GEMS中的慷慨与暴饮暴食:网格分子模拟

J. Wozniak, P. Brenner, D. Thain, A. Striegel, J. Izaguirre
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引用次数: 22

摘要

生物分子模拟产生的输出数据比传统计算系统有效管理的数据要多。研究人员需要分布式系统,以允许资源池,共享模拟数据,并可靠地发布试探性和最终结果。为了满足这一需求,我们设计了GEMS,这是一个使生物分子研究人员能够存储、搜索和共享大规模模拟数据的系统。主要的设计问题是在慷慨和贪吃之间取得平衡。一方面,存储提供商希望慷慨地与协作者共享资源。另一方面,未经检查的数据生成器可能非常贪吃,很容易复制不必要的数据,直到填满所有可用空间。为了平衡慷慨和贪婪,GEMS允许存储提供者和数据生产者声明和执行存储消费和数据复制的策略。通过利用仿真数据的已知属性,系统能够区分必须保留的高值最终结果和可以在必要时删除和重新生成的低值中间结果。我们已经在一个工作站集群上构建了GEMS的原型,并演示了它存储新数据、在策略限制内进行复制以及从故障中恢复的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generosity and gluttony in GEMS: grid enabled molecular simulations
Biomolecular simulations produce more output data than can be managed effectively by traditional computing systems. Researchers need distributed systems that allow the pooling of resources, the sharing of simulation data, and the reliable publication of both tentative and final results. To address this need, we have designed GEMS, a system that enables biomolecular researchers to store, search, and share large scale simulation data. The primary design problem is striking a balance between generosity and gluttony. On one hand, storage providers wish to be generous and share resources with their collaborators. On the other hand, an unchecked data producer can be gluttonous and easily replicate data unnecessarily until it fills all available space. To balance generosity and gluttony, GEMS allows both storage providers and data producers to state and enforce policies on the consumption of storage and the replication of data. By taking advantage of known properties of simulation data, the system is able to distinguish between high value final results that must be preserved and low value intermediate results that can be deleted and regenerated if necessary. We have built a prototype of GEMS on a cluster of workstations and demonstrate its ability to store new data, to replicate within policy limits, and to recover from failures.
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