Collaborative Research: SI2-SSI: Adding Volunteer Computing to the Research Cyberinfrastructure

消费类设备——台式机和笔记本电脑、平板电脑、智能手机——的计算能力总和远远超过了机构计算资源。“志愿计算”使用这些由其所有者自愿提供的消费设备来进行科学计算。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。它是由加州大学伯克利分校在国家科学基金会的支持下于2002年开始开发的。到目前为止，BOINC一直是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。在许多科学领域，大约有40个这样的项目：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世界社区网格（多种应用）。这些项目总共有大约40万名活跃的志愿者和12千万亿次的计算吞吐量。这种模式虽然在某种程度上是成功的，但已经达到了极限。项目和志愿者的数量停滞不前。志愿者计算提供了大量的计算能力，但只提供给少数研究项目。对其他科学家来说，有两个主要障碍。首先，创建BOINC项目有很大的开销：学习新技术、创建公共网站、进行宣传等等。第二，志愿计算具有风险和不确定性；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，并通过用一种新的“中央代理”模式取代竞争项目模式，使所有从事高通量计算的科学家都可以使用志愿计算。新模式有两个相关部分：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透明地卸载到志愿者计算机上。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的计算，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，而不是特定的项目。例如，参与者可能会报名为癌症研究捐款。作为该项目的一部分，将开发一个中央代理，它将动态地将其计算资源分配给进行这类研究的项目。该项目通过鼓励“志愿计算”和让公民参与研究本身的进行，动员公众对科学研究的支持和兴趣。它同时推进了NSF在扩大公民参与的同时推进科学的使命。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。该决策可能涉及作业的估计运行时、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，以及作业提交者的身份。2)作业格式转换：将作业描述（输入/输出文件规范，资源和时间要求）映射到它们的BOINC对等物。3)应用打包：调整现有的应用程序（如nanoHub的仿真工具和TACC的Autodock）在BOINC下运行。我们将使用BOINC的虚拟机设施，它将应用程序打包为虚拟机映像（VirtualBox或Docker）和要在虚拟机中运行的程序。这允许现有的Linux应用程序在Windows和Mac等消费者桌面平台上运行，并提供强大的安全沙箱和有效的独立于应用程序的检查点/重启机制。4)文件处理：在现有存储系统（通常从外部防火墙无法访问）到internet可见的服务器之间移动输入和输出文件。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)作业监控和控制：调整现有的基于web或命令行的工具，用于监控批次作业的进度，以及用于终止作业，以与BOINC一起工作。这将使用BOINC提供的现有Web rpc来实现这些目的。该项目将根据需要设计和实现新软件，测试其正确性、性能和可伸缩性，并将其部署到生产环境中，从而执行这些任务。该项目的第二部分——一个基于志愿者的科学偏好分配计算能力的代理系统——将被设计和原型化。这涉及到几个子任务：1)设计志愿者偏好模式，包括科学领域和子领域、项目国籍和机构、具体项目和申请、包括/排除等。2)设计一个模式，为工作流分配属性（例如，他们的区域，子区域，机构等），并为工作流分配配额或优先级。3)设计存储上述信息的关系数据库。4)在尊重志愿者偏好并优化配额、公平和吞吐量标准的情况下，设计和实施将志愿者资源分配给工作流的政策。这将作为一个BOINC“客户经理”来实现，这样志愿者就可以看到一个单一的界面，而不是许多单独的项目和网站。

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.