Reference : OpenMP optimisation of the eXtended Discrete Element Method (XDEM)

	Document type :	Reports : External report
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/46716

Title :	OpenMP optimisation of the eXtended Discrete Element Method (XDEM)
Language :	English
Author, co-author :	Ojeda-May, Pedro [Umeå Universitet > MIT Huset > High Performance Computing Center North (HPC2N)]
	Eriksson, Jerry [Umeå Universitet > MIT Huset > High Performance Computing Center North (HPC2N)]
	Rousset, Alban [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Besseron, Xavier [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Mainassara Chekaraou, Abdoul Wahid [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Peters, Bernhard [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Publication date :	2-Mar-2021
Publisher :	Partnership for Advanced Computing in Europe
Abstract :	[en] The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM method by adding features where both micro and macroscopic observables can be computed simultaneously by coupling different time and length scales. In this sense XDEM belongs the category of multi-scale/multi-physics applications which can be used in realistic simulations. In this whitepaper, we detail the different optimisations done during the preparatory PRACE project to overcome known bottlenecks in the OpenMP implementation of XDEM. We analysed the Conversion, Dynamic, and the combined Dynamics-Conversion modules with Extrae/Paraver and Intel VTune profiling tools in order to find the most expensive functions. The proposed code modifications improved the performance of XDEM by ~17% for the computational expensive Dynamics-Conversion combined modules (with 48 cores, full node). Our analysis was performed in the Marenostrum 4 (MN4) PRACE infrastructure at Barcelona Supercomputing Center (BSC).
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/46716
Other URL :	https://prace-ri.eu/wp-content/uploads/WP298.pdf
FnR project :	FnR ; FNR13318107 > Bernhard Peters > VP4HPC > Virtual Prototyping Enhanced Through Novel High Performance Computing Technology > 01/02/2019 > 31/01/2021 > 2018

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