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

Richard Gowers, Amir Hajiahmadi Farmahini, Daniel Friedrich, Lev Sarkisov

Research output: Contribution to journalArticlepeer-review

Abstract

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 CO2 adsorption in IRMOF-1 at 208K. 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
JournalMolecular simulation
Volume44
Issue number4
Early online date20 Sep 2017
DOIs
Publication statusE-pub ahead of print - 20 Sep 2017

Keywords

  • Benchmarking
  • grand canonical Monte Carlo
  • Adsorption
  • computational performance
  • Sampling

Fingerprint

Dive into the research topics of 'Automated analysis and benchmarking of GCMC simulation programs in application to gas adsorption.'. Together they form a unique fingerprint.

Cite this