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Integration of the Italian cache federation within the CMS computing model
The next decades at HL-LHC will be characterized by a huge increase of both storage and computing requirements (between one and two orders of magnitude). Moreover we foresee a shift on resources provisioning towards the exploitation of dynamic (on private or public cloud and HPC facilities) solution...
Autores principales: | , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
SISSA
2019
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.22323/1.351.0014 http://cds.cern.ch/record/2797736 |
Sumario: | The next decades at HL-LHC will be characterized by a huge increase of both storage and
computing requirements (between one and two orders of magnitude). Moreover we foresee a
shift on resources provisioning towards the exploitation of dynamic (on private or public cloud
and HPC facilities) solutions. In this scenario the computing model of the CMS experiment is
pushed towards an evolution for the optimization of the amount of space that is managed
centrally and the CPU efficiency of the jobs that run on "storage-less" resources. In particular
the computing resources of the "Tier2" sites layer, for the most part, can be instrumented to
read data from a geographically distributed cache storage based on unmanaged resources,
reducing, in this way, the operational efforts by a large fraction and generating additional
flexibility.
The objective of this contribution is to present the first implementation of an INFN federation
of cache servers, developed also in collaboration with the eXtreme Data Cloud EU project. The
CNAF Tier-1 plus Bari and Legnaro Tier-2s provide unmanaged storages which have been
organized under a common namespace. This distributed cache federation has been seamlessly
integrated in the CMS computing infrastructure, while the technical implementation of this
solution is based on XRootD, largely adopted in the CMS computing model under the
"Anydata, Anytime, Anywhere project" (AAA).
The results in terms of CMS workflows performances will be shown. In addition a complete
simulation of the effects of the described model under several scenarios, including dynamic
hybrid cloud resource provisioning, will be discussed. Finally a plan for the upgrade of such a
prototype towards a stable INFN setup seamlessly integrated with production CMS computing
infrastructure will be discussed. |
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