HDF5

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Category

Development, Library

Description

HDF5 is a data model, library, and file format for storing and managing data. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data. HDF5 is portable and is extensible, allowing applications to evolve in their use of HDF5. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analyzing data in the HDF5 format.

Available versions (Euler, old software stack)

Legacy versions Supported versions New versions
1.8.12 1.8.13

Please note that this page refers to installations from the old software stack. There are two software stacks on Euler. Newer versions of software are found in the new software stack.

Environment modules (Euler, old software stack)

The hdf5 module is a smart module, which checks for a loaded compiler and MPI module and then loads the corresponding HDF5 version. For the module load command example, we use the standard compiler gcc/4.8.2 and did not load any MPI module (which results in the serial HDF5 version).
Version Module load command Additional modules loaded automatically
1.8.12 module load gcc/4.8.2 hdf5/1.8.12 szip/2.1
1.8.13 module load new gcc/4.8.2 hdf5/1.8.13 szip/2.1

Please note that this page refers to installations from the old software stack. There are two software stacks on Euler. Newer versions of software are found in the new software stack.

License information

BSD-style license

Notes

According to https://portal.hdfgroup.org/pages/viewpage.action?pageId=48809672 one can not build parallel HDF5 with support for the C++ interface. You have to decide if you would like to use either parallel HDF5 without support for the C++ interface, or serial HDF5 with support for the C++ interface. Please note that the centrally installed h5py packages (Python bindings for HDF5) is linked against a serial HDF5 installation. If you would like to use parallel h5py, then you would need to install mpi4py and h5py locally, using a parallel HDF5 installation.

Links

https://support.hdfgroup.org/HDF5

https://en.wikipedia.org/wiki/Hierarchical_Data_Format
http://www.h5py.org