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This tutorial assumes that you are somewhat familiar with parallel programming with MPI (Message Passing Interface).

If you are not familiar with parallel programming, here is a tutorial that may be of interest:

• Tutorial on HDF5 I/O tuning at NERSC

Some of the terms that you must understand in this tutorial are:

• MPI Communicator:

  Allows a group of processes to communicate with each other.

  Following are the MPI routines for initializing MPI and the communicator and finalizing a session with MPI:

  
      C               Fortran          Description
      --              -------          -----------
      MPI_Init        MPI_INIT         Initialize MPI (MPI_COMM_WORLD usually)
  
      MPI_Comm_size   MPI_COMM_SIZE    Define how many processes are contained 
                                       in the communicator
  
      MPI_Comm_rank   MPI_COMM_RANK    Define the process ID number within 
                                       the communicator (from 0 to n-1)
  
      MPI_Finalize    MPI_FINALIZE     Exiting MPI
  

• Collective:   MPI defines this to mean all processes of the communicator must participate in the right order.

Parallel HDF5 opens a parallel file with a communicator. It returns a file handle to be used for future access to the file.

All processes are required to participate in the collective Parallel HDF5 API. Different files can be opened using different communicators.

Examples of what you can do with the Parallel HDF5 collective API:

• File Operation:            Create, open and close a file
• Object Creation:          Create, open, and close a dataset
• Object Structure:         Extend a dataset (increase dimension sizes)
• Dataset Operations:   Write to or read from a dataset
  (Array data transfer can be collective or independent.)

Once a file is opened by the processes of a communicator:

• All parts of the file are accessible by all processes.
• All objects in the file are accessible by all processes.
• Multiple processes write to the same dataset.
• Each process writes to a individual dataset.

Please refer to the Supported Configuration Features Summary in the release notes for the current release of HDF5 for an up-to-date list of the platforms that we support Parallel HDF5 on.