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doc: Environment, suggested changes

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architeuthidae 2024-07-12 16:33:40 +08:00 committed by Sébastien Bourdeauducq
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doc/manual/environment.rst
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@ -39,11 +39,11 @@ Note that the key (the name of the device) is ``led`` and the value is itself a
Remote (normally, non-realtime) devices must have accessible, suitable controllers and drivers; see :doc:`developing_a_ndsp` for more information, including how to add entries for new remote devices to your device database. Local devices (normally, realtime, e.g. your Sinara hardware) must be factually attached to your system, and more importantly, your gateware and firmware must have been compiled to account for them, and to expect them at those ports. Remote (normally, non-realtime) devices must have accessible, suitable controllers and drivers; see :doc:`developing_a_ndsp` for more information, including how to add entries for new remote devices to your device database. Local devices (normally, realtime, e.g. your Sinara hardware) must be factually attached to your system, and more importantly, your gateware and firmware must have been compiled to account for them, and to expect them at those ports.
While controllers can be added and removed to your device database relatively easily, in order to make new real-time hardware accessible, it is generally also necessary to recompile and reflash your gateware and firmware. (If you purchase your hardware from M-Labs, you will generally be provided with new binaries and necessary assistance.) While controllers can be added and removed to your device database relatively easily, in order to make new real-time hardware accessible, it is generally also necessary to recompile and reflash your gateware and firmware. (If you purchase your hardware from M-Labs, you will normally be provided with new binaries and necessary assistance.)
Adding (or removing) new real-time hardware is a difference in *system configuration,* which is specified by the JSON system description file used in compilation of gateware and firmware. The device database generally provides that information to ARTIQ which can change from instance to instance ARTIQ is run, e.g., device names and aliases, network addresses, clock frequencies, and so on. The system configuration file defines that information which is *not* permitted to change, e.g. what device is associated with which EEM port. Insofar as data is duplicated between the two, the device database is obliged to agree with the system description file, not the other way around. Adding or removing new real-time hardware is a difference in *system configuration,* which must be specified at compilation time of gateware and firmware. For Kasli and Kasli-SoC, this is managed in the form of a JSON usually called the *system description* file. The device database generally provides that information to ARTIQ which can change from instance to instance ARTIQ is run, e.g., device names and aliases, network addresses, clock frequencies, and so on. The system configuration defines that information which is *not* permitted to change, e.g., what device is associated with which EEM port or RTIO channels. Insofar as data is duplicated between the two, the device database is obliged to agree with the system description, not the other way around.
If you obtain your hardware from M-Labs, you will always be provided with a ``device_db.py`` to match your system configuration, which you can edit as necessary to add remote devices, aliases, and so on. In the relatively unlikely case that you are writing a device database from scratch, the ``artiq_ddb_template`` utility can be used to generate a template device database directly from the JSON system description file used to compile your gateware and firmware. This is the easiest way to ensure that details such as the allocation of RTIO channel numbers will be represented in the device database correctly. If you obtain your hardware from M-Labs, you will always be provided with a ``device_db.py`` to match your system configuration, which you can edit as necessary to add remote devices, aliases, and so on. In the relatively unlikely case that you are writing a device database from scratch, the ``artiq_ddb_template`` utility can be used to generate a template device database directly from the JSON system description used to compile your gateware and firmware. This is the easiest way to ensure that details such as the allocation of RTIO channel numbers will be represented in the device database correctly.
Local devices Local devices
^^^^^^^^^^^^^ ^^^^^^^^^^^^^
@ -52,7 +52,7 @@ Local device entries are dictionaries which contain a ``type`` field set to ``lo
The fields ``module`` and ``class`` determine the location of the Python class of the driver. The ``arguments`` field is another (possibly empty) dictionary that contains arguments to pass to the device driver constructor. ``arguments`` is often used to specify the RTIO channel number of a peripheral, which must match the channel number in gateware. The fields ``module`` and ``class`` determine the location of the Python class of the driver. The ``arguments`` field is another (possibly empty) dictionary that contains arguments to pass to the device driver constructor. ``arguments`` is often used to specify the RTIO channel number of a peripheral, which must match the channel number in gateware.
The allocation of RTIO channels to EEM ports is done automatically when the gateware is compiled, and while conceptually simple (channels are assigned one after the other, from zero upwards, for each device entry in the system description file) it is not entirely straightforward (different devices require different numbers of RTIO channels). Again, the easiest way to handle this when writing a new device database is automatically, using ``artiq_ddb_template``. On Kasli and Kasli-SoC, the allocation of RTIO channels to EEM ports is done automatically when the gateware is compiled, and while conceptually simple (channels are assigned one after the other, from zero upwards, for each device entry in the system description file) it is not entirely straightforward (different devices require different numbers of RTIO channels). Again, the easiest way to handle this when writing a new device database is automatically, using ``artiq_ddb_template``.
Controllers Controllers
^^^^^^^^^^^ ^^^^^^^^^^^
@ -71,14 +71,14 @@ If an entry is a string, that string is used as a key for another lookup in the
Arguments Arguments
--------- ---------
Arguments are values that parameterize the behavior of an experiment. ARTIQ supports both interactive arguments, requested and supplied at some point while an experiment is running, as well as submission-time arguments, requested in the build phase and set before the experiment is executed. For more on arguments in practice, see :ref:`mgmt-arguments`. For argument types and specific reference, see the relevant sections of :doc:`the core language reference <core_language_reference>`, as well as the example experiment ``examples/no_hardware/interactive.py``. Arguments are values that parameterize the behavior of an experiment. ARTIQ supports both interactive arguments, requested and supplied at some point while an experiment is running, and submission-time arguments, requested in the build phase and set before the experiment is executed. For more on arguments in practice, see the tutorial section :ref:`mgmt-arguments`. For supported argument types and specific reference, see the relevant sections of :doc:`the core language reference <core_language_reference>`, as well as the example experiment ``examples/no_hardware/interactive.py``.
Datasets Datasets
-------- --------
Datasets are values that are read and written by experiments and principally live in a key-value store. They exist to facilitate exchange and storage of information between experiments, from experiments to the management system, and from experiments to storage. Datasets may be either scalars (``bool``, ``int``, ``float``, or NumPy scalar) or NumPy arrays. For basic use of datasets, see the :ref:`management system tutorial <getting-started-datasets>`. Datasets are values that are read and written by experiments kept in a key-value store. They exist to facilitate the exchange and preservation of information between experiments, from experiments to the management system, and from experiments to long-term storage. Datasets may be either scalars (``bool``, ``int``, ``float``, or NumPy scalar) or NumPy arrays. For basic use of datasets, see the :ref:`management system tutorial <getting-started-datasets>`.
A dataset may be broadcasted (``broadcast=True``), that is, distributed to all clients connected to the master. This is useful e.g. for the ARTIQ dashboard to plot results while an experiment is in progress and give rapid feedback to the user. Broadcasted datasets live in a global key-value store owned by the master. Care should be taken that experiments use distinctive real-time result names in order to avoid conflicts. Broadcasted datasets may be used to communicate values across experiments; for instance, a periodic calibration experiment may update a dataset read by payload experiments. A dataset may be broadcast (``broadcast=True``), that is, distributed to all clients connected to the master. This is useful e.g. for the ARTIQ dashboard to plot results while an experiment is in progress and give rapid feedback to the user. Broadcasted datasets live in a global key-value store owned by the master. Care should be taken that experiments use distinctive real-time result names in order to avoid conflicts. Broadcasted datasets may be used to communicate values across experiments; for instance, a periodic calibration experiment might update a dataset read by payload experiments.
Broadcasted datasets are replaced when a new dataset with the same key (name) is produced. By default, they are erased when the master halts. Broadcasted datasets may be made persistent (``persistent=True``, which also implies ``broadcast=True``), in which case the master stores them in a LMDB database typically called ``dataset_db.mdb``, where they are saved across master restarts. Broadcasted datasets are replaced when a new dataset with the same key (name) is produced. By default, they are erased when the master halts. Broadcasted datasets may be made persistent (``persistent=True``, which also implies ``broadcast=True``), in which case the master stores them in a LMDB database typically called ``dataset_db.mdb``, where they are saved across master restarts.