Poster Open Access

Workflows Automation in Computational Chemistry.

zapata, Felipe; Ridder, Lars; Hidding, Johan; Gangarapu, Satesh; Infante, Ivan; Visscher, Lucas

Research on modern computational quantum chemistry relies on a set of computational tools to carry out calculations. The complexity of the calculations usually requires intercommunication between the different simulation tools, such communication is usually done through shell scripts that try to automate input/output actions like: write some input for a target quantum chemistry code; submit the calculation to a supercomputer using some sort of queue system like Slurm or Torque; resume in case of a recoverable failure; analyze the output data both manually or with some kind of script; and finally perform several post-processing steps over the raw data. Such scripts are difficult to maintain and extend, requiring both a significant programming expertise to work with them and constant user intervention, resulting in a sub-optimal use of the valuable computational resources. Also as the workflows complexity increase, the manual approach is impractical due to the among of data that must be analysed. Being then desirable a set of automatic and extensible tools that allows to perform complex simulations in heterogeneous hardware platforms. In this work, we present a Python Software to carry out complex simulations in an extensible and automatic way. We also present its application to the simulation of the nonadiabatic molecular dynamics of quantum dots.

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