Visualization of Scientific Data for High Energy Physics: Basic Architecture and a Case Study

1994 ◽  
pp. 43-53
Author(s):  
Carlo E. Vandoni
Keyword(s):  
High Energy Physics ◽  
High Energy ◽  
Scientific Data ◽  
Energy Physics

A case study on parallel HDF5 dataset concatenation for high energy physics data analysis

2021 ◽  
pp. 102877
Author(s):  
Sunwoo Lee ◽  
Kai-yuan Hou ◽  
Kewei Wang ◽  
Saba Sehrish ◽  
Marc Paterno ◽  
...  
Keyword(s):  
Data Analysis ◽  
High Energy Physics ◽  
High Energy ◽  
Energy Physics

scholarly journals A case study in preserving a high energy physics application with Parrot

2015 ◽  
Vol 664 (3) ◽  
pp. 032022 ◽  
Author(s):  
H Meng ◽  
M Wolf ◽  
P Ivie ◽  
A Woodard ◽  
M Hildreth ◽  
...  
Keyword(s):  
High Energy Physics ◽  
High Energy ◽  
Energy Physics

Learning with first, second, and no derivatives: A case study in high energy physics

1994 ◽  
Vol 6 (2) ◽  
pp. 181-206 ◽  
Author(s):  
Roberto Battiti ◽  
Giampietro Tecchiolli
Keyword(s):  
High Energy Physics ◽  
High Energy ◽  
Energy Physics

scholarly journals High Energy Physics Data Popularity : ATLAS Datasets Popularity Case Study

2020 ◽  
Author(s):  
Maria Grigorieva ◽  
Eugeny Tretyakov ◽  
Alexei Klimentov ◽  
Dmitry Golubkov ◽  
Tatiana Korchuganova ◽  
...  
Keyword(s):  
High Energy Physics ◽  
High Energy ◽  
Energy Physics

scholarly journals Real-time HEP analysis with funcX, a high-performance platform for function as a service

2020 ◽  
Vol 245 ◽  
pp. 07046
Author(s):  
Anna Elizabeth Woodard ◽  
Ana Trisovic ◽  
Zhuozhao Li ◽  
Yadu Babuji ◽  
Ryan Chard ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
High Energy Physics ◽  
High Energy ◽  
Service Platform ◽  
Performance Function ◽  
Service Paradigm ◽  
Heterogeneous Resources ◽  
Energy Physics

We explore how the function as a service paradigm can be used to address the computing challenges in experimental high-energy physics at CERN. As a case study, we use funcX—a high-performance function as a service platform that enables intuitive, flexible, efficient, and scalable remote function execution on existing infrastructure—to parallelize an analysis operating on columnar data to aggregate histograms of analysis products of interest in real-time. We demonstrate efficient execution of such analyses on heterogeneous resources.

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