Making campus bridging work for researchers: a case study with mlRho

A. Thota, B. Haubold, Scott Michael, T. Doak, Sen Xu, R. Henschel
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引用次数: 1

Abstract

An increasing number of biologists' computational demands have outgrown the capacity of desktop workstations and they are turning to supercomputers to run their simulations and calculations. Many of today's computational problems, however, require larger resource commitments than even individual universities can provide. XSEDE is one of the first places researchers turn to when they outgrow their campus resources. XSEDE machines are far larger (by at least an order of magnitude) than what most universities offer. Transitioning from a campus resource to an XSEDE resource is seldom a trivial task. XSEDE has taken many steps to make this easier, including the Campus Bridging initiative, the Campus Champions program, the Extended Collaborative Support Service (ECSS) [1] program, and through education and outreach. In this paper, our team of biologists and application support analysts (including a Campus Champion) dissect a computationally intensive biology project and share the insights we gain to help strengthen the programs mentioned above. We worked on a project to calculate population mutation and recombination rates of tens of genome profiles using mlRho [2], a serial, open-source, genome analysis code. For the initial investigation, we estimated that we would need 6.3 million service units (SUs) on the Ranger system. Three of the most important places where the biologists needed help in transitioning to XSEDE were (i) preparing the proposal for 6.3 million SUs on XSEDE, (ii) scaling up the existing workflow to hundreds of cores and (iii) performance optimization. The Campus Bridging initiative makes all of these tasks easier by providing tools and a consistent software stack across centers. Ideally, Campus Champions are able to provide support on (i), (ii) and (iii), while ECSS staff can assist with (ii) and (iii). But (i), (ii) and (iii) are often not part of a Campus Champion's regular job description. To someone writing an XSEDE proposal for the first time, a link to the guidelines and a few pointers may not always be enough for a successful application. In this paper we describe a new role for a campus bridging expert to play in closing the gaps between existing programs and present mlRho as a case study.
为研究人员提供校园桥梁:以mlRho为例
越来越多的生物学家的计算需求已经超出了台式工作站的能力,他们转向超级计算机来运行他们的模拟和计算。然而,今天的许多计算问题需要更多的资源投入,甚至单个大学都无法提供。当研究人员的校园资源不足时,XSEDE是他们最先求助的地方之一。XSEDE机器比大多数大学提供的机器要大得多(至少大一个数量级)。从校园资源到XSEDE资源的转换很少是一项简单的任务。XSEDE已经采取了许多措施,包括校园桥接计划、校园冠军计划、扩展协作支持服务(ECSS)[1]计划,以及通过教育和推广,使这一切变得更容易。在本文中,我们的生物学家和应用支持分析师团队(包括一名校园冠军)剖析了一个计算密集型生物学项目,并分享了我们获得的见解,以帮助加强上述项目。我们利用mlRho[2](一个系列的、开源的基因组分析代码)进行了一个项目,计算了数十个基因组谱的群体突变和重组率。对于最初的调查,我们估计Ranger系统需要630万个服务单元(su)。在过渡到XSEDE的过程中,生物学家需要帮助的三个最重要的地方是:(i)准备XSEDE上630万个su的提案,(ii)将现有工作流扩展到数百个内核,(iii)性能优化。校园桥接计划通过跨中心提供工具和一致的软件堆栈,使所有这些任务变得更加容易。理想情况下,校园冠军能够在(i)、(ii)和(iii)方面提供支持,而ECSS的工作人员可以在(ii)和(iii)方面提供帮助。但(i)、(ii)和(iii)通常不是校园冠军的常规工作描述的一部分。对于第一次编写XSEDE提案的人来说,指南的链接和一些指针可能并不总是足以使应用程序成功。在本文中,我们描述了校园桥梁专家在缩小现有项目之间差距方面发挥的新作用,并将mlRho作为案例研究。
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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