https://doi.org/10.1051/epjconf/202125103022
MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
1 Dipartimento di Fisica, Università degli Studi di Milano and INFN Sezione di Milano, Milan, Italy
2 CERN, Theoretical Physics Department and OpenLab, CH-1211 Geneva 23, Switzerland
3 Quantum Research Centre, Technology Innovation Institute, Abu Dhabi, UAE
* e-mail: stefano.carrazza@unimi.it
** e-mail: juan.cruz@mi.infn.it
*** e-mail: marco.rossi@cern.ch
**** e-mail: marco.zaro@mi.infn.it
Published online: 23 August 2021
In this proceedings we present MadFlow, a new framework for the automation of Monte Carlo (MC) simulation on graphics processing units (GPU) for particle physics processes. In order to automate MC simulation for a generic number of processes, we design a program which provides to the user the possibility to simulate custom processes through the Mad-Graph5_aMC@NLO framework. The pipeline includes a first stage where the analytic expressions for matrix elements and phase space are generated and exported in a GPU-like format. The simulation is then performed using the VegasFlow and PDFFlow libraries which deploy automatically the full simulation on systems with different hardware acceleration capabilities, such as multi-threading CPU, single-GPU and multi-GPU setups. We show some preliminary results for leading-order simulations on different hardware configurations.
© The Authors, published by EDP Sciences, 2021
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