scholarly journals Key4hep: Status and Plans

2021 ◽  
Vol 251 ◽  
pp. 03025
Author(s):  
Placido Fernandez Declara ◽  
Wenxing Fang ◽  
Frank Gaede ◽  
Gerardo Ganis ◽  
Benedikt Hegner ◽  
...  
Keyword(s):  
Performance Studies ◽  
Data Model ◽  
High Energy Physics ◽  
High Energy ◽  
Future Collider ◽  
Physics Performance ◽  
Main Components ◽  
Adaptation Processes ◽  
Energy Physics

Detector optimisation and physics performance studies are an integral part of the development of future collider experiments. The Key4hep project aims to design a common set of software tools for future, or even present, High Energy Physics projects. The proceeding describes the main components that are developed as part of Key4hep: the event data model EDM4hep, simulation interfaces to Delphes and Geant4, the k4MarlinWrapper to integrate iLCSoft components, as well as build and validation tools to ensure functionality and compatibility among the components. They also include the different adaptation processes by the CEPC, CLIC, FCC, and ILC communities towards this project, which show that Key4hep is a viable long term solution as baseline software for high energy experiments.

scholarly journals TECHNOLOGIES FOR LARGE DATA MANAGEMENT IN SCIENTIFIC COMPUTING

2014 ◽  
Vol 25 (02) ◽  
pp. 1430001 ◽  
Author(s):  
ALBERTO PACE
Keyword(s):  
Data Management ◽  
High Energy Physics ◽  
Hadron Collider ◽  
Scientific Research ◽  
Large Data ◽  
High Energy ◽  
Worldwide Distribution ◽  
Systematic Collection ◽  
Energy Physics

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago. This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project. The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

scholarly journals Mock Data Challenge for the MPD/NICA Experiment on the HybriLIT Cluster

2018 ◽  
Vol 173 ◽  
pp. 04006 ◽  
Author(s):  
Konstantin Gertsenberger ◽  
Oleg Rogachevsky
Keyword(s):  
Data Model ◽  
High Energy Physics ◽  
Simulated Data ◽  
High Energy ◽  
Physical Analysis ◽  
Simulation Studies ◽  
Production Environment ◽  
Full Production ◽  
Physics Experiments ◽  
Energy Physics

Simulation of data processing before receiving first experimental data is an important issue in high-energy physics experiments. This article presents the current Event Data Model and the Mock Data Challenge for the MPD experiment at the NICA accelerator complex which uses ongoing simulation studies to exercise in a stress-testing the distributed computing infrastructure and experiment software in the full production environment from simulated data through the physical analysis.

scholarly journals HEPiX Benchmarking Solution for WLCG Computing Resources

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Domenico Giordano ◽  
Manfred Alef ◽  
Luca Atzori ◽  
Jean-Michel Barbet ◽  
Olga Datskova ◽  
...  
Keyword(s):  
Working Group ◽  
High Energy Physics ◽  
High Energy ◽  
Computing Power ◽  
Software Applications ◽  
Processor Architectures ◽  
Group A ◽  
Benchmark Suite ◽  
Main Components ◽  
Energy Physics

AbstractThe HEPiX Benchmarking Working Group has developed a framework to benchmark the performance of a computational server using the software applications of the High Energy Physics (HEP) community. This framework consists of two main components, named HEP-Workloads and HEPscore. HEP-Workloads is a collection of standalone production applications provided by a number of HEP experiments. HEPscore is designed to run HEP-Workloads and provide an overall measurement that is representative of the computing power of a system. HEPscore is able to measure the performance of systems with different processor architectures and accelerators. The framework is completed by the HEP Benchmark Suite that simplifies the process of executing HEPscore and other benchmarks such as HEP-SPEC06, SPEC CPU 2017, and DB12. This paper describes the motivation, the design choices, and the results achieved by the HEPiX Benchmarking Working group. A perspective on future plans is also presented.

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