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New HDF5 Features
HDF5 Release 1.10.0 introduces several new features
of the HDF5 Library. A brief description of each new feature
and links to documentation for that feature appear below.
Due to the requirements of some of the new features,
the format of a 1.10.x HDF5 file is likely to be different from
that of a 1.8.x HDF5 file. This means that tools and applications
built to read 1.10.x files will be able to read a 1.8.x file,
but tools built to read 1.8.x files may not be able to read
a 1.10.x file.
SWMR
Data acquisition and computer modeling systems often need to
analyze and visualize data while it is being written. It is not
unusual, for example, for an application to produce results in the
middle of a run that suggest some basic parameters be changed,
sensors be adjusted, or the run be scrapped entirely.
To enable users to check on such systems,
we have been developing a concurrent read/write file access pattern
we call SWMR (pronounced swimmer). SWMR is short for
single-writer/multiple-reader. SWMR functionality allows a writer
process to add data to a file while multiple reader processes read
from the file.
Fine-tuning the Metadata Cache
The orderly operation of the metadata cache is crucial to SWMR
functioning. A number of APIs have been developed to handle
the requests from writer and reader processes and to give applications
the control of the metadata cache they might need. However, the
metadata cache APIs can be used when SWMR is not being used; so,
these functions are described separately.
Collective Metadata I/O
Calls for HDF5 metadata can result in many small reads and writes.
On metadata reads, collective metadata I/O can improve performance
by allowing the library to perform optimizations when reading the
metadata, by having one rank read the data and broadcasting it
to all other ranks.
Collective metadata I/O improves metadata write performance
through the construction of an MPI derived datatype
that is then written collectively in a single call.
File Space Management
Usage patterns when working with an HDF5 file sometimes result in
wasted space within the file. This can also impair access times when
working with the resulting files.
The new file space management feature provides strategies for
managing space in a file to improve performance in both of these arenas.
Virtual Datasets (VDS)
With a growing amount of data in HDF5, the need has emerged to access
data stored across multiple HDF5 files using standard HDF5 objects,
such as groups and datasets, without rewriting or rearranging the data.
The new virtual dataset (VDS) feature enables an application
to draw on multiple datasets and files to create virtual datasets
without moving or rewriting any data.
Partial Edge Chunk Options
New options for the storage and filtering of partial edge chunks
in a dataset provide a tool for tuning I/O speed and file size
in cases where the dataset size may not be a multiple of the chunk size.
Additional New APIs
In addition to the features described above,
several additional new functions, a new struct, and new macros
have been introduced or newly versioned in this release.
For more information on these features, see the
“User, Reference, and Design Documentation” section below.
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Obtaining, Testing, and Experimenting with This Software
These features are now available in HDF5 Release 1.10.0,
release on March 31, 2016.
See Obtaining
the Latest HDF5 Software.
Address any questions to the HDF Group Help Desk
(email address below).
This release includes changes in the HDF5 storage format.
These changes come into play
when one or more of the new features listed above is used or
when an application calls for use of the latest storage format
(H5Pset_libver_bounds).
If an application built on HDF5 Release 1.10.0 avoids use of the
new features and does not request use of the latest format,
applications built on HDF5 Release 1.8.x will be able to read
files the first application created.
In addition, applications originally written for use with
HDF5 Release 1.8.x can be linked against a suitably configured
HDF5 Release 1.10.x library, thus taking advantage of performance
improvements in 1.10.
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The HDF Group
