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Oxana Smirnova

Oxana Smirnova

Senior Lecturer, Deputy Head of division

Oxana Smirnova

Impact of different compilers and build types on Geant4 simulation execution time


  • Caterina Marcon
  • Oxana Smirnova
  • Servesh Muralidharan

Summary, in English

Experimental observations and advanced computer simulations in High Energy Physics (HEP) paved the way for the recent discoveries at the Large Hadron Collider (LHC) at CERN. Currently, Monte Carlo simulations account for a very significant amount of computational resources of the Worldwide LHC Computing Grid (WLCG). The current growth in available computing performance will not be enough to fulfill the expected demand for the forthcoming High Luminosity run (HL-LHC). More efficient simulation codes are therefore required.This study focuses on evaluating the impact of different build methods on the simulation execution time. The Geant4 toolkit, the standard simulation code for the LHC experiments, consists of a set of libraries which can be either dynamically or statically linked to the simulation executable. Dynamic libraries are currently the preferred build method.In this work, three versions of the GCC compiler, namely 4.8.5, 6.2.0 and 8.2.0 have been used. In addition, a comparison between four optimization levels (Os, O1, O2 and O3) has also been performed.Static builds for all the GCC versions considered, exhibit a reduction in execution times of about 10%. Switching to newer GCC version results in an average of 30% improvement in the execution time regardless of the build type. In particular, a static build with GCC 8.2.0 leads to an improvement of about 34% with respect to the default configuration (GCC 4.8.5, dynamic, O2). The different GCC optimization flags do not affect the execution times.


  • Particle and nuclear physics
  • eSSENCE: The e-Science Collaboration

Publishing year







EPJ Web of Conferences



Document type

Journal article


EDP Sciences


  • Subatomic Physics
  • Other Computer and Information Science




  • ISSN: 2100-014X