The mean shift image segmentation algorithm is very computationintensive. To address the need to deal with a large number of remotesensing (RS) image segmentations in real-world applications, this studyhas investigat...The mean shift image segmentation algorithm is very computationintensive. To address the need to deal with a large number of remotesensing (RS) image segmentations in real-world applications, this studyhas investigated the parallelization of the mean shift algorithm on asingle graphics processing unit (GPU) and a task-scheduling methodwith message passing interface (MPI)+OpenCL programming model on aGPU cluster platform. This paper presents the test results of the parallelmean shift image segmentation algorithm on Shelob, a GPU clusterplatform at Louisiana State University, with different datasets andparameters. The experimental results show that the proposed parallelalgorithm can achieve good speedups with different configurations andRS data and can provide an effective solution for RS image processingon a GPU cluster.展开更多
针对使用中央处理器(Central Processing Unit, CPU)硬件实现密度聚类、相似性度量等算法提取船舶习惯航迹的过程中存在复杂度高、计算时间长等方面的不足,提出使用图形处理器(Graphics Processing Unit, GPU)高性能计算及GPU优化算法...针对使用中央处理器(Central Processing Unit, CPU)硬件实现密度聚类、相似性度量等算法提取船舶习惯航迹的过程中存在复杂度高、计算时间长等方面的不足,提出使用图形处理器(Graphics Processing Unit, GPU)高性能计算及GPU优化算法以提升船舶轨迹相似性度量与聚类的速度性能,大幅缩短船舶轨迹特征提取过程中的时间开销。利用长江南槽交汇水域船舶自动识别系统(Automatic Identification System, AIS)动态船舶轨迹信息进行方法验证,通过对比传统基于CPU的方法验证了所提出的基于GPU的船舶轨迹相似性度量及聚类算法存在较优的速度性能,为快速提取研究水域中的船舶特征提供新的理论依据。展开更多
在高性能计算领域,拥有强大浮点计算能力的协处理器正在快速发展。近年来,利用协处理器(如GPU)来加速时域有限差分FDTD算法的计算过程成为电磁研究领域的热点问题。在GPU集群上实现了三维UPML-FDTD算法并进行了优化。采用电偶极子激励...在高性能计算领域,拥有强大浮点计算能力的协处理器正在快速发展。近年来,利用协处理器(如GPU)来加速时域有限差分FDTD算法的计算过程成为电磁研究领域的热点问题。在GPU集群上实现了三维UPML-FDTD算法并进行了优化。采用电偶极子激励源对算法的模拟结果同解析解进行了验证,结果表明该算法具有较高的精度;同时,在NVIDIA Tesla M2070和K20mGPU集群上对FDTD算法的性能进行测试,对优化前后的计算结果以及GPU与CPU的计算性能进行了比较,并使用80块NVIDIA Tesla K20mGPU进行了可扩展性测试。从本文的研究结果可以看出,经过优化的FDTD算法性能有了较大的提升,而且FDTD算法在GPU集群上获得了比较理想的并行效率。展开更多
We have proposed a general numerical framework for plasma simulations on graphics processing unit clusters based on microscopic kinetic equations with full collision terms.Our numerical algorithm consistently deals wi...We have proposed a general numerical framework for plasma simulations on graphics processing unit clusters based on microscopic kinetic equations with full collision terms.Our numerical algorithm consistently deals with both long-range(classical forces in the Vlasov term)and short-range(quantum processes in the collision term)interactions.Providing the relevant particle masses,charges and types(classical,fermionic or bosonic),as well as the external forces and the matrix elements(in the collisional integral),the algorithm consistently solves the coupled multi-particle kinetic equations.Currently,the framework is being tested and applied in the field of relativistic heavy-ion collisions;extensions to other plasma systems are straightforward.Our framework is a potential and competitive numerical platform for consistent plasma simulations.展开更多
基金the Engineering Research Center of Geospatial Information and Digital Technology(NASG)(Wuhan University)[grant number SIDT20170601]Hubei Provincial Key Laboratory of Intelligent Geoinformation Processing(China University of Geosciences(Wuhan))[grant number KLIGIP2016A03]+2 种基金the Fundamental Research Funds for the Central Universities[grant number ZYGX2015J111]Key Laboratory of Spatial Data Mining&Information Sharing of the Ministry of Education(Fuzhou University)[grant number 2016LSDMIS06],[grant number 2017LSDMIS03]and also the National Science Foundation of the United States(Award Nos.1251095,1723292)。
文摘The mean shift image segmentation algorithm is very computationintensive. To address the need to deal with a large number of remotesensing (RS) image segmentations in real-world applications, this studyhas investigated the parallelization of the mean shift algorithm on asingle graphics processing unit (GPU) and a task-scheduling methodwith message passing interface (MPI)+OpenCL programming model on aGPU cluster platform. This paper presents the test results of the parallelmean shift image segmentation algorithm on Shelob, a GPU clusterplatform at Louisiana State University, with different datasets andparameters. The experimental results show that the proposed parallelalgorithm can achieve good speedups with different configurations andRS data and can provide an effective solution for RS image processingon a GPU cluster.
文摘针对使用中央处理器(Central Processing Unit, CPU)硬件实现密度聚类、相似性度量等算法提取船舶习惯航迹的过程中存在复杂度高、计算时间长等方面的不足,提出使用图形处理器(Graphics Processing Unit, GPU)高性能计算及GPU优化算法以提升船舶轨迹相似性度量与聚类的速度性能,大幅缩短船舶轨迹特征提取过程中的时间开销。利用长江南槽交汇水域船舶自动识别系统(Automatic Identification System, AIS)动态船舶轨迹信息进行方法验证,通过对比传统基于CPU的方法验证了所提出的基于GPU的船舶轨迹相似性度量及聚类算法存在较优的速度性能,为快速提取研究水域中的船舶特征提供新的理论依据。
文摘在高性能计算领域,拥有强大浮点计算能力的协处理器正在快速发展。近年来,利用协处理器(如GPU)来加速时域有限差分FDTD算法的计算过程成为电磁研究领域的热点问题。在GPU集群上实现了三维UPML-FDTD算法并进行了优化。采用电偶极子激励源对算法的模拟结果同解析解进行了验证,结果表明该算法具有较高的精度;同时,在NVIDIA Tesla M2070和K20mGPU集群上对FDTD算法的性能进行测试,对优化前后的计算结果以及GPU与CPU的计算性能进行了比较,并使用80块NVIDIA Tesla K20mGPU进行了可扩展性测试。从本文的研究结果可以看出,经过优化的FDTD算法性能有了较大的提升,而且FDTD算法在GPU集群上获得了比较理想的并行效率。
基金supported by National Natural Science Foundation of China(No.12105227)。
文摘We have proposed a general numerical framework for plasma simulations on graphics processing unit clusters based on microscopic kinetic equations with full collision terms.Our numerical algorithm consistently deals with both long-range(classical forces in the Vlasov term)and short-range(quantum processes in the collision term)interactions.Providing the relevant particle masses,charges and types(classical,fermionic or bosonic),as well as the external forces and the matrix elements(in the collisional integral),the algorithm consistently solves the coupled multi-particle kinetic equations.Currently,the framework is being tested and applied in the field of relativistic heavy-ion collisions;extensions to other plasma systems are straightforward.Our framework is a potential and competitive numerical platform for consistent plasma simulations.
