A study of dynamic optimization of data acquisition system using GRID technology

利用GRID技术的数据采集系统动态优化研究

基本信息

批准号：
15540295
负责人：
ITOH Ryosuke
金额：
$ 2.37万
依托单位：
High Energy Accelerator Research Organization (2004)The High Energy Accelerator Research Organization (2003)
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15540295/
关键词：
High energy physics Data acquisition system GRID データー収集システム Grid 最適化

项目摘要

In a conventional data acquisition system, the function and data flow of event builder and trigger processor are fixed, and there are possibilities of wasting resouces or performance bottleneck depending on the accelerator condition. The purpose of this study is to optimize the usage of the processors and the data flow dynamically by a real time monitoring of the processor load and the data flow rate. In the first year, the monitoring mechanism was developed using a test bench system consisting of 25 PC servers connected via a large GbE switch. The mechanism was realized utilizing Network Shared Memory(NSM) used for the Belle experiment and it was succeeded to make it work. The transfer speed between nodes was also measured using a GRID software called MICH-G2 and was confirmed to be more than 60MB/sec.In the second year, the development of the optimization mechanism of processor utilization and data flow was done. A dynamic change of processing function on a processor was realized by … More modularizing the processing software and replacing them using a dynamic link with the data acquisition framework. Together with a use of large ring buffers and socket connections implemented on each processing node, it was succeeded to change data flow path and/or processing function on a node without interrupting the data acquisition. As the last step, an algorithms to optimize system-wide performance was trying to be developed, however, we have not yet succeeded to develop the mechanism satisfying the real usage in the data acquisition system. A massive switch of the data flow path and processing software is observed to happen at some boundary during a gradual change in the data flow rate, resulting in a waste of resources. Sometimes a short stop of the data acquisition is observed during the switching. Therefore, we need to continue the effort to improve the optimization algorithm with some new technology like the neural-net.The mechanism developed for the monitoring of data flow and processor load was used for the real time reconstruction farm of the Belle experiment and it was reported at the international conference on Computing in High Energy Physics 04. Less

在传统的数据采集系统中，事件生成器和触发处理器的功能和数据流是固定的，并且根据加速器条件存在浪费资源或性能瓶颈的可能性。本研究的目的是优化处理器的使用。第一年，监控机制是使用由通过网络实现的大型 GbE 交换机连接的 25 台 PC 服务器组成的测试台系统开发的。 Belle实验中使用了共享内存（NSM），并且成功地使用了名为MICH-G2的GRID软件测量了节点之间的传输速度，并确认在第二年超过了60MB/秒。开发了处理器利用率和数据流的优化机制，通过将处理软件模块化并使用数据采集框架的动态链接来替换它们，从而实现了处理器上处理功能的动态变化。使用大型环形缓冲区和套接字连接在每个处理节点上实施，成功地在不中断数据采集的情况下改变节点上的数据流路径和/或处理功能。作为最后一步，我们正在尝试开发一种优化系统范围性能的算法。目前尚未成功开发出满足数据采集系统实际使用的机制，在数据流量逐渐变化的过程中，会在某些边界处观察到数据流路径和处理软件的大量切换，从而造成浪费。有时在切换期间会观察到数据采集的短暂停止。因此，我们需要继续努力利用神经网络等新技术来改进优化算法。为监控数据流和处理器负载而开发的机制被用于Belle实验的实时重建农场，并得到了很好的应用。在高能物理计算国际会议上的报告04. 少