Grids as Production Computing Environments: The Engineering Aspects of NASA's Information Power Grid
HPDC(1999)
摘要
Information Power Grid (IPG) is the name of NASA's project to build a fully distributed computing and data management environment - a Grid. The IPG project has near, medium, and long-term goals that represent a continuum of engineering, development, and research topics. The overall goal is to provide the NASA scientific and engineering communities a substantial increase in their ability to solve problems that depend on use of large-scale and/or dispersed resources: aggregated computing, diverse data archives, laboratory instruments and engineering test facilities, and human collaborators.The approach involves infrastructure and services that can locate, aggregate, integrate, and manage resources from across the NASA enterprise. An important aspect of IPG is to produce a common view of these resources, and at the same time provide for distributed management and local control. In addition to addressing the overall goal of enhanced science and engineering, there is a potential important side effect. With a large collection of resources that have common use interfaces and a common management approach, the potential exists for a considerable pool of computing capability that could relatively easily, e.g., be called on in extraordinary situations such as crisis response.IPG is a collaboration between NASA and the NSF PACIs [1], and the initial set of distributed services are based on the Globus metacomputing system [5]. The near term goal of IPG is a prototype production Grid, which entails developing, deploying, and supporting infrastructure like LDAP information servers and PKI security services, and the engineering aspects of adapting R&D systems like Globus to a production environment.
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common use interface,ipg project,aggregated computing,engineering community,engineering aspects,nasa enterprise,common management approach,information power grid,engineering aspect,production computing environments,engineering test facility,overall goal,side effect,distributed processing,resource management,data engineering,grid computing,distributed computing,data management,energy management,production
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