Collaborative Research: Si2-SSI: Adding Volunteer Computing to the Research Cyberinfrastructure

协作研究:Si2-SSI:将志愿计算添加到研究网络基础设施中

基本信息

  • 批准号:
    1550350
  • 负责人:
  • 金额:
    $ 12.04万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-08-01 至 2017-07-31
  • 项目状态:
    已结题

项目摘要

The aggregate computing power of consumer devices - desktop and laptop computers, tablets, smartphones - far exceeds that of institutional computing resources. "Volunteer computing" uses these consumer devices, volunteered by their owners, to do scientific computing. In addition to providing additional, much-needed computational resources to scientists, volunteer computing publicizes scientific research and engages citizens in science. BOINC is the primary software system for volunteer computing. It was developed at UC Berkeley with NSF support starting in 2002. Until now, BOINC has been based on a model of independent competing projects. Scientists set up their own BOINC servers, port their applications to run on BOINC, and publicize their projects to attract volunteers. There are about 40 such projects, in many areas of science: examples include Einstein@home, CERN, and SETI@home (astrophysics), Rosetta@home and GPUGrid.net (biomedicine), Climateprediction.net (climate study), and IBM World Community Grid (multiple applications). Together these projects have about 400,000 active volunteers and 12 PetaFLOPS of computing throughput. This model, while successful to an extent, has reached a limit. The number of projects and volunteers has stagnated. Volunteer computing is supplying lots of computing power, but only to a few research projects. For other scientists, there are two major barriers. First, creating a BOINC project has significant overhead: learning a new technology, creating a public web site, generating publicity, and so on. Second, volunteer computing is risky and uncertain; there is no guarantee that a new project will attract volunteers. This project aims to break this barrier, and to make volunteer computing available to all scientists doing high-throughput computing, by replacing the competing-projects model with a new "central broker" model. The new model has two related parts: 1) the integration of BOINC with existing high-throughput computing facilities such as supercomputing centers and science portals. Jobs currently run on cluster nodes will be transparently offloaded to volunteer computers. Scientists using these facilities will see faster turnaround times; they'll benefit from volunteer computing without even knowing it's there. 2) The project will change the volunteer interface so that participants sign up for scientific areas and goals rather then for particular projects. For example, a participant might sign up to contribute to cancer research. A central broker, to be developed as part of this project, would dynamically assign their computing resources to projects doing that type of research. This project mobilizes public support for and interest in scientific research by encouraging "volunteer computing" and engaging citizens in the conduct of the research itself. It simultaneously advances NSF's mission to advance science while broadening citizen engagement.The first year of this project will prototype each of these parts, and will integrate BOINC with TACC and nanoHub. Integrating BOINC with existing HTC systems involves several subtasks: 1) Job routing: modifying existing job processing systems used by TACC and nanoHub (Launcher and Rappture respectively) to decide when a group of jobs should be offloaded to BOINC. This decision might involve the estimated runtime of the jobs, input and output file sizes, data sensitivity, the deadline or priority of the jobs, and the identity of the job submitter. 2) Job format conversion: mapping job descriptions (input/output file specifications, resource and timing requirements) to their BOINC equivalents. 3) Application packaging: adapting existing applications (such as nanoHub's simulation tools and TACC's Autodock) to run under BOINC. We will use BOINC's virtual machine facility, which packages an application as a virtual machine image (VirtualBox or Docker) and a program to be run within the VM. This allows existing Linux applications to run on consumer desktop platforms such as Windows and Mac, as well as providing a strong security sandbox and an efficient application-independent checkpoint/restart mechanism. 4) File handling: moving input and output files between existing storage systems (typically inaccessible from outside firewalls) to Internet-visible servers. This will use existing BOINC components that manage files based on hashes to eliminate duplicate transfer and storage of files. 5) Job monitoring and control: adapting existing web- or command-line based tools for monitoring the progress of batches of jobs, and for aborting jobs, to work with BOINC. This will use existing Web RPCs provided by BOINC for these purposes. This project will carry out these tasks by designing and implementing new software as needed, testing for correctness, performance, and scalability, and deploying it in a production environment. The second part of the project - a brokering system for allocating computing power based on volunteer scientific preferences - will be designed and prototyped. This involves several subtasks: 1) Designing a schema for volunteer preferences, including scientific areas and sub-areas, project nationality and institutions, specific projects and applications, inclusions/exclusions, and so on. 2) Designing a schema for assigning attributes to job streams (e.g. their area, sub-area, institution, etc.), and for assigning quotas or priorities to job streams. 3) Designing a relational database for storing the above information. 4) Designing and implementing policies for assigning volunteer resources to job streams in a way that respects volunteer preferences and optimizes quota, fairness, and throughput criteria. This will be implemented as a BOINC "account manager" so that volunteers see a single interface rather than lots of separate projects and web sites.
消费类设备(台式机和笔记本电脑、平板电脑、智能手机)的总计算能力远远超过机构计算资源。 “志愿者计算”使用这些消费者设备,由他们的主人自愿,做科学计算。除了为科学家提供额外的、急需的计算资源外,志愿计算还宣传科学研究,并吸引公民参与科学。BOINC是志愿者计算的主要软件系统。 它是在加州大学伯克利分校开发的,从2002年开始得到NSF的支持。到目前为止,BOINC一直基于独立竞争项目的模式。 科学家们建立了自己的BOINC服务器,将他们的应用程序移植到BOINC上运行,并宣传他们的项目以吸引志愿者。 大约有40个这样的项目,在许多科学领域:例子包括Einstein@home,CERN和SETI@home(天体物理学),Rosetta@home和GPUGrid.net(生物医学),Climateprediction.net(气候研究)和IBM World Community Grid(多种应用程序)。 这些项目总共有大约40万名活跃的志愿者和12 PetaFLOPS的计算吞吐量。这种模式虽然在一定程度上是成功的,但也达到了极限。 项目和志愿者的数量停滞不前。 志愿者计算正在提供大量的计算能力,但只限于少数研究项目。 对于其他科学家来说,有两个主要的障碍。 首先,创建一个BOINC项目有很大的开销:学习一项新技术,创建一个公共网站,产生宣传,等等;其次,志愿者计算是有风险和不确定性的;不能保证一个新项目会吸引志愿者。该项目旨在打破这一障碍,并使志愿者计算提供给所有科学家做高吞吐量计算,取代竞争项目模式与新的“中央代理”模式。新模型有两个相关部分:1)BOINC与现有的高吞吐量计算设施(如超级计算中心和科学门户)的集成。当前在集群节点上运行的作业将被透明地卸载到志愿计算机。使用这些设施的科学家将看到更快的周转时间;他们将受益于志愿者计算,甚至不知道它的存在。2)该项目将改变志愿者界面,以便参与者注册科学领域和目标,而不是特定项目。例如,参与者可能会报名为癌症研究做出贡献。作为该项目的一部分开发的中央代理将动态地将其计算资源分配给进行该类型研究的项目。该项目通过鼓励“志愿计算”和让公民参与研究本身的开展,调动公众对科学研究的支持和兴趣。它同时推进了NSF的使命,即在扩大公民参与的同时推进科学。该项目的第一年将对这些部分进行原型设计,并将BOINC与TACC和nanoHub集成在一起。将BOINC与现有的HTC系统集成涉及几个子任务:1)作业路由:修改TACC和nanoHub(分别为Launcher和Rappture)使用的现有作业处理系统,以决定何时将一组作业卸载到BOINC。这个决定可能涉及作业的估计运行时间、输入和输出文件大小、数据敏感性、作业的截止日期或优先级以及作业子进程的标识。2)工作格式转换:将工作描述(输入/输出文件规范,资源和时间要求)映射到其BOINC等价物。3)应用程序打包:调整现有的应用程序(如nanoHub的模拟工具和TACC的Autodock),使其在BOINC下运行。我们将使用BOINC的虚拟机工具,它将应用程序打包为虚拟机映像(VirtualBox或Docker)和在VM中运行的程序。 这允许现有的Linux应用程序在消费者桌面平台(如Windows和Mac)上运行,并提供强大的安全沙箱和高效的独立于应用程序的检查点/重启机制。4)文件处理:将输入和输出文件在现有存储系统(通常无法从外部防火墙访问)之间移动到Internet可见的服务器。 这将使用现有的BOINC组件,这些组件基于哈希来管理文件,以消除文件的重复传输和存储。5)作业监控:调整现有的基于Web或命令行的工具,用于监视批量作业的进度,以及中止作业,以与BOINC一起工作。这将使用BOINC为这些目的提供的现有Web RPC。该项目将通过根据需要设计和实现新软件,测试正确性,性能和可扩展性,并将其部署到生产环境中来执行这些任务。该项目的第二部分-一个根据志愿者的科学偏好分配计算能力的中介系统-将被设计和制作原型。 这涉及几个子任务:1)设计志愿者偏好的模式,包括科学领域和子领域、项目国籍和机构、具体项目和应用、包括/排除等。2)设计分配工作流属性的模式(例如,其领域、子领域、机构等),以及为作业流分配配额或优先级。3)设计一个关系数据库来存储上述信息。4)设计和实施政策,以尊重志愿者偏好并优化配额、公平性和吞吐量标准的方式将志愿者资源分配给工作流。 这将被实现为一个BOINC的“帐户管理器”,这样志愿者就可以看到一个单一的界面,而不是许多独立的项目和网站。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Lucas Wilson其他文献

Design and analysis of special concentrically braced frames with A500 and annealed A500 square hollow section steel braces
使用 A500 及退火 A500 方形空心截面钢支撑的特殊中心支撑框架的设计与分析
  • DOI:
    10.1016/j.jcsr.2025.109668
  • 发表时间:
    2025-11-01
  • 期刊:
  • 影响因子:
    4.300
  • 作者:
    Ali Jafari;Lucas Wilson;Machel L. Morrison
  • 通讯作者:
    Machel L. Morrison

Lucas Wilson的其他文献

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