基于MT-SNiPER框架与PODIO的并行化事例数据管理系统
Parallelized Event Data Management System Based on MT-SNiPER Framework and PODIO
AI总结：
针对未来高能物理实验海量数据的离线处理挑战，研究人员基于MT-SNiPER框架与PODIO开发了并行化事例数据管理系统，实现多线程事例处理支持，并在OSCAR中完成了应用与性能评估。
摘要：
软件框架是众多高能物理（HEP）实验离线数据处理软件的骨架。事例数据管理包含事例数据模型（EDM）、瞬态事例存储以及数据输入/输出模块，实现了框架的核心功能，对整套离线软件的性能有重大影响。未来的高能物理实验将生成规模日益庞大的数据，给离线数据处理带来了挑战。为解决这一问题，研究人员基于SNiPER（非对撞机物理实验软件）通用软件框架，以及面向未来高能物理实验的通用EDM工具包PODIO，开发了一套支持高效并行化数据处理应用的通用事例数据管理系统。本文介绍了并行化事例数据管理（PEDM）系统的实现方案，包括其与MT-SNiPER和PODIO的集成，以及用于支持多线程事例处理的GlobalStore的实现细节。最后，本文展示了该数据管理系统在OSCAR（超级陶粲装置离线软件）中的应用情况与性能评估结果。
英文摘要：
Software framework serves as a skeleton for the offline data processing software for many high energy physics (HEP) experiments. The event data management, including the event data model (EDM), transient event store and data input/output, implements the core functionalities of the framework, and has a great impact on the performance of the entire offline software. Future HEP experiments are generating increasingly large amounts of data, bringing challenges to offline data processing. To address this issue, a common event data management system that supports efficient parallelized data processing applications has been developed based on SNiPER (Software for Non-collider Physics ExpeRiments) common software framework as well as PODIO, a common EDM toolkit for future HEP experiments. In this paper, the implementation of a parallelized event data management (PEDM) system is introduced, including the integration with MT-SNiPER and PODIO, as well as the implementation of GlobalStore to support multi-threaded event processing. Finally, the application and performance evaluation of the data management system in OSCAR (offline software of Super Tau Charm Facility) is presented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
