SBIR Phase I: GPU-based Raster Processing Algorithms

SBIR 第一阶段：基于 GPU 的光栅处理算法

• 批准号: 0945742
• 负责人: Robert Cheetham
• 金额: $ 15万
• 依托单位: Azavea Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0945742&HistoricalAwards=false
• 关键词: SBIR; Phase; GPU; based; Raster

This Small Business Innovation Research (SBIR) Phase I project will test the feasibility of using Graphics Processing Units (GPU's) for substantially increasing the performance of raster Geographic Information Systems (GIS) software operations. Map Algebra is a linguistic and algorithm framework for combining and transforming raster data and is the basis for raster-based analysis in all contemporary desktop GIS products. It is used for many types of government and business needs including ecology, land conservation, business siting, watershed analysis, transportation planning, hazard risk assessment, wildfire propagation and many other domains. However, particularly when working with large data sets, raster processing is usually too slow to support real-time calculation for web-based applications, even when the work can be distributed across multiple machines. It is therefore mostly consigned to workstation environments and people trained in the techniques. This project will focus its efforts on raster processing for server-based applications, where it is believed that both the greatest improvements can be made, there is a substantial market opportunity and, given the types of applications to which these techniques are applied, great potential for positive social impact. Most contemporary work in geographic information systems is directed at three types of activity: a) database development; b) desktop analysis and map production; and c) web-based display of maps for a variety of purposes. This project is directed at enabling a far broader audience, through use in web-based software applications, to perform sophisticated analysis with real-time results. If successful, this will enable real-time, online calculation of open space acquisition models, sea level inundation impact, natural hazard assessment, military scenario planning and travel cost calculation, to name only a few applications. These applications are currently all tied to desktop systems due to the significant amount of time, memory and processing power required to execute the operations. By moving these calculations to the GPU, it is believed that at least an order of magnitude improvement in the performance can be made and such applications could move to from the desktop to a web-based platform.

该小企业创新研究（SBIR）第一阶段项目将测试使用图形处理单元（GPU）大幅提高栅格地理信息系统（GIS）软件操作性能的可行性。地图代数是一个用于组合和转换栅格数据的语言和算法框架，是所有当代桌面GIS产品中基于栅格的分析的基础。它被用于许多类型的政府和商业需求，包括生态、土地保护、商业选址、流域分析、交通规划、危害风险评估、野火传播和许多其他领域。然而，特别是在处理大型数据集时，栅格处理通常太慢，无法支持基于web的应用程序的实时计算，即使工作可以分布在多台机器上。因此，它主要委托给工作站环境和受过技术培训的人员。该项目将把重点放在基于服务器的应用程序的栅格处理上，相信在这方面可以取得最大的改进，有大量的市场机会，并且考虑到这些技术所应用的应用类型，具有积极社会影响的巨大潜力。大多数地理信息系统的当代工作是针对三种类型的活动：a)数据库开发；B)桌面分析和地图制作；c)基于网络的地图显示，用于各种目的。该项目旨在通过使用基于web的软件应用程序，使更广泛的受众能够使用实时结果执行复杂的分析。如果成功，这将实现开放空间获取模型的实时在线计算，海平面淹没影响，自然灾害评估，军事情景规划和旅行成本计算，仅举几例应用。由于执行操作需要大量的时间、内存和处理能力，这些应用程序目前都与桌面系统绑定在一起。通过将这些计算转移到GPU上，人们相信至少可以在性能上提高一个数量级，并且这些应用程序可以从桌面转移到基于web的平台上。