- Grid computing environments. - Overview of Grid computing environments. - 20.1 INTRODUCTION. - It puts the corresponding section of this book in context and integrates a survey of a set of 28 chapters gathered together by the Grid Computing Environment (GCE) group of the Global Grid Forum, which is being published in 2002 as a special issue of Concurrency and Computation: Practice and Experience. - Several of the chapters here are extensions or reprints of those papers.. - Often it takes the form of a Web portal that provides the user interface to a multitier Grid application development stack, but it may also be as simple as a GridShell that allows a user access to and control over Grid resources in the same way a conventional shell allows the user access to the file system and process space of a regular operating system.. - Grid Computing – Making the Global Infrastructure a Reality. - 20.2 OVERALL CLASSIFICATION. - Grid Computing Environments can be classified in several different ways. - One straight- forward classification is in terms of the technologies used. - Some of these issues are important for performance or architecture, but often can look to the user as not so important. - The ease of development using modern technologies often yields greater functionality in the GCE for a given amount of implementation effort. - Technology differences in the projects are important, but more interesting at this stage are the differences in capabilities and the model of computing explicit or implicit in the GCE.. - This leads to the concept of GCE collaboratories supporting sharing among scientific teams working on the same problem area.. - We can build a picture of different GCE approaches by viewing the problem as some sort of generalization of the task of computing on a single computer. - We can follow the lead of UNIX [and Legion (Chapter 10) in its distributed extension], and define a basic GCEShell providing access to the core distributed computing functions. - These two (or more) calls (component interactions) can represent different functions or the middle-tier call can be coupled with a high performance mirror. - typically the middle-tier provides control and the backend provides ‘raw data transfer’. - Chapter 21 has an excellent review of the different programming models for the Grid.. - Looking at commercial portals, one finds that they usually support sophisticated user interfaces with multiple subwindows aggregated in the user interface. - Middle tier or proxy Linkage. - Figure 20.1 Middle-tier and raw (HPC) linked components of an application.. - This aggregation is not stressed in any paper in this special issue although it is provided implicitly.. - Apart from particular features, a GCE usually implies a particular computing model for the Grid, and this model is reflected in the GCE architecture and the view of the Grid presented to the user. - For example, object models for applications are very popular, and this object view is reflected in the view of the Grid presented to the user by the GCE. - With this preamble, we can now classify the papers in this special issue. - 20.3 SUMMARY OF GCE PROJECTS AND FEATURES. - 20.3.1 Technology for building GCE systems. - In the previous section of this book we have described the basic architecture and tech- nologies needed to build a Grid, and we have described the basic component for the different types of GCEs mentioned in the previous section. - Chapter 21 provides an excel- lent overview of many of the backend application programming issues.. - References [4–7] and Chapter 26 describe, respectively, Java, CORBA, Python and Perl Commodity Grid interfaces to the Globus Toolkit. - Chapter 27, describes the Grid Portal Development Toolkit (GPDK), a suite of JavaBeans suitable for Java-based GCE environments. - The problem-solving environments (PSEs)in References [8–10] are built on top of the Java Commodity Grid Kit [4]. - The portals described in Chapter 28 are built directly on top of the Perl Commodity Grid Kit [7].. - this chapter designs and proto- types a possible event or messaging support for the Grid. - Chapter 22 describes the Narada Brokering system, which leverages peer-to-peer technology to provide a framework for routing messages in the wide area. - Reference [12] provides C support for interfacing to the Globus Toolkit, and por- tals exposing the toolkit’s capabilities can be built on the infrastructure of this paper.. - 20.3.2 Largely problem-solving environments. - GPDK builds on the Java CoG Kit [4], which by itself builds on the Globus Toolkit that finally builds on the native capabilities of the Grid component resources. - Reference [15] has an interesting discussion of the architectural changes to a ‘legacy’ PSE consequent to switching to a Grid Portal approach. - A similar portal is the XCAT Science portal [18], which is based on the concept of application Notebooks that contain web pages, Python scripts and control code specific to an application. - In this case, the Python script code plays the role of the GCEShell. - it also interfaces to the powerful Cactus distributed environment [20]. - This is also an important objective of the work on Cactus described in Chapter 23.. - 20.3.3 Largely basic GCEShell portals. - Here we describe the set of portals designed to support generic computing capabili- ties on the Grid. - This paper also describes how specific PSEs can be built on top of the basic GCEShell portal.. - Unicore [28] was one of the pioneering full-featured GCEShell portals developed originally to support access to a specific set of European supercomputers, but recently has been interfaced to the Globus Toolkit, and as described in Chapter 29, to the Open Grid Services Architecture described in Chapter 8. - 20.3.4 Security. - One of the primary tasks of any Grid portal is to manage secure access to Grid resources.. - Kerberos is required by some installations (DoD and DoE, for instance, in the United States), and Grid Computing Environments developed for them are based on this security model.. - 20.3.5 Workflow. - The latter integrates Grid work- flow with the dataflow paradigm, which is well established in the visualization community.. - We expect this to be a major topic of study in the future.. - 20.3.6 Data management. - Data intensive applications are expected to be critical on the Grid but support of this is not covered in the papers of this special issue. - This is primarily because of the fact that data management software is still relatively new on the Grid.. - 20.3.7 GCEShell tools. - In our GCE computing model, one expects a library of tools to be built up that add value to the basic GCEShell capabilities. - The previous two sections describe two tools – workflow and data management of special interest, and here we present a broad range of other tools that appeared in several chapters in this special issue.. - NetBuild [31] supports distributed libraries with automatic configuration of software on the wide variety of target machines on the Grids of growing heterogeneity.. - Chapter 33 describes another well-regarded parameter sweep system APST that builds on the AppLeS appli- cation level scheduling system.. - 20.3.8 GCE computing model. - In the preamble we suggested that it was interesting to consider the computing model underlying GCEs. - This refers to the way we think about the world of files, computers, databases and programs exposed through a portal. - Note that in the notation of Figure 20.1, MPI is at the ‘HPC backend linkage’ layer and not at the middleware. - Reference [10] supports the Cactus environment [20], Chapter 23] that has well- developed support for Grid computing at the HPC layer, that is, it supports backend programming interfaces and not the middle-tier GCEShell environment. - The astrophysics problem-solving environment of Reference [10] augments Cactus with a full middle-tier environment.. - ‘Middle tier’. - Figure 20.2 A proxy service programming model showing four types of interactions to and from users (portal interface), between proxy and raw resource, other middle-tier components and between other raw (HPC) resources.. - Figure 20.3 A wrapped application programming model showing three types of interactions to and from users (portal interface), to and from other middle-tier components, and between other raw (HPC) resources.. - to the input of the other from a UNIX shell command. - Such a hybrid-programming model with actions partly specified internally and partly specified at the service level is important to the success of the Grid and should be built into programming models for it.. - Actually going back to point 2 in Section 20.2, the proxy and NetSolve mod- els are not really different as indicated in Figures 20.2. - In the proxy model, one exposes the interaction between middle-tier and backend. - In the wrapped service model of NetSolve and Ninf, one presents a single entity to the user. - In both cases, one can have separate middle-tier and HPC (‘real’, ‘raw’ or ‘native’) communication. - In the XCAT model, a software component system [Chapter 9] is used, which implements the wrapped service or proxy model. - An additional aspect of the computing model that must be addressed by GCE systems is the way in which resources are managed. - While this is a concept that is not used in any of the current systems described here, there is a good chance it will be used as we scale Grid system to very large sizes.. - (2002) Features of the Java commodity grid kit. - Concurrency and Computation: Practice and Experience, 14, Grid Com- puting Environments Special Issue 13 – 14.. - Concurrency and Computation: Practice and Experience, 14, Grid Computing Environments Special Issue 13 – 14.. - (2002) pyGlobus: A python interface to the globus toolkit. - Concurrency and Com- putation: Practice and Experience, 14, Grid Computing Environments Special Issue 13 – 14.. - Concurrency and Computation: Practice and Experience, 14, Grid Computing Envi- ronments Special Issue 13 – 14.. - Concur- rency and Computation: Practice and Experience, 14, Grid Computing Environments Special Issue 13 – 14.. - Concurrency and Compu- tation: Practice and Experience, 14, Grid Computing Environments Special Issue 13 – 14.. - (2002) Web-based access to the grid using the grid resource broker portal. - Concurrency and Computation: Practice and Experience, 14, Grid Computing Environ- ments Special Issue 13 – 14.. - (2000) GridSim: A toolkit for the modeling and simulation of distributed resource management and scheduling for Grid Computing. - Concurrency and Computa- tion: Practice and Experience, 14, Grid Computing Environments Special Issue 13 – 14.. - (2002) The grid portal development kit. - Concurrency and Computation: Prac- tice and Experience, 14, Grid Computing Environments Special Issue 13 – 14, This article is reprinted in this Volume.. - Concurrency and Computation: Practice and Expe- rience, 14, Grid Computing Environments Special Issue 13 – 14.. - (2002) Innovations of the NetSolve grid comput- ing system. - (2000) UNICORE – A grid computing environment. - (2000) Economics paradigm for resource management and scheduling in grid computing. - (2002) A software development environment for grid computing. - (2002) Engineering an interoperable computational collaboratory on the grid
Xem thử không khả dụng, vui lòng xem tại trang nguồn hoặc xem
Tóm tắt