Exascale Data Processing in Heterogeneous Distributed Computing Infrastructure for Applications in High Energy Physics

2020 ◽  
Vol 51 (6) ◽  
pp. 995-1068
Author(s):  
A. A. Klimentov
Keyword(s):  
Distributed Computing ◽  
Data Processing ◽  
High Energy Physics ◽  
High Energy ◽  
Heterogeneous Distributed Computing ◽  
Distributed Computing Infrastructure ◽  
Computing Infrastructure ◽  
Energy Physics

scholarly journals Computing in High Energy Physics

2005 ◽  
Vol 20 (14) ◽  
pp. 3021-3032
Author(s):  
Ian M. Fisk
Keyword(s):  
Distributed Computing ◽  
Large Scale ◽  
High Energy Physics ◽  
High Energy ◽  
Next Generation ◽  
Physical Infrastructure ◽  
Commodity Computing ◽  
Physics Experiments ◽  
Insight Into ◽  
Energy Physics

In this review, the computing challenges facing the current and next generation of high energy physics experiments will be discussed. High energy physics computing represents an interesting infrastructure challenge as the use of large-scale commodity computing clusters has increased. The causes and ramifications of these infrastructure challenges will be outlined. Increasing requirements, limited physical infrastructure at computing facilities, and limited budgets have driven many experiments to deploy distributed computing solutions to meet the growing computing needs for analysis reconstruction, and simulation. The current generation of experiments have developed and integrated a number of solutions to facilitate distributed computing. The current work of the running experiments gives an insight into the challenges that will be faced by the next generation of experiments and the infrastructure that will be needed.

scholarly journals China-EU scientific cooperation on JUNO distributed computing

2020 ◽  
Vol 245 ◽  
pp. 03038
Author(s):  
Giuseppe Andronico
Keyword(s):  
Distributed Computing ◽  
Data Centers ◽  
High Energy Physics ◽  
Liquid Scintillator ◽  
Statistical Significance ◽  
High Energy ◽  
Relative Energy ◽  
Infrastructure Development ◽  
Scientific Cooperation ◽  
Computing Infrastructure

The Jiangmen Underground Neutrino Observatory (JUNO) is an underground 20 kton liquid scintillator detector being built in the south of China. Targeting an unprecedented relative energy resolution of 3% at 1 MeV, JUNO will be able to study neutrino oscillation phenomena and determine neutrino mass ordering with a statistical significance of 3-4 sigma within six years running time. These physics challenges are addressed by a large Collaboration localized in three continents. In this context, key to the success of JUNO will be the realization of a distributed computing infrastructure to fulfill foreseen computing needs. Computing infrastructure development is performed jointly by the Institute for High Energy Physics (IHEP) (part of Chinese Academy of Sciences (CAS)), and a number of Italian, French and Russian data centers, already part of WLCG (Worldwide LHC Computing Grid). Upon its establishment, JUNO is expected to deliver not less than 2 PB of data per year, to be stored in the data centers throughout China and Europe. Data analysis activities will be also carried out in cooperation. This contribution is meant to report on China-EU cooperation to design and build together the JUNO computing infrastructure and to describe its main characteristics and requirements.

A new approach to distributed computing in high energy physics

1992 ◽  
Author(s):  
Paul Avery ◽  
Chandra Chegireddy ◽  
John Brothers ◽  
Theodore Johnson ◽  
Aric Zion
Keyword(s):  
Distributed Computing ◽  
High Energy Physics ◽  
High Energy ◽  
New Approach ◽  
Energy Physics

scholarly journals RAPPORT: running scientific high-performance computing applications on the cloud

2013 ◽  
Vol 371 (1983) ◽  
pp. 20120073 ◽  
Author(s):  
Jeremy Cohen ◽  
Ioannis Filippis ◽  
Mark Woodbridge ◽  
Daniela Bauer ◽  
Neil Chue Hong ◽  
...  
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
High Performance ◽  
High Energy Physics ◽  
High Energy ◽  
Cloud Infrastructure ◽  
Is Research ◽  
Performance Computing ◽  
Computing Infrastructure ◽  
Energy Physics

Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

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