At ECMWF, the Integrated Forecasting System (IFS) is undergoing an incremental code refactoring aimed at running the forecast on heterogeneous computing architectures. One strategy is using the open-source and in-house developed Atlas library, which provides data structures, memory management and parallelisation techniques, as well as some data manipulation techniques such as interpolation and model component coupling. Crucial parts of the IFS have been extracted as dwarf-codes and have been extensively optimised and ported to non-CPU hardware using the Fortran FIELD API. Built on this experience, this poster presents how new Atlas data structures and memory management techniques are implemented and employed, in order to provide a more generic approach that could be merged into or replace FIELD API eventually. The comparisons of Atlas vs. original Fortran data structures are carried out on “dwarf-cloudsc”, a representative IFS physics parametrisation dwarf.