An efficient and extensible format, library, and API for binary trajectory data from molecular simulations
Year: 2013
Type: article
Abstract: Molecular dynamics simulations is an important application in theoretical chemistry, and with the large high-performance computing resources available today the programs also generate huge amounts of output data. In particular in life sciences, with complex biomolecules such as proteins, simulation projects regularly deal with several terabytes of data. Apart from the need for more cost-efficient storage, it is increasingly important to be able to archive data, secure the integrity against disk or file transfer errors, to provide rapid access, and facilitate exchange of data through open interfaces. There is already a whole range of different formats used, but few if any of them (including our previous ones) fulfill all these goals. To address these shortcomings, we present "Trajectory Next Generation" (TNG)--a flexible but highly optimized and efficient file format designed with interoperability in mind. TNG both provides state-of-the-art multiframe compression as well as a container framework that will make it possible to extend it with new compression algorithms without modifications in programs using it. TNG will be the new file format in the next major release of the GROMACS package, but it has been implemented as a separate library and API with liberal licensing to enable wide adoption both in academic and commercial codes.
DOI: 10.1002/jcc.23495
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2154605091