One of the great benefits of using Oracle products is their support for multiple programming frameworks. By supporting .NET, Java/J2EE, PHP, and C/C++ applications, all developers can use Oracle’s advanced database features, providing true flexibility for development organizations. Each of Oracle’s data access drivers is designed to maximize performance of its respective framework and to enable access to the latest database features.
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Brains, unlike artificial neural nets, use sym- bols to summarise and reason about perceptual input. But unlike symbolic AI, they “ground” the symbols in the data: the symbols have meaning in terms of data, not just meaning imposed by the outside user. If neural nets could be made to grow their own symbols in the way that brains do, there would be a good prospect of combining neural networks and symbolic AI, in such a way as to combine the good features of each.
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This paper will discuss the difficulties and methods involved in debugging the Linux kernel on huge clusters. Intermittent errors that occur once every few years are hard to debug and become a real problem when running across thousands of machines simultaneously. The more we scale clusters, the more reliability becomes critical. Many of the normal debugging luxuries like a serial console or physical access are unavailable. Instead, we need a new strategy for addressing thorny intermittent race conditions. This paper presents the case for a new set of tools that are critical to solve these problems and also very useful in a broader context. It then presents the design for one such tool created from a hybrid of a Google internal tool and the open source LTTng project. Real world case studies are included.
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BioTeam first became interested in Univa UD’s software efforts after hearing Univa CTO Steve Tueckespeak in Regensburg, Germany at the 2007 Grid Engine workshop. Shortly after that event Univa formally became Univa UD after merging with United Devices. At the time, Steve’s company seemed to be one of the few companies positioning themselves to offer full support and professional services encompassing commonly used open source products such as Sun Grid Engine that BioTeam often works with in the field. Individually these popular open source resources are relatively easy to acquire but Univa UD seemed to be making an interesting effort to become the one stop shop for a fully supported and integrated set of commonly required tools and technology.
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Microsoft® Windows® Compute Cluster Server 2003 is designed specifically to run parallel, high-performance computing (HPC) applications to solve complex computations. Windows Compute Cluster Server 2003 accelerates time-to-insight by providing an HPC platform that is simple to deploy, operate and integrate with existing infrastructure and tools.
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An important argument for the introduction of software managed clusters is that of scale: By constructing the cluster out of commodity compute elements, one can, by simply adding new elements, improve the reliability of the overall system in terms of performance and in availability. The limits to how far such a cluster can be scaled seems to be dependent on the scalability of its management software, which in its core has a collection of distributed algorithms to guarantee the correct operation of the cluster. The complexity of these algorithms makes them a vulnerable component of the system in terms of their impact on the overall scalability of the system.
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The X1 Content Connector for Microsoft Exchange gives users immediate access to any content in their Exchange cluster through the X1 Enterprise Client. X1 enables powerful, unified search capability across Exchange server clusters, local files and local email. Users can search Exchange and receive results federated with search results from local and enterprise server-based content. Through seamless integration with Microsoft Outlook ®, users can perform common email functions from inside the X1 interface
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ODA is an OSCAR Database API to make it easy for users to use the OSCAR database. When using ODA, there is no need to know how to connect the database or determine what its schema look like. ODA deployed on the OSCAR Subversion trunk uses Perl modules to connect, update, and query the database. Also, all the database subroutines for the end users are defined in a single Perl module, which is a collection of database subroutines and does the intermediate work between back-end database and OSCAR installation. As the previous paper showed, the old ODA has three problems. First, it can not fully support new features of OSCAR.
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