It is fair to say that the lack of activity on the main FortranCL repository for the last 6 years suggests the project has long been forgotten this makes it unattractive for developers to latch on to this as a solution. Other options for GPU acceleration include FortranCL, CUDA (C/C++), OpenCL, and HIP. This is a plus for Fortran programmers, who have a large presence in Department of Energy labs and in earth science departments around the world. PGI compilers ship completely with the CUDA toolkit and a Fortran compiler (pgfortran) that support OpenACC and CUDA-Fortran, languages for writing code that operates on GPUs. The Portland Group Compilers are gaining popularity with the growing interest in accelerating HPC applications with Graphics Processing Units (GPUs). Given this, many applications rely on having a usable working version of HDF5 that they can link into their applications. HDF5 is portable and is extensible, allowing applications to evolve in their use of HDF5." Other data models, like NetCDF from UCAR, are built on top of HDF5 and are heavily used in oceanography, meteorology, and other earth science domains. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data. From the HDF website "HDF5 is a data model, library, and file format for storing and managing data. HDF5 has long been a standard for sharing scientific data across High Performance Computing (HPC) platforms.
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