Predicting dataset popularity for the CMS experiment

17th International Workshop on Advanced Computing and Analysis Techniques in Physics Research

物理学;计算机科学

Kuznetsov, V.^1 ; Li, T.^1 ; Giommi, L.^2 ; Bonacorsi, D.^2 ; Wildish, T.^3

Cornell University, Ithaca

NY

14850, United States^1

University of Bologna, INFN-Bologna, Italy^2

Princeton University, NJ

08544, United States^3

关键词: Computing infrastructures;    Computing resource;    Data-driven approach;    Dynamic data;    Physics analysis;    Site utilization;    System behaviors;    User activity;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/762/1/012048/pdf
DOI  :  10.1088/1742-6596/762/1/012048

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The CMS experiment at the LHC accelerator at CERN relies on its computing infrastructure to stay at the frontier of High Energy Physics, searching for new phenomena and making discoveries. Even though computing plays a significant role in physics analysis we rarely use its data to predict the system behavior itself. A basic information about computing resources, user activities and site utilization can be really useful for improving the throughput of the system and its management. In this paper, we discuss a first CMS analysis of dataset popularity based on CMS meta-data which can be used as a model for dynamic data placement and provide the foundation of data-driven approach for the CMS computing infrastructure.