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The condo of condos 公寓中的公寓
James B. Bottum, R. Marinshaw, Henry Neeman, James Pepin, J. V. Oehsen
University-located computational and data storage resources are increasingly being aggregated into shared university-level systems that are dubbed "condominium clusters." This session will describe the "Condo of Condos," a "consortium of the willing" that is working together to extend this condominium model both locally and across the consortium. By aggregating resources and expertise at the institutional level it will be possible to create distributed technical and support operations that provide faculty and students with methods to leverage a much larger and robust set of resources. Partnering with Internet2, the consortium will use the Innovation Platform to connect campuses and allow high performance interconnections through Science DMZs that can be built and broken down in ad-hoc ways using SDN. The ability to develop these network connections, coupled with the project's community building characteristics, will be a model for "team science" that can be extended and replicated nationally. By leveraging existing local and national computing resources (XSEDE and Open Science Grid), we will enable science and education deployments that are not possible today, making complex collaborations with computational needs routine. This project will be transformative for campus IT and will create a community of practitioners that shares resources, experience, and expertise to facilitate new knowledge and discovery.
位于大学的计算和数据存储资源越来越多地聚集到被称为“共管集群”的共享大学级系统中。这个环节将介绍“共管公寓”,一个“自愿的联盟”,它正在共同努力,在本地和整个联盟中扩展这种共管公寓模式。通过在机构层面上整合资源和专业知识,将有可能创建分布式技术和支持操作,为教师和学生提供利用更大、更强大的资源集的方法。与Internet2合作,该联盟将使用创新平台连接校园,并通过科学dmz实现高性能互连,这些dmz可以使用SDN以自组织方式构建和分解。发展这些网络联系的能力,加上项目的社区建设特点,将成为“团队科学”的一个模式,可以在全国推广和复制。通过利用现有的本地和国家计算资源(XSEDE和开放科学网格),我们将实现今天不可能实现的科学和教育部署,使具有计算需求的复杂协作成为常态。这个项目将为校园IT带来变革,并将创建一个从业者社区,分享资源、经验和专业知识,以促进新知识和发现。
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引用次数: 3
New atomic resolution insights into dynamic protein-carbohydrate interactions enabled by high-performance computing 新的原子分辨率洞察动态蛋白质-碳水化合物的相互作用,使高性能计算
Olgun Guvench
Protein-carbohydrate interactions are a critical component of cellular structure and function. However, the inherent flexibility of biological carbohydrate polymers and the microheterogeneity resulting from their non-template-based biosynthesis complicate their study using experimental methods. Therefore, simulation approaches, and all-atom explicit-solvent molecular dynamics (MD) simulations in particular, provide an enabling technology for advancing the understanding of protein-carbohydrate interactions at the atomic level of resolution. Here, we detail our recent MD studies on the CD44 receptor performed using the highly-parallel NAMD MD engine with the CHARMM all-atom force field on the Kraken supercomputer. With these technologies, simulation time lengths of hundreds of nanoseconds are routinely reached. Combining both regular unbiased MD and advanced MD methods that bias sampling to important degrees of freedom, new insights are obtained into the function of CD44, which is both a receptor for large carbohydrate molecules in the extracellular matrix and whose own function is modulated by covalent attachment of branched carbohydrates to make CD44 a glycoprotein. In particular, the simulations explain, for the first time, the molecular mechanism of the experimentally-observed order-to-disorder transition in CD44 that is known to enhance its carbohydrate binding affinity. Additionally, the simulations explain, again for the first time, the molecular mechanism through which particular monosaccharides in branched carbohydrates covalently attached to CD44 have been experimentally observed to block CD44 binding to extracellular matrix carbohydrates. These insights expand the understanding of how CD44 performs its biological functions, which include cell adhesion, migration, and vascular trafficking. Importantly, these new insights enabled by leading-edge simulation and computing technologies have not been accessible by existing experimental methods.
蛋白质-碳水化合物相互作用是细胞结构和功能的重要组成部分。然而,生物碳水化合物聚合物固有的灵活性和由其非模板生物合成引起的微异质性使实验方法的研究复杂化。因此,模拟方法,特别是全原子显式溶剂分子动力学(MD)模拟,为在原子水平上提高对蛋白质-碳水化合物相互作用的理解提供了一种使能技术。在这里,我们详细介绍了我们最近在Kraken超级计算机上使用高度并行的NAMD MD引擎和CHARMM全原子力场对CD44受体进行的MD研究。使用这些技术,通常可以达到数百纳秒的模拟时间长度。结合常规的无偏MD和先进的MD方法,将采样偏倚到重要的自由度,对CD44的功能有了新的认识,CD44既是细胞外基质中大碳水化合物分子的受体,其自身的功能是通过支链碳水化合物的共价附着来调节的,使CD44成为糖蛋白。特别是,模拟首次解释了CD44中实验观察到的有序到无序转变的分子机制,这种转变已知会增强其碳水化合物结合亲和力。此外,模拟还首次解释了在实验中观察到的与CD44共价连接的支链碳水化合物中的特定单糖阻断CD44与细胞外基质碳水化合物结合的分子机制。这些见解扩展了对CD44如何执行其生物学功能的理解,包括细胞粘附、迁移和血管运输。重要的是,这些由前沿模拟和计算技术实现的新见解是现有实验方法无法获得的。
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引用次数: 0
A high-level framework for parallelizing legacy applications for multiple platforms 为多个平台并行处理遗留应用程序的高级框架
R. Arora, Ejenio Capetillo, P. Bangalore, M. Mernik
The tremendous growth and diversification in the area of computer architectures has contributed towards an upsurge in the number of parallel programing paradigms, languages, and environments. However, it is often difficult for domain-experts to develop expertise in multiple programming paradigms and languages in order to write performance-oriented parallel applications. Several active research projects aim at reducing the burden on programmers by raising the level of abstraction of parallel programming. However, a majority of such research projects either entail manual invasive reengineering of existing code to insert new directives for parallelization or force conformance to specific interfaces. Some systems require that the programmers rewrite their entire application in a new parallel programing language or a domain-specific language. Moreover, only a few research projects are addressing the need of a single framework for generating parallel applications for multiple hardware platforms or doing hybrid programming. This paper presents a high-level framework for parallelizing existing serial applications for multiple target platforms. The framework, currently in its prototype stage, can semi-automatically generate parallel applications for systems with both distributed-memory architectures and shared-memory architectures through MPI, OpenMP, and hybrid programming. For all the test cases considered so far, the performance of the generated parallel applications is comparable to that of the manually written parallel versions of the applications. Our approach enhances the productivity of the end-users as they are not required to learn any low-level parallel programming, shortens the parallel application development cycle for multiple platforms, and preserves the existing version of serial applications.
计算机体系结构领域的巨大增长和多样化促成了并行编程范例、语言和环境数量的激增。然而,为了编写面向性能的并行应用程序,领域专家通常很难掌握多种编程范式和语言的专业知识。一些活跃的研究项目旨在通过提高并行编程的抽象水平来减轻程序员的负担。然而,大多数这样的研究项目要么需要手动侵入性地重新设计现有代码,以插入新的并行指令,要么强制遵守特定的接口。有些系统要求程序员用新的并行编程语言或特定于领域的语言重写整个应用程序。此外,只有少数研究项目正在解决为多个硬件平台生成并行应用程序或进行混合编程的单一框架的需求。本文提出了一个高级框架,用于并行化现有的多目标平台串行应用程序。该框架目前处于原型阶段,可以通过MPI、OpenMP和混合编程,半自动地为具有分布式内存架构和共享内存架构的系统生成并行应用程序。对于到目前为止考虑的所有测试用例,生成的并行应用程序的性能与手工编写的应用程序的并行版本的性能相当。我们的方法提高了终端用户的生产力,因为他们不需要学习任何低级并行编程,缩短了多平台并行应用程序的开发周期,并保留了串行应用程序的现有版本。
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引用次数: 5
Referee consensus: a platform technology for nonlinear optimization 裁判共识:一种非线性优化平台技术
D. Krieger, M. McNeil, Jinyin Zhang, W. Schneider, Xin Li, D. Okonkwo
Electrical current flow within populations of neurons is a fundamental constituent of brain function. The resulting fluctuating magnetic fields may be sampled noninvasively with an array of magnetic field detectors positioned outside the head. This is magnetoencephalography (MEG). Each source may be characterized by 5-6 parameters, the xyz location and the xyz direction. The magnetic field measurements are nonlinear in the location parameters; hence the source location is identifiable only via search of the brain volume. When there is one or a very few sources, this may be practical; solutions for the general problem have poor resolution and are readily defeated. Referee consensus is a novel cost function which enables identification of a source at one location at a time regardless of the number and location of other sources. This "independence" enables solution of the general problem and insures suitability to grid computing. The computation scales linearly with the number of nonlinear parameters. Since the method is not readily disrupted by noise or the presence of multiple unknown source, it is applicable to single trial data. MEG recordings were obtained from 26 volunteers while they performed a cognitive task The single trial recordings were processed on the Open Science Grid (≈300 CPU hours/sec of data) On average 500+ active sources were found throughout. Statistical analyses demonstrated 1-2 mm resolving power and high confidence findings (p < 0.0001) when testing for task specific information in the extracted virtual recordings. Referee consensus is applicable to a variety of systems in addition to MEG, e.g. the connectivity problem, the blurred image, both passive and active SONAR, and seismic tomography. Applicability requires (1) that the measurements be linear in at least one of the source parameters and (2) that a sequence of measurements in time be obtained.
神经元群内的电流流动是大脑功能的基本组成部分。所产生的波动磁场可以用位于头部外部的磁场探测器阵列进行非侵入性采样。这是脑磁图(MEG)。每个源可以用5-6个参数,xyz位置和xyz方向来表征。磁场测量在位置参数上是非线性的;因此,只有通过搜索脑容量才能确定源位置。当有一个或很少的来源时,这可能是实用的;一般问题的解决方案的解决性很差,而且很容易失败。裁判共识是一种新颖的成本函数,它允许在一个地点同时识别一个来源,而不管其他来源的数量和位置。这种“独立性”能够解决一般问题,并确保网格计算的适用性。计算量与非线性参数的数量成线性关系。由于该方法不易受到噪声或多个未知源的干扰,因此适用于单次试验数据。在26名志愿者执行认知任务时获得脑磁图记录,单次试验记录在开放科学网格(≈300 CPU小时/秒的数据)上进行处理,平均发现500多个活动源。统计分析表明,在提取的虚拟录音中测试任务特定信息时,分辨率为1- 2mm,置信度高(p < 0.0001)。除了MEG之外,裁判共识还适用于各种系统,例如连通性问题、图像模糊、被动和主动声纳以及地震层析成像。适用性要求:(1)测量值在至少一个源参数上是线性的;(2)在时间上获得一系列测量值。
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引用次数: 6
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery 极端科学与工程发现环境:探索之门会议论文集
Nancy Wilkins-Diehr
On behalf of the organizing committee for XSEDE13, welcome to this annual gathering of an extended community of individuals interested in advancing research cyberinfrastructure and integrated digital services for the benefit of science and society. Last year's conference, with 600 attendees (one-quarter students) from 41 states, set a high bar---it was dynamic and exciting. This year we are building on that momentum while focusing on new activities in high-end analysis, including the impact of science gateways and the relevance of computation and high-end analysis in the biosciences.
我谨代表XSEDE13的组委会,欢迎大家参加这个一年一度的聚会,这是一个由对推进研究网络基础设施和综合数字服务以造福科学和社会感兴趣的个人组成的扩展社区。去年的会议有来自41个州的600名与会者(其中四分之一是学生),会议设置了一个很高的标准——充满活力,令人兴奋。今年,我们将以这一势头为基础,重点关注高端分析领域的新活动,包括科学门户的影响以及生物科学中计算和高端分析的相关性。
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引用次数: 23
Supercomputer assisted generation of machine learning agents for the calibration of building energy models 超级计算机辅助生成机器学习代理,用于校准建筑能源模型
J. Sanyal, J. New, Richard E. Edwards
Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the "Autotune" research which employs machine learning algorithms to generate agents for the different kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.
建筑能源建模(BEM)是一种为设计和改造目的对建筑物的能源使用进行建模的方法。EnergyPlus是能源部的旗舰软件,可以为不同类型的建筑执行BEM。EnergyPlus的输入通常可以扩展到几千个参数,这些参数必须由专家手动校准才能实现真实的能量建模。这使得它具有挑战性和昂贵,从而使建筑能源建模在较小的项目中不可行。在本文中,我们描述了“Autotune”研究,该研究采用机器学习算法为美国建筑库存中的不同类型的标准参考建筑生成代理。参数化空间和各种建筑位置和类型使这成为一个具有挑战性的计算问题,需要使用超级计算机。数百万EnergyPlus模拟在超级计算机上运行,这些模拟随后被用于训练机器学习算法以生成代理。这些代理一旦创建,就可以在很短的时间内运行,从而允许经济有效地校准建筑模型。
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引用次数: 15
Improvements of the UltraScan scientific gateway to enable computational jobs on large-scale and open-standards based cyberinfrastructures UltraScan科学网关的改进,使计算工作能够在大规模和基于开放标准的网络基础设施上进行
M. S. Memon, N. Attig, Gary Gorbet, Lahiru Gunathilake, M. Riedel, T. Lippert, S. Marru, A. Grimshaw, F. Janetzko, B. Demeler, Raminderjeet Singh
The UltraScan data analysis application is a software package that is able to take advantage of computational resources in order to support the interpretation of analytical ultracentrifugation (AUC) experiments. Since 2006, the UltraScan scientific gateway has been used with ordinary Web browsers in TeraGrid by scientists studying the solution properties of biological and synthetic molecules. Unlike other applications, UltraScan is implemented on a gateway architecture and leverages the power of supercomputing to extract very high resolution information from the experimental data. In this contribution, we will focus on several improvements of the UltraScan scientific gateway that enable a standardized job submission and management to computational resources while retaining its lightweight design in order to not disturb the established workflows of its end-users. This paper further presents a walkthrough of the architectural design including one real installation deployment of UltraScan in Europe. The aim is to provide evidence for the added value of open standards and resulting interoperability enabling not only UltraScan application submissions to resources offered in the US cyber infrastructure Extreme Science and Engineering Discovery Environment (XSEDE), but also submissions to similar infrastructures in Europe and around the world. The use of the Apache Airavata framework for scientific gateways within our approach bears the potential to have an impact on several other scientific gateways too.
UltraScan数据分析应用程序是一个软件包,能够利用计算资源来支持分析性超离心(AUC)实验的解释。自2006年以来,UltraScan科学网关已与TeraGrid中的普通Web浏览器一起使用,供科学家研究生物和合成分子的溶液特性。与其他应用程序不同,UltraScan是在网关架构上实现的,并利用超级计算的能力从实验数据中提取非常高分辨率的信息。在本文中,我们将重点介绍UltraScan科学网关的几项改进,这些改进可以实现标准化的作业提交和计算资源管理,同时保留其轻量级设计,以免干扰最终用户的既定工作流程。本文进一步介绍了建筑设计的演练,包括UltraScan在欧洲的一次实际安装部署。其目的是为开放标准的附加价值和由此产生的互操作性提供证据,使UltraScan应用程序不仅可以提交到美国网络基础设施极端科学与工程发现环境(XSEDE)中提供的资源,还可以提交到欧洲和世界各地的类似基础设施中。在我们的方法中使用Apache Airavata框架作为科学网关,也有可能对其他几个科学网关产生影响。
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引用次数: 6
NCAR storage accounting and analysis possibilities NCAR存储核算和分析的可能性
David L. Hart, P. Gillman, Erich Thanhardt
While most HPC operators diligently track computing usage and utilization on a job-by-job basis, far fewer sites have implemented mechanisms for tracking and accounting for usage of their storage systems. As we enter an era of larger and larger data sets, the need to monitor, track, and analyze users' consumption of storage resources becomes more critical for planning, operating, and managing petascale storage environments. NCAR's Computational and Information Systems Laboratory has long had a formal accounting mechanism in place for its archival storage system and has recently extended a similar mechanism to its recently acquired 11-PB disk resource. The collected data helps both NCAR's users and administrators by supporting reports and analyses to guide the use and management of these vital resources.
虽然大多数HPC运营商都在逐个作业地跟踪计算的使用情况和利用率,但很少有站点实现了跟踪和计算存储系统使用情况的机制。随着我们进入一个数据集越来越大的时代,监控、跟踪和分析用户对存储资源的消耗对于规划、操作和管理千万亿级存储环境变得更加重要。NCAR的计算和信息系统实验室长期以来一直为其档案存储系统建立了正式的会计机制,并且最近将类似的机制扩展到其最近获得的11-PB磁盘资源。收集的数据通过支持报告和分析来指导这些重要资源的使用和管理,从而帮助NCAR的用户和管理员。
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引用次数: 4
Alleviating the scaling problem of cosmological hydrodynamic simulations with HECA 用HECA缓解宇宙流体力学模拟的标度问题
L. Oser, M. Gajbe, K. Nagamine, G. Bryan, J. Ostriker, R. Cen
We (the CAGE team) present a possible solution to the scaling problem that is inherent to cosmological simulations of structure formation. With an increasing number of computational nodes the resources that are lost due to communication overhead and load balancing is growing and thereby limiting the problem sizes and/or resolution level that can be computed in a reasonable amount of time. To alleviate this problem, we propose the HECA (Hierarchical Ensemble Computing Algorithm). Instead of running a full-box cosmological simulation, we perform multiple (only limited by the number of processing nodes) zoom-in simulations concurrently that are independent of each other and thereby providing a perfect scaling to large core counts. In these simulations we can reach a much higher resolution level that would be unfeasible to achieve in a full-box simulation. We show that with the help of HECA we are able to efficiently use the ressources provided by modern petascale supercomputers to simulate a statistically significant sample of galaxies.
我们(CAGE团队)提出了一种可能的解决方案,以解决结构形成的宇宙学模拟所固有的缩放问题。随着计算节点数量的增加,由于通信开销和负载平衡而丢失的资源也在增加,从而限制了在合理时间内可以计算的问题大小和/或解决级别。为了解决这个问题,我们提出了层次集成计算算法(HECA)。我们没有运行一个完整的宇宙模拟,而是同时执行多个相互独立的放大模拟(仅受处理节点数量的限制),从而提供了一个完美的扩展到大型核心计数。在这些模拟中,我们可以达到更高的分辨率水平,这在全箱模拟中是无法实现的。我们表明,在HECA的帮助下,我们能够有效地利用现代千万亿次超级计算机提供的资源来模拟具有统计意义的星系样本。
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引用次数: 0
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Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
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