ITR: Distributed Analysis of Large Distributed Datasets with Java (BlueOx)

大型强子对撞机（LHC）在欧洲核子研究中心，瑞士的高能物理实验的数据存储和分析的规模，提供了新的挑战，有必要研究到新的概念的CPU利用率。产生的数据量太大，无法存储在任何一所大学。相反，数据将被存档在一个中央位置。该项目将开发技术和软件包，使远程地点的研究人员能够有效地对这些数据进行分布式分析。该提案将支持调查如何将用户对特定分析的请求和一些代码发送到存储数据的位置并在那里运行代码。然后，系统将收集和汇编结果，并将其呈现给用户。该框架将是BlueOx系统，Java将是BlueOx框架的实现语言，以利用其跨平台兼容性，该框架面临的最重要挑战是可扩展性。该项目计划通过在中等规模的计算集群上使用模拟数据的大型虚拟数据集对其进行测试来研究和提高可扩展性。目的是保持通用性，使其对许多大型科学项目有用。

The scale of data storage and analysis for the high energy physics experiments at the Large Hadron Collider (LHC) at CERN, Switzerland, provides new challenges and necessitates research into new concepts of CPU utilization. The quantity of data produced is too large to store at any single university. Rather, the data will be archived in a central location. This project will develop techniques and software packages to enable the efficient distributed analysis of these data by researchers at remote sites. This proposal would support the investigation into how to send a user's request for a particular analysis and some code to the locations where the data are stored and run the code there. The system would then collect and assemble the results and present them to the user. The framework would be the BlueOx system and Java will be the implementation language for the BlueOx framework so as to take advantage of its cross-platform compatibility.The most important challenge facing the framework is that of scalability. This project plans to study and improve the scalability by testing it with large dummy datasets of simulated data on a moderate-sized computing cluster. The aim is to keep the generality that can make it useful to many large scientific projects.