Working with benchmark datasets in the Cuby framework

14 February 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The development and benchmarking of computational chemistry methods relies on comparison with benchmark data. More and larger benchmark datasets are becoming available, and working efficiently with them is a necessity. The Cuby framework provides rich functionality for working with datasets, comes with many ready-to-use predefined benchmark sets, and interfaces with a wide range of computational chemistry software. Here we review the tools Cuby provides for working with datasets and provide examples of more advanced workflows, such as handling large numbers of computations on HPC resources and reusing previously computed data. Cuby has also been extended recently to include two important benchmark databases, NCIAtlas and GMTKN55.


benchmark datasets
software framework
modular software
method validation

Supplementary materials

Supplementary information for the paper
Additional data and input example.

Supplementary weblinks


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