On the feasibility of running entity-level simulations on grid platforms

Alan Su, F. Berman, H. Casanova
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引用次数: 2

Abstract

Scientists have long relied on abstract models to study phenomena that are too complex for direct observation and experimentation. As new scientific modeling methodologies emerge, new computing technologies must be developed. In this paper, we focus on entity-level modeling, a modeling approach that is gaining prevalence in many scientific fields. Although the principles of entity-level modeling are straightforward, entity-level simulations require a large amount of compute resource and grid platforms can meet such resource needs. Unfortunately, efficient large-scale distributed entity-level simulations have proven elusive, typically due to nondeterminism that renders classical distributed application deployment strategies ineffective. In this work, we propose a method for dynamically remapping application tasks to cope with this inherent nondeterminism. We evaluate the efficacy of this method in a simulated grid computing environment and discuss the feasibility of executing entity-level applications on grids.
论在网格平台上运行实体级仿真的可行性
长期以来,科学家们一直依靠抽象模型来研究那些过于复杂而无法直接观察和实验的现象。随着新的科学建模方法的出现,必须开发新的计算技术。在本文中,我们关注实体级建模,这是一种在许多科学领域中越来越流行的建模方法。虽然实体级建模的原理简单明了,但实体级仿真需要大量的计算资源,网格平台可以满足这种资源需求。不幸的是,高效的大规模分布式实体级模拟已被证明是难以实现的,这通常是由于不确定性导致经典的分布式应用程序部署策略无效。在这项工作中,我们提出了一种动态重新映射应用程序任务的方法来处理这种固有的不确定性。我们在模拟网格计算环境中评估了该方法的有效性,并讨论了在网格上执行实体级应用程序的可行性。
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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