Scheduling large parametric modelling experiments on a distributed meta-computer
Scheduling large parametric modelling experiments on a distributed meta-computer
复制标题
在分布式元计算机上安排大型参数建模实验
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
J. Giddy
中科院分区：
文献类型：
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作者：
D. Abramson;J. Giddy
Nimrod是一个工具，它使得基于对一系列参数化场景的探索来并行和分发大型计算实验变得容易。使用Nimrod，可以指定和生成参数实验，然后控制跨分布式计算机的代码执行。Nimrod已被应用于一系列应用领域，包括生物信息学、运筹学、电子CAD、生态建模和计算机电影。Nimrod在生成工作方面非常成功，但它没有包含在底层资源上调度计算的机制。因此，用户不会知道实验可能何时完成。我们目前正在构建一个新版本的Nimrod，称为Nimrod/G。Nimrod/G将把Nimrod工作岗位生成技术与Globus整合在一起，Globus是一个国际项目，它正在为大型元计算应用程序构建底层基础设施。使用Globus，Nimrod用户可以指定计算实验的时间和成本限制。Globus提供了在使用联网排队超级计算机时估计执行时间和等待延迟的机制。然后，Nimrod/G将使用这些信息，以满足用户指定的最后期限和成本预算的方式安排工作。通过这种方式，多个Nimrod用户可以从计算网络获得服务质量。
Nimrod is a tool which makes it easy to parallelise and distribute large computational experiments based on the exploration of a range of parameterised scenarios. Using Nimrod, it is possible to specify and generate a parametric experiment, and then control the execution of the code across distributed computers. Nimrod has been applied to a range of application areas, including Bioinformatics, Operations Research, Electronic CAD, Ecological Modelling and Computer Movies. Nimrod was extremely successful at generating work, but it contained no mechanisms for scheduling the computation on the underlying resources. Consequently, users would not have any idea when an experiment might complete. We are currently building a new version of Nimrod, called Nimrod/G. Nimrod/G will integrate Nimrod job generation techniques with Globus, an international project which is building the underlying infrastructure for large meta-computing applications. Using Globus, it will be possible for Nimrod users to specify time and cost constraints on computational experiments. Globus provides mechanisms for estimating execution time and waiting delays when using networked queued supercomputers. Nimrod/G will then use these to schedule the work in a way which meets user specified deadlines and cost budgets. In this way, multiple Nimrod users can obtain a quality-of-service from the computational network.