Collaborative Research: Any Data, Anytime, Anywhere

协作研究：任何数据、任何时间、任何地点

• 批准号: 1104549
• 负责人: Frank Wuerthwein
• 金额: $ 81.44万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1104549&HistoricalAwards=false
• 关键词: Collaborative; Research; Any; Data; Anytime

The Grid computing model connects computers that are scattered over a wide geographic area, allowing their computing power to be shared. Just as the World Wide Web enables access to information, computer grids enable access to distributed computing resources. These resources include detectors, computer cycles, computer storage, visualization tools, and more. Thus, grids can combine the resources of thousands of different computers that are not fully utilized, and assemble these to create a massively powerful resource, and, with GRID software, this resource can be accessible from a personal computer. For scientists in international collaborations, grid computing provides the power that can enable effective collaborations whose members are widely dispersed geographically. Grids also can enable simulations that might take weeks on a single PC to run in hours on a grid. Further, the development of computing grids also develops new communities. Grids therefore encourage and require people from different countries and cultures to work together to solve problems.Grid computing works because people participating in grids opt to share their computer power with others. This opens many questions, both social and technical. Who should be allowed to use each grid? Whose job should get priority in the queue to use grid power? What is the best way to protect user security? How will users pay for grid usage? Answering these questions requires all-new technical solutions, each of which must evolve as other grid and information technologies develop. Since grids involve countries and regions all over the world, these solutions must also suit different technical requirements, limitations and usage patterns.The Large Hadron Collider (LHC), the accelerator facility discussed in this proposal, is a particle accelerator constructed as a collaboration between more than 50 countries. The world's largest machine, it accelerates particles to nearly the speed of light and then steers these particles into 600 million collisions every second. Data from these collisions is expected to change our basic understanding of antimatter, dark energy and more. The LHC will produce 15 million gigabytes of data a year: the storage capacity of around 20,000,000 CDs. Thousands of physicists all over the world want timely access to this data.The LHC Computing Grid (LCG) combines the computing resources of more than 140 computing centers aiming to harness the power of 100,000 computers to process, analyze and store data produced from the LHC, making it equally available to all partners, regardless of their physical location. Through this proposal, a new LCG computing model for the CMS experiment at the LHC will enable dynamic access to existing world-wide data caches and will provide the capabilities for applications on any laptop, server, or cluster, to access data seamlessly from wherever it is stored. Data access will no longer require the operation of large scale storage infrastructures local to the participating procesors.. This model will give the distributed physics groups automated access to "Any Data" at "Anytime" from "Anywhere", decreasing data access costs, and reducing application failure. When pre-staging of voluminous datasets into such local storage is not plausible - due to either a lack of local hardware capability or instantaneous demand - it will be replaced with on-demand access of only those data objects the analysis actually requires from any remote site where the data are available. This significantly reduces the overall I/O and storage space requirements outside the CMS computer systems. The total cost of ownership of computer centers at universities throughout the US is thus significantly reduced, as the dominant human as well as hardware costs related to provisioning and operating a storage infrastructure disappear. The project will enable smaller scale university clusters and physicists' desktop computers access to all types of CMS data and thus improve the scientific output of CMS scientists nationwide.Further, this proposed infrastructure could be used for data-driven research in all fields, ranging from other natural sciences to social sciences and the humanities.

网格计算模型将分散在广阔地理区域的计算机连接起来，允许共享它们的计算能力。正如万维网使人们能够访问信息一样，计算机网格使人们能够访问分布式计算资源。这些资源包括探测器、计算机周期、计算机存储、可视化工具等。因此，网格可以联合收割机将数千台未充分利用的不同计算机的资源组合起来，并将这些资源组合成一个强大的资源，而且，使用网格软件，可以从个人计算机访问这些资源。对于国际合作的科学家来说，网格计算提供了一种力量，可以实现有效的合作，其成员在地理上分布广泛。网格还可以使在单个PC上可能需要数周的模拟在网格上运行数小时。此外，计算网格的发展也发展了新的社区。因此，网格鼓励并要求来自不同国家和文化的人们一起工作来解决问题。网格计算之所以有效，是因为参与网格的人们选择与他人共享他们的计算机能力。这引发了许多社会和技术问题。谁应该被允许使用每个网格？谁的工作应该在使用电网电力的队列中获得优先权？保护用户安全的最佳方法是什么？用户将如何为电网使用付费？解决这些问题需要全新的技术解决方案，每一种解决方案都必须随着其他网格和信息技术的发展而发展。由于电网涉及世界各地的国家和地区，这些解决方案也必须适应不同的技术要求、限制和使用模式。大型强子对撞机（LHC）是50多个国家合作建造的粒子加速器，也是本提案中讨论的加速器设施。这是世界上最大的机器，它将粒子加速到接近光速，然后每秒将这些粒子引导到6亿次碰撞。来自这些碰撞的数据有望改变我们对反物质、暗能量等的基本理解。大型强子对撞机每年将产生1500万千兆字节的数据：大约2000万张CD的存储容量。LHC计算网格（LCG）结合了140多个计算中心的计算资源，旨在利用10万台计算机的能力来处理、分析和存储LHC产生的数据，使所有合作伙伴都能平等地获得这些数据，而无论他们的物理位置如何。通过这一提议，LHC CMS实验的新LCG计算模型将能够动态访问现有的全球数据缓存，并为任何笔记本电脑，服务器或集群上的应用程序提供从存储的任何地方无缝访问数据的能力。 数据访问将不再需要参与处理器本地的大规模存储基础架构的操作。该模型将使分布式物理组能够在“任何时间”从“任何地方”自动访问“任何数据”，降低数据访问成本，并减少应用程序故障。当由于缺乏本地硬件能力或瞬时需求而无法将大量数据集预暂存到这种本地存储中时，将由仅从数据可用的任何远程站点按需访问分析实际需要的那些数据对象来取代。这大大减少了CMS计算机系统外部的总体I/O和存储空间需求。因此，美国各地大学计算机中心的总拥有成本显著降低，因为与配置和操作存储基础设施相关的主要人力和硬件成本消失了。该项目将使规模较小的大学集群和物理学家的台式计算机能够访问所有类型的CMS数据，从而提高全国CMS科学家的科学产出。此外，该拟议的基础设施可用于所有领域的数据驱动研究，从其他自然科学到社会科学和人文科学。