Elastic computing on Cloud resources for the CMS experiment

Di Maria, Riccardo (2015) Elastic computing on Cloud resources for the CMS experiment. [Laurea magistrale], Università di Bologna, Corso di Studio in Fisica [LM-DM270]
Documenti full-text disponibili:
Documento PDF
Download (6MB) | Anteprima


Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Di Maria, Riccardo
Relatore della tesi
Correlatore della tesi
Corso di studio
Curriculum B: Fisica nucleare e subnucleare
Ordinamento Cds
Parole chiave
Cloud, Grid, High Energy Physics, Computing, dynamic allocation, Cloud Bursting, virtualization, Worker Nodes
Data di discussione della Tesi
24 Luglio 2015

Altri metadati

Statistica sui download

Gestione del documento: Visualizza il documento