JSON/TOML configuration

While the openPMD API intends to be a backend-independent implementation of the openPMD standard, it is sometimes useful to pass configuration parameters to the specific backend in use. For each backend, configuration options can be passed via a JSON- or TOML-formatted string or via environment variables. A JSON/TOML option always takes precedence over an environment variable.

The fundamental structure of this JSON configuration string is given as follows:

  "adios2": "put ADIOS2 config here",
  "hdf5": "put HDF5 config here",
  "json": "put JSON config here"

Every JSON configuration can alternatively be given by its TOML equivalent:

# put ADIOS2 config here

# put HDF5 config here

# put JSON config here

This structure allows keeping one configuration string for several backends at once, with the concrete backend configuration being chosen upon choosing the backend itself.

Options that can be configured via JSON are often also accessible via other means, e.g. environment variables. The following list specifies the priority of these means, beginning with the lowest priority:

  1. Default values

  2. Automatically detected options, e.g. the backend being detected by inspection of the file extension

  3. Environment variables

  4. JSON/TOML configuration. For JSON/TOML, a dataset-specific configuration overwrites a global, Series-wide configuration.

  5. Explicit API calls such as setIterationEncoding()

The configuration is read in a case-insensitive manner, keys as well as values. An exception to this are string values which are forwarded to other libraries such as ADIOS2. Those are read “as-is” and interpreted by the backend library. Parameters that are directly passed through to an external library and not interpreted within openPMD API (e.g. adios2.engine.parameters) are unaffected by this and follow the respective library’s conventions.

The configuration string may refer to the complete openPMD::Series or may additionally be specified per openPMD::Dataset, passed in the respective constructors. This reflects the fact that certain backend-specific parameters may refer to the whole Series (such as storage engines and their parameters) and others refer to actual datasets (such as compression). Dataset-specific configurations are (currently) only available during dataset creation, but not when reading datasets.

Additionally, some backends may provide different implementations to the Series::flush() and Attributable::flushSeries() calls. JSON/TOML strings may be passed to these calls as optional parameters.

A JSON/TOML configuration may either be specified as an inline string that can be parsed as a JSON/TOML object, or alternatively as a path to a JSON/TOML-formatted text file (only in the constructor of openPMD::Series, all other API calls that accept a JSON/TOML specification require in-line datasets):

  • File paths are distinguished by prepending them with an at-sign @. JSON and TOML are then distinguished by the filename extension .json or .toml. If no extension can be uniquely identified, JSON is assumed as default.

  • If no at-sign @ is given, an inline string is assumed. If the first non-blank character of the string is a {, it will be parsed as a JSON value. Otherwise, it is parsed as a TOML value.

For a consistent user interface, backends shall follow the following rules:

  • The configuration structures for the Series and for each dataset should be defined equivalently.

  • Any setting referring to single datasets should also be applicable globally, affecting all datasets (specifying a default).

  • If a setting is defined globally, but also for a concrete dataset, the dataset-specific setting should override the global one.

  • If a setting is passed to a dataset that only makes sense globally (such as the storage engine), the setting should be ignored except for printing a warning. Backends should define clearly which keys are applicable to datasets and which are not.

  • All dataset-specific options should be passed inside the dataset object, e.g.:

      "adios2": {
        "dataset": {
          "put dataset options": "here"
    # put dataset options here

Backend-independent JSON configuration

The openPMD backend can be chosen via the JSON/TOML key backend which recognizes the alternatives ["hdf5", "adios2", "json"].

The iteration encoding can be chosen via the JSON/TOML key iteration_encoding which recognizes the alternatives ["file_based", "group_based", "variable_based"]. Note that for file-based iteration encoding, specification of the expansion pattern in the file name (e.g. data_%T.json) remains mandatory.

The key defer_iteration_parsing can be used to optimize the process of opening an openPMD Series (deferred/lazy parsing). By default, a Series is parsed eagerly, i.e. opening a Series implies reading all available iterations. Especially when a Series has many iterations, this can be a costly operation and users may wish to defer parsing of iterations to a later point adding {"defer_iteration_parsing": true} to their JSON/TOML configuration.

When parsing non-eagerly, each iteration needs to be explicitly opened with Iteration::open() before accessing. (Notice that Iteration::open() is generally recommended to be used in parallel contexts to avoid parallel file accessing hazards). Using the Streaming API (i.e. SeriesInterface::readIteration()) will do this automatically. Parsing eagerly might be very expensive for a Series with many iterations, but will avoid bugs by forgotten calls to Iteration::open(). In complex environments, calling Iteration::open() on an already open environment does no harm (and does not incur additional runtime cost for additional open() calls).

The key resizable can be passed to Dataset options. It if set to {"resizable": true}, this declares that it shall be allowed to increased the Extent of a Dataset via resetDataset() at a later time, i.e., after it has been first declared (and potentially written). For HDF5, resizable Datasets come with a performance penalty. For JSON and ADIOS2, all datasets are resizable, independent of this option.

Configuration Structure per Backend


A full configuration of the ADIOS2 backend:

  "adios2": {
    "engine": {
      "type": "sst",
      "preferred_flush_target": "disk",
      "parameters": {
        "BufferGrowthFactor": "2.0",
        "QueueLimit": "2"
    "dataset": {
      "operators": [
          "type": "blosc",
          "parameters": {
            "clevel": "1",
            "doshuffle": "BLOSC_BITSHUFFLE"
    "attribute_writing_ranks": 0
# ignore all attribute writes not issued on these ranks
# can also be a list if multiple ranks need to be given
# however rank 0 should be the most common option here
attribute_writing_ranks = 0

type = "sst"
preferred_flush_target = "disk"

BufferGrowthFactor = "2.0"
QueueLimit = "2"

# use double brackets to indicate lists
type = "blosc"

# specify parameters for the current operator
clevel = "1"
doshuffle = "BLOSC_BITSHUFFLE"

# use double brackets a second time to indicate a further entry
# specify a second operator here
type = "some other operator"

# the parameters dictionary can also be specified in-line
parameters.clevel = "1"
parameters.doshuffle = "BLOSC_BITSHUFFLE"

All keys found under adios2.dataset are applicable globally as well as per dataset, any other keys such as those found under adios2.engine only globally. Explanation of the single keys:

  • adios2.engine.type: A string that is passed directly to adios2::IO:::SetEngine for choosing the ADIOS2 engine to be used. Please refer to the official ADIOS2 documentation for a list of available engines.

  • adios2.engine.parameters: An associative array of string-formatted engine parameters, passed directly through to adios2::IO::SetParameters. Please refer to the official ADIOS2 documentation for the available engine parameters. The openPMD-api does not interpret these values and instead simply forwards them to ADIOS2.

  • adios2.engine.preferred_flush_target Only relevant for BP5 engine, possible values are "disk" and "buffer" (default: "disk").

    • If "disk", data will be moved to disk on every flush.

    • If "buffer", then only upon ending an IO step or closing an engine.

    This behavior can be overridden on a per-flush basis by specifying this JSON/TOML key as an optional parameter to the Series::flush() or Attributable::seriesFlush() methods.

    Additionally, specifying "disk_override" or "buffer_override" will take precedence over options specified without the _override suffix, allowing to invert the normal precedence order. This way, a data producing code can hardcode the preferred flush target per flush() call, but users can e.g. still entirely deactivate flushing to disk in the Series constructor by specifying preferred_flush_target = buffer_override. This is useful when applying the asynchronous IO capabilities of the BP5 engine.

  • adios2.dataset.operators: This key contains a list of ADIOS2 operators, used to enable compression or dataset transformations. Each object in the list has two keys:

    • type supported ADIOS operator type, e.g. zfp, sz

    • parameters is an associative map of string parameters for the operator (e.g. compression levels)

  • adios2.use_span_based_put: The openPMD-api exposes the span-based Put() API of ADIOS2 via an overload of RecordComponent::storeChunk(). This API is incompatible with compression operators as described above. The openPMD-api will automatically use a fallback implementation for the span-based Put() API if any operator is added to a dataset. This workaround is enabled on a per-dataset level. The workaround can be completely deactivated by specifying {"adios2": {"use_span_based_put": true}} or it can alternatively be activated indiscriminately for all datasets by specifying {"adios2": {"use_span_based_put": false}}.

  • adios2.attribute_writing_ranks: A list of MPI ranks that define metadata. ADIOS2 attributes will be written only from those ranks, any other ranks will be ignored. Can be either a list of integers or a single integer.


Specifying adios2.attribute_writing_ranks can lead to serious serialization performance improvements at large scale.

Operations specified inside adios2.dataset.operators will be applied to ADIOS2 datasets in writing as well as in reading. Beginning with ADIOS2 2.8.0, this can be used to specify decompressor settings:

  "adios2": {
    "dataset": {
      "operators": [
          "type": "blosc",
          "parameters": {
            "nthreads": 2

In older ADIOS2 versions, this specification will be without effect in read mode. Dataset-specific configurations are (currently) only possible when creating datasets, not when reading.

Any setting specified under adios2.dataset is applicable globally as well as on a per-dataset level. Any setting under adios2.engine is applicable globally only.


A full configuration of the HDF5 backend:

  "hdf5": {
    "dataset": {
      "chunks": "auto"
    "vfd": {
      "type": "subfiling",
      "ioc_selection": "every_nth_rank",
      "stripe_size": 33554432,
      "stripe_count": -1

All keys found under hdf5.dataset are applicable globally as well as per dataset. Explanation of the single keys:

  • hdf5.dataset.chunks: This key contains options for data chunking via H5Pset_chunk. The default is "auto" for a heuristic. "none" can be used to disable chunking.

    An explicit chunk size can be specified as a list of positive integers, e.g. hdf5.dataset.chunks = [10, 100]. Note that this specification should only be used per-dataset, e.g. in resetDataset()/reset_dataset().

    Chunking generally improves performance and only needs to be disabled in corner-cases, e.g. when heavily relying on independent, parallel I/O that non-collectively declares data records.

  • hdf5.vfd.type selects the HDF5 virtual file driver. Currently available are:

    • "default": Equivalent to specifying nothing.

    • subfiling": Use the subfiling VFD. Note that the subfiling VFD needs to be enabled explicitly when configuring HDF5 and threaded MPI must be used. When using this VFD, the options described below are additionally available. They correspond with the field entries of H5FD_subfiling_params_t, refer to the HDF5 documentation for their detailed meanings.

      • hdf5.vfd.ioc_selection: Must be one of ["one_per_node", "every_nth_rank", "with_config", "total"]

      • hdf5.vfd.stripe_size: Must be an integer

      • hdf5.vfd.stripe_count: Must be an integer

Other backends

Do currently not read the configuration string. Please refer to the respective backends’ documentations for further information on their configuration.