Analyzing and Modeling of Medical Data on Distributed Computing Infrastructures

G. Terstyánszky, T. Kiss, V. Korkhov, S. Olabarriaga
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Abstract

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.
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基于分布式计算基础设施的医疗数据分析与建模
研究人员想要分析医疗保健数据,这可能需要大量的计算和数据资源。要拥有它们,它们需要访问分布式计算基础设施(DCI)。使用它们需要研究人员可能不具备的专业知识。工作流可以隐藏基础结构。有许多工作流系统,但它们不能互操作。学习工作流系统并在工作流系统中创建工作流可能需要大量的努力。考虑到这些努力,期望研究人员学习新的工作流系统是不合理的,如果他们想要运行其他工作流系统的工作流。因此,互操作性的缺乏阻碍了工作流的共享,并且浪费了大量的研究工作。FP7在可用数据中心上大规模科学模拟的共享可互操作工作流(SHIWA)项目开发了粗粒度互操作性(CGI)来实现工作流共享。该项目创建了SHIWA仿真平台(SSP),以支持CGI作为生产级服务。本文描述了如何将CGI方法用于医疗保健中的分析和模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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