Understanding the Performance of a Prototype of a WLCG Data Lake for HL-LHC

J. Schovancová, S. Campana, X. E. Curull, M. Girone, I. Kadochnikov, G. McCance
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Abstract

Storage is identified as one of the main challenges for WLCG in the next decade in the computing strategy document for HL-LHC [1]. Extrapolating todays computing models, the ATLAS and CMS experiments alone would need one order of magnitude more storage resources than what could be provided by the funding agencies. Organization and consolidation of storage and evolution of the compute facilities will be central in addressing the possible resources shortage. In this contribution we describe the architecture of a prototype of a WLCG data lake for HL-LHC. A WLCG data lake aims to provide a geographically distributed storage service, distributed across large data centres interconnected by fast networks with low latency. We present methodology used to measure and understand the performance of a WLCG data lake prototype, in order to compare event throughput at the same cost at the same compute facilities backed by the traditional storage services and backed by the WLCG data lake. We will discuss various possible data processing models w.r.t. network latency, available storage media, and data caching approaches. We will present benchmarks for storage service and compute performance.
HL-LHC中WLCG数据湖原型的性能研究
在HL-LHC的计算策略文档中,存储被确定为未来十年WLCG面临的主要挑战之一[1]。根据目前的计算模型推断,单是ATLAS和CMS实验就需要比资助机构所能提供的存储资源多一个数量级。组织和整合存储以及计算设施的发展将是解决可能出现的资源短缺问题的核心。在本文中,我们描述了HL-LHC的WLCG数据湖原型的体系结构。WLCG数据湖旨在提供地理上分布式的存储服务,分布在由低延迟快速网络连接的大型数据中心之间。我们提出了用于度量和理解WLCG数据湖原型性能的方法,以便比较由传统存储服务和WLCG数据湖支持的相同计算设施在相同成本下的事件吞吐量。我们将讨论各种可能的数据处理模型,包括网络延迟、可用存储介质和数据缓存方法。我们将介绍存储服务和计算性能的基准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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