检索结果-南通市图书馆

Accelerating geospatial analysis on gpus using CUDA

Journal of Zhejiang University-Science C(Computers and Electronics) 2011年第12期12卷 990-999页

作者： Ying-jie XIA Li KUANG Xiu-mei LI Hangzhou Institute of Service Engineering Hangzhou Normal University Hangzhou 310012 China Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Provincial Key Laboratory for Computer Information Processing Technology Sooehow University Soochow 215006 China

Inverse distance weighting (IDW) interpolation and viewshed are two popular algorithms for geospatial *** interpolation assigns geographical values to unknown spatial points using values from a usually scattered set of known points,and viewshed identifies the cells in a spatial raster that can be seen by *** the implementations of both algorithms are available for different scales of input data,the computation for a large-scale domain requires a mass amount of cycles,which limits their *** to the growing popularity of the graphics processing unit (gpu) for general purpose applications,we aim to accelerate geospatial analysis via a gpu based parallel computing *** this paper,we propose a generic methodological framework for geospatial analysis based on gpu and its programming model Compute Unified Device Architecture (CUDA),and explore how to map the inherent parallelism degrees of IDW interpolation and viewshed to the framework,which gives rise to a high computational *** CUDA-based implementations of IDW interpolation and viewshed indicate that the architecture of gpu is suitable for parallelizing the algorithms of geospatial *** results show that the CUDA-based implementations running on gpu can lead to dataset dependent speedups in the range of 13-33-fold for IDW interpolation and 28-925-fold for viewshed *** computation time can be reduced by an order of magnitude compared to classical sequential versions,without losing the accuracy of interpolation and visibility judgment.

关键词： general purpose gpu CUDA Geospatial analysis Parallelization

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Optimization of a precise integration method for seismic modeling based on graphic processing unit

引用

Earthquake Science 2010年第4期23卷 387-393页

作者： Jingyu Li Genyang Tang Tianyue Hu School of Earth and Space Sciences Peking University Beijing 100871 China Department of Earth Sciences Cambridge University Cambridge CB2 3EQ United Kingdom

general purpose graphic processing unit （gpu） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a gpu-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, gpu parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and gpu calculation brings high computational efficiency, which means that high-performing gpu parallel calculation can make seismic forward modeling closer to real seismic records.

关键词： precise integration method seismic modeling general purpose gpu graphic processing unit

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：