Automated analysis and benchmarking of GCMC simulation programs in application to gas adsorption

Richard J. Gowers, Amir H. Farmahini, Daniel Friedrich, Lev Sarkisov

Research output: Contribution to journalArticlepeer-review


In this work we set out to evaluate the computational performance of several popular Monte Carlo simulation programs, namely Cassandra, DL Monte, Music, Raspa and Towhee, in modelling gas adsorption in crystalline materials. We focus on the reference case of adsorption in IRMOF-1 at 208 K. To critically assess their performance, we first establish some criteria which allow us to make this assessment on a consistent basis. Specifically, the total computational time required for a program to complete a simulation of an adsorption point, consists of the time required for equilibration plus time required to generate a specific number of uncorrelated samples of the property of interest. Our analysis shows that across different programs there is a wide difference in the statistical value of a single MC step, however their computational performance is quite comparable. We further explore the use of energy grids and energy bias techniques, as well as the efficiency of the parallel execution of the simulations. The test cases developed are made openly available as a resource for the community, and can be used for validation and as a template for further studies.
Original languageEnglish
Pages (from-to)309-321
Issue number4
Early online date20 Sept 2017
Publication statusPublished - 4 Mar 2018


  • Benchmarking
  • grand canonical Monte Carlo
  • adsorption
  • computational performance
  • sampling


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