Titlebook: Parallel Processing and Applied Mathematics, Part II; 9th International Co Roman Wyrzykowski,Jack Dongarra,Jerzy Wa?niewski Conference proc

Ccu106

Fine Grained Parallelism in Recursive Function Callsism, mainly by focusing on calls which can be invoked in parallel. However, not all recursive algorithms allow concurrent execution of function calls. In this paper we study how we can extract concurrency from those recursive functions which cannot be parallelized with the commonly used methods. The

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On-Line Grid Monitoring Based on Distributed Query Processingeduction. We present a?solution for on-line monitoring of large-scale computing infrastructures based on Complex Event Processing principles and technologies. We focus on leveraging CEP for distributed processing of client queries and monitoring data streams. This results in significant reduction of

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Distributed Memory Virtualization with the Use of SDDSfLtributed .s of multicomputer nodes. In other words they are a tool for distributed memory virtualization. Applications that use . benefit from a fast data access and a scalability offered by such data structures. On the other hand, adapting an application to work with . may require significant chang

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Dynamic Compatibility Matching of Services for Distributed Workflow Executionay have the same functionality, they may accept input and produce output in different formats. The proposed solution learns matching of outputs and inputs at runtime and uses this knowledge in subsequent runs of workflow applications. The presented solution was implemented in an existing workflow ex

exigent

Fortify

Dynamic Business Metrics-driven Resource Provisioning in Cloud Environmentsatic scalability feature enables cloud-based systems to seamlessly adjust to the constantly changing environment of the Internet. Despite their usefulness there is still much space for improvements. In this paper we introduce an approach to automatic infrastructure scaling, based on observation of b