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A Distributed Workflow Management System with Case Study of Real-life Scientific Applications on Grids

机译:分布式工作流管理系统,以实际的网格科学应用为例

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Next-generation scientific applications feature complex workflows comprised of many computing modules with intricate inter-module dependencies. Supporting such scientific workflows in wide-area networks especially Grids and optimizing their performance are crucial to the success of collaborative scientific discovery. We develop a Scientific Workflow Automation and Management Platform (SWAMP), which enables scientists to conveniently assemble, execute, monitor, control, and steer computing workflows in distributed environments via a unified web-based user interface. The SWAMP architecture is built entirely on a seamless composition of web services: the functionalities of its own are provided and its interactions with other tools or systems are enabled through web services for easy access over standard Internet protocols while being independent of different platforms and programming languages. SWAMP also incorporates a class of efficient workflow mapping schemes to achieve optimal end-to-end performance based on rigorous performance modeling and algorithm design. The performance superiority of SWAMP over existing workflow mapping schemes is justified by extensive simulations, and the system efficacy is illustrated by large-scale experiments on real-life scientific workflows for climate modeling through effective system implementation, deployment, and testing on the Open Science Grid.
机译:下一代科学应用程序具有复杂的工作流程,这些工作流程由许多计算模块组成,这些模块具有复杂的模块间依赖性。在广域网(尤其是网格)中支持此类科学工作流程并优化其性能对于协作科学发现的成功至关重要。我们开发了科学的工作流程自动化和管理平台(SWAMP),使科学家能够通过基于Web的统一用户界面在分布式环境中方便地组装,执行,监视,控制和引导计算工作流程。 SWAMP体系结构完全建立在Web服务的无缝组合上:提供了其自身的功能,并通过Web服务实现了与其他工具或系统的交互,从而可以轻松地通过标准Internet协议进行访问,同时独立于不同的平台和编程语言。 SWAMP还结合了一类有效的工作流映射方案,以基于严格的性能建模和算法设计来实现最佳的端到端性能。广泛的仿真证明了SWAMP相对于现有工作流映射方案的性能优越性,并且通过在开放式科学网格上有效实施,部署和测试有效的气候模型的现实科学工作流的大规模实验,证明了系统的有效性。 。

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