即时数据分析与还原

Filip Leonarski
{"title":"即时数据分析与还原","authors":"Filip Leonarski","doi":"10.1080/08940886.2023.2245730","DOIUrl":null,"url":null,"abstract":"X-ray facilities are currently going through a wave of upgrades. In the synchrotron world, upgrading to the 4th generation machine is the goal for many facilities. MAX IV (Sweden), ESRF-EBS (France), and Sirius (Brazil) are the pioneers; APS (USA) just started its upgrade; HEPS (China) is under construction; and SLS 2.0 upgrade (Switzerland) will begin shortly. For X-ray free electron lasers, LCLS-II (USA) will be capable of producing 1 million pulses per second, a fourorder-of-magnitude improvement over LCLS in repetition rate. Beamlines will also receive enhancements together with accelerators to enable groundbreaking research. The difficulties posed by growing data volumes and the requirements for computational power, however, are shared by all of these upgrade programs. For instance, upgraded facilities could generate tens of petabytes of data annually, and kilohertz realtime data analysis is anticipated. In addition, the performance requirements of computing components like microprocessors, disks, and network interfaces are increasing more slowly than the IT infrastructure requirements of synchrotron facilities. It is unrealistic to believe that the anticipated increase in data creation can be accommodated by just waiting for the next chip generation. To cope with this pressing issue, X-ray facilities may have to make a difficult decision: either expand investment budget in IT infrastructure dramatically, or restrict experiment performance. Therefore, we believe innovative solutions are required to meet the challenge through altering community practice. The examples provided in this special edition of Synchrotron Radiation News illustrate how this is feasible. Nikitin et al. present a real-time processing solution for a 2-BM tomography beamline at the APS. Having instant feedback about the experiment’s progress allows the experiment team to collect only the necessary data. In addition, the software allows for focusing only on events of interest. The paper also gives insight into the algorithms and computing infrastructure essential for real-time operation, with part of the calculation accelerated on a GPU. Blanschke et al. present the advantages of using external high-performance computing facilities. The paper describes a fruitful collaboration between LCLS and the National Energy Research Scientific Computing Center (Berkeley, USA). Images collected at the Xray free electron laser are processed in realtime at the supercomputing center, providing quick feedback to the experiment team. By using external resources, the facility does not need to operate large clusters on-site, but can adjust the size and type of external computing resources based on the demand of particular experiments. Underwood et al. describe a lossy compression scheme for serial macromolecular crystallography for LCLS. The method is based on the observation that only a small fraction of pixels—those with and near Bragg spots—in a protein diffraction image contribute to solving a 3D structure. The authors of the paper show that the data quality will not degrade if the remaining background pixels are compressed with a lossy algorithm. By doing so, they can get even an order of magnitude better compression as compared to the current lossless approach. Finally, this issue includes a contribution by M. Burian et al. The article presents recent developments in streaming functionality from commercial detectors produced by DECTRIS. This option enables analysis and processing of X-ray images prior to saving them on disk. An important aspect of the functionality is including detector and beamline metadata with the streamed images. n","PeriodicalId":503466,"journal":{"name":"Synchrotron Radiation News","volume":"19 1","pages":"2 - 2"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On-the-Fly Data Analysis and Reduction\",\"authors\":\"Filip Leonarski\",\"doi\":\"10.1080/08940886.2023.2245730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"X-ray facilities are currently going through a wave of upgrades. In the synchrotron world, upgrading to the 4th generation machine is the goal for many facilities. MAX IV (Sweden), ESRF-EBS (France), and Sirius (Brazil) are the pioneers; APS (USA) just started its upgrade; HEPS (China) is under construction; and SLS 2.0 upgrade (Switzerland) will begin shortly. For X-ray free electron lasers, LCLS-II (USA) will be capable of producing 1 million pulses per second, a fourorder-of-magnitude improvement over LCLS in repetition rate. Beamlines will also receive enhancements together with accelerators to enable groundbreaking research. The difficulties posed by growing data volumes and the requirements for computational power, however, are shared by all of these upgrade programs. For instance, upgraded facilities could generate tens of petabytes of data annually, and kilohertz realtime data analysis is anticipated. In addition, the performance requirements of computing components like microprocessors, disks, and network interfaces are increasing more slowly than the IT infrastructure requirements of synchrotron facilities. It is unrealistic to believe that the anticipated increase in data creation can be accommodated by just waiting for the next chip generation. To cope with this pressing issue, X-ray facilities may have to make a difficult decision: either expand investment budget in IT infrastructure dramatically, or restrict experiment performance. Therefore, we believe innovative solutions are required to meet the challenge through altering community practice. The examples provided in this special edition of Synchrotron Radiation News illustrate how this is feasible. Nikitin et al. present a real-time processing solution for a 2-BM tomography beamline at the APS. Having instant feedback about the experiment’s progress allows the experiment team to collect only the necessary data. In addition, the software allows for focusing only on events of interest. The paper also gives insight into the algorithms and computing infrastructure essential for real-time operation, with part of the calculation accelerated on a GPU. Blanschke et al. present the advantages of using external high-performance computing facilities. The paper describes a fruitful collaboration between LCLS and the National Energy Research Scientific Computing Center (Berkeley, USA). Images collected at the Xray free electron laser are processed in realtime at the supercomputing center, providing quick feedback to the experiment team. By using external resources, the facility does not need to operate large clusters on-site, but can adjust the size and type of external computing resources based on the demand of particular experiments. Underwood et al. describe a lossy compression scheme for serial macromolecular crystallography for LCLS. The method is based on the observation that only a small fraction of pixels—those with and near Bragg spots—in a protein diffraction image contribute to solving a 3D structure. The authors of the paper show that the data quality will not degrade if the remaining background pixels are compressed with a lossy algorithm. By doing so, they can get even an order of magnitude better compression as compared to the current lossless approach. Finally, this issue includes a contribution by M. Burian et al. The article presents recent developments in streaming functionality from commercial detectors produced by DECTRIS. This option enables analysis and processing of X-ray images prior to saving them on disk. An important aspect of the functionality is including detector and beamline metadata with the streamed images. n\",\"PeriodicalId\":503466,\"journal\":{\"name\":\"Synchrotron Radiation News\",\"volume\":\"19 1\",\"pages\":\"2 - 2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Synchrotron Radiation News\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/08940886.2023.2245730\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Synchrotron Radiation News","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/08940886.2023.2245730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

X 射线设备目前正经历着升级换代的浪潮。在同步加速器领域,升级到第四代机器是许多设施的目标。MAX IV(瑞典)、ESRF-EBS(法国)和 Sirius(巴西)是先驱;APS(美国)刚刚开始升级;HEPS(中国)正在建设中;SLS 2.0 升级(瑞士)即将开始。在 X 射线自由电子激光器方面,LCLS-II(美国)将能够每秒产生 100 万个脉冲,在重复率方面比 LCLS 提高了四个数量级。光束线和加速器也将得到加强,以实现突破性研究。然而,数据量的增长和对计算能力的要求所带来的困难是所有这些升级计划所共同面临的。例如,升级后的设施每年可产生数十 PB 的数据,预计将进行千赫兹实时数据分析。此外,对微处理器、磁盘和网络接口等计算组件性能要求的增长速度比同步辐射设施对 IT 基础设施要求的增长速度要慢。如果认为仅仅等待下一代芯片的出现就能满足预期的数据创建增长需求,那是不现实的。为了应对这一紧迫问题,X 射线设施可能不得不做出艰难的决定:要么大幅增加 IT 基础设施的投资预算,要么限制实验性能。因此,我们认为需要创新的解决方案,通过改变社区实践来应对挑战。本期《同步辐射新闻》特刊提供的实例说明了这一点的可行性。Nikitin 等人介绍了 APS 的 2-BM 层析成像光束线的实时处理解决方案。有了实验进度的即时反馈,实验小组就可以只收集必要的数据。此外,该软件还允许只关注感兴趣的事件。论文还深入介绍了实时运行所必需的算法和计算基础设施,其中部分计算是通过 GPU 加速完成的。Blanschke 等人介绍了使用外部高性能计算设施的优势。论文介绍了 LCLS 与国家能源研究科学计算中心(美国伯克利)之间富有成效的合作。X 射线自由电子激光器采集的图像在超级计算中心进行实时处理,为实验团队提供快速反馈。通过使用外部资源,该设施无需在现场运行大型集群,而是可以根据特定实验的需求调整外部计算资源的规模和类型。Underwood 等人描述了一种用于 LCLS 串行大分子晶体学的有损压缩方案。该方法基于这样一个观察结果:在蛋白质衍射图像中,只有一小部分像素--有布拉格斑点的像素和靠近布拉格斑点的像素--有助于三维结构的求解。论文作者指出,如果使用有损算法压缩剩余的背景像素,数据质量不会下降。与目前的无损压缩方法相比,他们的压缩效果甚至可以提高一个数量级。最后,本期还收录了 M. Burian 等人撰写的文章。文章介绍了 DECTRIS 公司生产的商用探测器在流式功能方面的最新进展。该选项可在将 X 射线图像保存到磁盘之前对其进行分析和处理。该功能的一个重要方面是将探测器和光束线元数据与流式图像结合在一起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-the-Fly Data Analysis and Reduction
X-ray facilities are currently going through a wave of upgrades. In the synchrotron world, upgrading to the 4th generation machine is the goal for many facilities. MAX IV (Sweden), ESRF-EBS (France), and Sirius (Brazil) are the pioneers; APS (USA) just started its upgrade; HEPS (China) is under construction; and SLS 2.0 upgrade (Switzerland) will begin shortly. For X-ray free electron lasers, LCLS-II (USA) will be capable of producing 1 million pulses per second, a fourorder-of-magnitude improvement over LCLS in repetition rate. Beamlines will also receive enhancements together with accelerators to enable groundbreaking research. The difficulties posed by growing data volumes and the requirements for computational power, however, are shared by all of these upgrade programs. For instance, upgraded facilities could generate tens of petabytes of data annually, and kilohertz realtime data analysis is anticipated. In addition, the performance requirements of computing components like microprocessors, disks, and network interfaces are increasing more slowly than the IT infrastructure requirements of synchrotron facilities. It is unrealistic to believe that the anticipated increase in data creation can be accommodated by just waiting for the next chip generation. To cope with this pressing issue, X-ray facilities may have to make a difficult decision: either expand investment budget in IT infrastructure dramatically, or restrict experiment performance. Therefore, we believe innovative solutions are required to meet the challenge through altering community practice. The examples provided in this special edition of Synchrotron Radiation News illustrate how this is feasible. Nikitin et al. present a real-time processing solution for a 2-BM tomography beamline at the APS. Having instant feedback about the experiment’s progress allows the experiment team to collect only the necessary data. In addition, the software allows for focusing only on events of interest. The paper also gives insight into the algorithms and computing infrastructure essential for real-time operation, with part of the calculation accelerated on a GPU. Blanschke et al. present the advantages of using external high-performance computing facilities. The paper describes a fruitful collaboration between LCLS and the National Energy Research Scientific Computing Center (Berkeley, USA). Images collected at the Xray free electron laser are processed in realtime at the supercomputing center, providing quick feedback to the experiment team. By using external resources, the facility does not need to operate large clusters on-site, but can adjust the size and type of external computing resources based on the demand of particular experiments. Underwood et al. describe a lossy compression scheme for serial macromolecular crystallography for LCLS. The method is based on the observation that only a small fraction of pixels—those with and near Bragg spots—in a protein diffraction image contribute to solving a 3D structure. The authors of the paper show that the data quality will not degrade if the remaining background pixels are compressed with a lossy algorithm. By doing so, they can get even an order of magnitude better compression as compared to the current lossless approach. Finally, this issue includes a contribution by M. Burian et al. The article presents recent developments in streaming functionality from commercial detectors produced by DECTRIS. This option enables analysis and processing of X-ray images prior to saving them on disk. An important aspect of the functionality is including detector and beamline metadata with the streamed images. n
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信