Outputs of simulation codes making use of the HDF5 file format are usually and mainly composed of several different attributes and datasets, storing either lightweight pieces of information or containing heavy parts of data. These objects, when written or read through the HDF5 layer, create metadata and data IO operations of different block sizes, which depend on the precision and dimension of the arrays that are being manipulated. By making use of simple block redistribution strategies, we present in this paper a case study showing HDF5 IO performance improvements for "in-memory" files stored in a distributed shared memory buffer using one-sided communications through the HDF5 API.