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Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids

机译:计算生命之树:利用桌面和服务网格的力量

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The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests.
机译:在生命科学的发展趋势研究,特别是在分子进化系统,正向着更大的数据集和不断更详细的进化模式,它可以产生大量的计算负荷。在过去的几年里,我们已经制定了旨在为研究人员提供及时需要完成这样的分析计算能力网格计算系统。我们的电网系统,被称为莱迪思的项目,是第一个网格计算的两种模式结合起来 - 的服务模式,这主要是联邦成员的大型机构HPC资源,并在桌面模式,它利用电脑的电源自愿一般公众。最近,我们制定了“科学门户网站”风格的web界面,使得它比以往任何时候都更容易为系统发育分析使用GARLI,使用最大似然法来推断生物的进化历史基因序列数据的基础上流行的程序来完成。本文描述了调度数千GARLI工作具有不同要求的异构网格资源,其中包括运行BOINC软件志愿者的电脑我们的做法。该系统的一个关键组成部分提供了一种使用机器学习与随机森林先验GARLI运行时估计。

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