Wu Q.,Anhui Normal University | Wang Q.,Hunan City University | Cheng X.,Anhui Key Laboratory of Natural Disaster Process and Prevention
Journal of Theoretical and Applied Information Technology | Year: 2013

In view of the problem that massive spatial data interpolation is a complex and time-consuming computing process, and the traditional CPU implementation methods can't meet the real-time processing demand, in this paper, we propose a parallel bilinear spatial interpolation algorithm, which is accelerated by the graphic processing unit(GPU) and implemented in compute unified device architecture(CUDA). Firstly, we introduce the basic idea of general purpose computing on graphics processing units (GPGPU) and then discuss the technology of the CUDA programming model. Secondly, we introduce the principle of the bilinear interpolation algorithm and analyze the feasibility of mapping the bilinear interpolation algorithm program onto the GPU, and then we provide detail of implementing our parallel bilinear spatial interpolation algorithm on GPU that uses the CUDA programming model. Finally, we conduct several groups of experiments to demonstrate the strength of our GPU implementation method by measuring the performance over standard CPU implementation. The experimental results show that the GPGPU-based parallel algorithm can take full advantage of the GPU's parallel computing capabilities, and can achieve about 40 times speedup; it is able to meet the demand of real-time processing of massive spatial data interpolation. © 2005 - 2013 JATIT & LLS. All rights reserved. Source


Sun P.,Anhui Normal University | Sun P.,Anhui Key Laboratory of Natural Disaster Process and Prevention | Zhang Q.,Suzhou University | Zhang Q.,Sun Yat Sen University | And 3 more authors.
Stochastic Environmental Research and Risk Assessment | Year: 2016

The Tarim River basin, China, is a typical arid inland river basin in China. Management of water resources and agricultural development rely heavily on the understanding of droughts. In this study, an integrated drought index is proposed, based on the Standardized Precipitation Evapotranspiration Index and the Standardized Runoff Index, and then the changing properties of drought regimes have been analyzed using a Markov Chain model. Results indicate that: (1) the Kaidu and Aksu Rivers are dominated by prompt transition between hydrological and meteorological droughts. Long-lasting droughts heavily impact agricultural development in the Kaidu and Yarkand River basins; (2) the Kaidu and Aksu River basins are influenced mainly by hydro-meteorological droughts and hydrological drought is dominant in the Yarkand River basin; (3) different drought conditions are the results of different sources of river runoff. Increasing precipitation alleviate droughts in the Tarim River basin. However, a drying tendency can still be found in the Kaidu River basin; (4) higher probability is detected for the transition from both meteorological and hydrological wet to both meteorological and hydrological dry, implying that the Tarim River basin is sensitive to both meteorological and hydrological droughts. Results of this study are of practical value for the regional management of water resources, planning of agricultural irrigation, and measures for mitigation of hydrological and meteorological droughts. © 2016 Springer-Verlag Berlin Heidelberg Source


Lu M.,Anhui Normal University | Lu M.,Anhui Key Laboratory of Natural Disaster Process and Prevention | Gao C.,Anhui Normal University | Su B.,National Climate Center | And 3 more authors.
Journal of Natural Disasters | Year: 2015

Based on the precipitation data during Jan. 1, 1959 and Dec. 31, 2008 from 110 stations around Huaihe River basin, AM and POT extreme precipitation sequences were established, 33 distribution functions of 4 categories were applied to fit the extreme precipitation sequences. Then the optimal probability distribution model was established. The results show that, daily spatial distribution of average precipitation of 1959-2008 of the basin reduces gradually from both boundaries to the center of the basin, and there are two strong precipitation centers, namely Huaihe River upstream region and eastern Yishusi valley, exist in the region. Also, K-S method checking showed that, Wakeby function is the optimal probabilistic distribution function for the two series AM. The error rate of the estimated values from the observed values increases with the increase of the actual precipitation, and the errors of most stations are less than 20%. According to analysis of the shape and scale parameters of the optimal probability distribution model, the probabilities of extreme precipitation are larger in zhumadian, Funan, Huainan regions and the intersection region of Anhui, Shandong and Jiangsu Provinces; the changes of extreme precipitation are not stable in the surroundings of the Huaihe River main stream and downstream areas. Based on the shape and scale parameters of optimal probability distribution model, the extreme precipitation hazard map was drawn. The map may provide a theoretical reference for the work of disaster prevention and mitigation of extreme precipitation events. Source

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