Working with benchmark datasets in the Cuby framework

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388963%3A_____%2F24%3A00586410" target="_blank" >RIV/61388963:_____/24:00586410 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1063/5.0203372" target="_blank" >https://doi.org/10.1063/5.0203372</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/5.0203372" target="_blank" >10.1063/5.0203372</a>

Result language
angličtina
Original language name
Working with benchmark datasets in the Cuby framework
Original language description
The development and benchmarking of computational chemistry methods rely 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 packages. 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 high performance computing resources and reusing previously computed data. Cuby has also been extended recently to include two important benchmark databases, NCIAtlas and GMTKN55.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10403 - Physical chemistry

Project
<a href="/en/project/GA22-17063S" target="_blank" >GA22-17063S: Data-driven approach to the development of next-generation semiempirical QM methods</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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