Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform
The observation of the associated production of the Higgs boson with two top quarks in proton-proton collisions is one of the highlights of the LHC Run 2. Driven by the theoretical description of the physics processes, the Matrix Element Method (MEM) consists in computing a probability that an event...
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2019-01-01
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doaj-6703605b4e78440490151fbf74a87ace2021-08-02T06:01:39ZengEDP SciencesEPJ Web of Conferences2100-014X2019-01-012140602810.1051/epjconf/201921406028epjconf_chep2018_06028Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platformGrasseau GillesBeaudette FlorianPerez Cristina MartinZabi AlexandreChiron ArnaudStrebler ThomasHautreux GabrielThe observation of the associated production of the Higgs boson with two top quarks in proton-proton collisions is one of the highlights of the LHC Run 2. Driven by the theoretical description of the physics processes, the Matrix Element Method (MEM) consists in computing a probability that an event is compatible with the signal hypothesis (ttH) or with one of the background hypotheses. It is a powerful classifying tool requiring high dimensional integral computations. The deployment of our MEM production code on GPU’s platform will be described. What follows will focus on the adaptation of the main components of the computations in OpenCL kernels, namely the Magraph matrix element code generator, VEGAS, and LHAPDF. Finally, the gain obtained on GPU’s platforms compared with classical CPU’s platforms will be assessed.https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_06028.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Grasseau Gilles Beaudette Florian Perez Cristina Martin Zabi Alexandre Chiron Arnaud Strebler Thomas Hautreux Gabriel |
spellingShingle |
Grasseau Gilles Beaudette Florian Perez Cristina Martin Zabi Alexandre Chiron Arnaud Strebler Thomas Hautreux Gabriel Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform EPJ Web of Conferences |
author_facet |
Grasseau Gilles Beaudette Florian Perez Cristina Martin Zabi Alexandre Chiron Arnaud Strebler Thomas Hautreux Gabriel |
author_sort |
Grasseau Gilles |
title |
Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform |
title_short |
Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform |
title_full |
Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform |
title_fullStr |
Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform |
title_full_unstemmed |
Deployment of a Matrix Element Method code for the ttH channel analysis on GPU’s platform |
title_sort |
deployment of a matrix element method code for the tth channel analysis on gpu’s platform |
publisher |
EDP Sciences |
series |
EPJ Web of Conferences |
issn |
2100-014X |
publishDate |
2019-01-01 |
description |
The observation of the associated production of the Higgs boson with two top quarks in proton-proton collisions is one of the highlights of the LHC Run 2. Driven by the theoretical description of the physics processes, the Matrix Element Method (MEM) consists in computing a probability that an event is compatible with the signal hypothesis (ttH) or with one of the background hypotheses. It is a powerful classifying tool requiring high dimensional integral computations. The deployment of our MEM production code on GPU’s platform will be described. What follows will focus on the adaptation of the main components of the computations in OpenCL kernels, namely the Magraph matrix element code generator, VEGAS, and LHAPDF. Finally, the gain obtained on GPU’s platforms compared with classical CPU’s platforms will be assessed. |
url |
https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_06028.pdf |
work_keys_str_mv |
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