Adaptive algorithms are an important technique to achieve portable high performance. They choose among solution methods and optimizations according to expected performance on a particular machine. Grid environments make the adaptation problem harder, because the optimal decision may change across runs and even during runtime. Therefore, the performance model used by an adaptive algorithm must be able to change decisions without high overhead. In this paper, we present work that is modifying previous research into rapid performance modeling to support adaptive grid applications through sampling and high granularity modeling. We also outline preliminary results that show the ability to predict differences in performance among algorithms in the same program.
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Virtual Observatory (VO) is a collection of interoperating data archives and software tools. Taking advantages of the latest information technologies, it aims to provide a data-intensively online research environment for astronomers all around the world. A large number of high-qualified astronomical software packages and libraries are powerful and easy of use, and have been widely used by astronomers for many years. Integrating those toolkits into the VO system is a necessary and important task for the VO developers.
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Beginning with version 2.5 (currently in Preview Edition) building Silverlight 2 applications, and especially assembling the User Interface components such as items from the toolbox, and layout controls, is easier than ever. A Note on This Tutorial. The history of the material for this tutorial is that Scott Guthrie wrote a terrific introduction to this material at the end of February, which he gave me permission to turn into a series of videos, currently (or soon to be) available on Silverlight.NET. This tutorial completes the circle by building on the videos and integrating the material into the Silverlight Tutorial series. The project we’re setting out to build is very similar to the Silverlight chat service built by ScottGu, and is shown in Figure 5-1
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Modern Geographical Information Systems (GIS) [1] provide a service-oriented architecture for interacting with geographical data sets and related maps. Web-based GIS systems are architected around the same principles as more general Web service systems based on SOAP [2], WSDL [3], and REST. Mirroring the World Wide Web Consortium and OASIS Web service standards-making bodies, the Open Geospatial Consortium [5] defines open standards for messages, XML data formats, and access protocols that are specific to the GIS community. In addition to OGC-based services, there are many companies (such as ESRI and AutoDesk) that provide proprietary, commercial solutions. Services from these various providers are not normally interoperable.
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Cyberinfrastructure 1 and e-Science 1 are conventionally presented in terms of Grid technologies 2 3 that support remote access to computational science resources (such as supercomputers), distributed data management, networked instruments and similar technologies. Web Services are a key technology for realizing this vision 4 5. In contrast to these heavyweight approaches, however, many important innovations in network programming are emerging outside the (by now) traditional Web Services framework and are collectively known as Web 2.0 6. As we discuss in this chapter, these developments need to be tracked and incorporated into the e-Science vision.
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This tutorial serves as a rapid overview of Autodesk’s Maya software. The 3D production pipeline can be broken down into several distinct activities and skill sets - we will cover all of these to give you a sense for building an entire scene from start to finish. The biological topic will be to create a visual depiction of how calcium chelation can affect cadherin flexibility. The tutorial is divided into 5 sections, each of which focus on an aspect of the 3D pipeline:
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Install and run examples Open Grid Services Infrastructure compliant You are a scientist, a businessperson, or an engineer. You are always looking for faster ways to do your computer processing, better ways to store and retrieve your data, more efficient ways to interact with your customers or suppliers or clients, all while spending less money. You may be asking yourself these questions, among others: How can I analyze the value of an investment portfolio in minutes, rather than hours? How can I significantly accelerate the drug discovery process?
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Everything You Wanted to Know about Globus, but Were Afraid To Ask Describing Globus Toolkit Version 4 An Early and Incomplete Draft Please send comments, criticisms, and suggestions to: foster@mcs.anl.gov Preface The Globus Toolkit (GT) has been developed since the late 1990s to support the development of service-oriented distributed computing applications and infrastructures. Core GT components address basic issues relating to security, resource access and management, data movement and management, resource discovery, and so forth. A broader “Globus universe” comprises numerous tools and components that build on core GT4 functionality to provide many useful application- level functions.
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