docs: Add qs for webui users (#8754)

* docs: Add qs for webui users

Adding a qs for webui users.

* revisions

docs/get-started/webui-qs.rst

@@ -0,0 +1,152 @@
+.. _qs-webui:
+
+##############################
+ Create Your First Experiment
+##############################
+
+Follow these steps to see how to run your first experiment.
+
+***************
+ Prerequisites
+***************
+
+You must have a running Determined cluster with the CLI installed.
+
+-  To set one up locally, visit :ref:`basic`.
+-  To set one up remotely, choose from On Prem, AWS, GCP, Kubernetes, or Slurm.
+
+*******************
+ Run an Experiment
+*******************
+
+.. tabs::
+
+   .. tab::
+
+      locally
+
+      Train a single model for a fixed number of batches, using constant values for all
+      hyperparameters on a single *slot*. A slot is a CPU or CPU computing device, which the
+      Determined master schedules to run.
+
+      .. note::
+
+         To run an experiment in a local training environment, your Determined cluster requires only
+         a single CPU or GPU. A cluster is made up of a master and one or more agents. A single
+         machine can serve as both a master and an agent.
+
+      #. Download and extract the tar file: :download:`mnist_pytorch.tgz
+         <../examples/mnist_pytorch.tgz>`.
+
+      #. Open a terminal window and navigate to the directory where you extracted the tar file.
+
+         The ``const.yaml`` file is a YAML-formatted :ref:`experiment configuration
+         <experiment-config-reference>` file that corresponds to an example experiment.
+
+      #. Create an experiment that specifies the ``const.yaml`` configuration file by typing the
+         following :ref:`CLI <cli-ug>` command.
+
+         .. code:: bash
+
+            det experiment create const.yaml .
+
+         The final dot (.) argument uploads all of the files in the current directory as the
+         *context directory* for your model. Determined copies the model context directory contents
+         to the trial container working directory.
+
+      #. To view the experiment in your browser:
+
+         -  Enter the following URL: **http://localhost:8080/**. This is the cluster address for
+            your local training environment.
+         -  Accept the default username of ``determined``, and click **Sign In**. A password is not
+            required.
+
+      #. Navigate to the home page and then visit your **Uncategorized** experiments.
+
+         .. image:: /assets/images/qswebui-recent-local.png
+            :alt: Determined AI WebUI Dashboard showing a user's recent experiment submissions
+
+      #. Select the experiment to display the experiment’s details such as Metrics.
+
+         .. image:: /assets/images/qswebui-metrics-local.png
+            :alt: Determined AI WebUI Dashboard showing details for a local experiment
+
+   .. tab::
+
+      remotely
+
+      Run a remote distributed training job.
+
+      .. note::
+
+         To run a remote distributed training job, you'll need a Determined cluster with multiple
+         GPUs. In distributed training, A cluster is made up of a master and one or more agents. The
+         master provides centralized management of the agent resources. By default, the
+         :ref:`slots-per-trial` value is set to ``1`` which disables distributed training.
+
+      #. Download and extract the tar file: :download:`mnist_pytorch.tgz
+         <../examples/mnist_pytorch.tgz>`.
+
+      #. Open a terminal window and navigate to the directory where you extracted the tar file.
+
+      #. Using your code editor, examine the ``distributed.yaml`` file. Notice the
+         ``resources.slots_per_trial`` field is set to a value of ``8``:
+
+         .. code:: yaml
+
+            resources:
+               slots_per_trial: 8
+
+         This is the number of available GPU resources. The ``slots_per_trial`` value must be
+         divisible by the number of GPUs per machine.
+
+         -  If necessary, use your code editor to change the value to match your hardware
+            configuration.
+
+      #. Sign in to your remote instance of Determined:
+
+         -  Enter the URL of your remote instance: **http://<ipAddress>:8080/**.
+         -  Sign in using your username and password.
+
+      #. To connect to the Determined master running on your remote instance, set the remote IP
+         address and port number in the ``DET_MASTER`` environment variable:
+
+         .. code:: bash
+
+            export DET_MASTER=<ipAddress>:8080
+
+      #. To create and run the experiment, run the following command, replacing ``<username>`` with
+         your username.
+
+         .. code:: bash
+
+            det -u <username> experiment create distributed.yaml .
+
+         -  The system will ask for your password.
+
+      #. In your browser, navigate to the home page and then visit **Your Recent Submissions**.
+
+         .. image:: /assets/images/qswebui-recent-remote.png
+            :alt: Determined AI WebUI Dashboard showing a user's recent experiment submissions
+
+      #. Select the experiment to display the experiment’s details such as Metrics. Notice the loss
+         curve is similar to the locally-run, single-GPU experiment but the time to complete the
+         trial is reduced by about half.
+
+         .. image:: /assets/images/qswebui-metrics-remote.png
+            :alt: Determined AI WebUI Dashboard showing details for a remote distributed experiment
+
+************
+ Learn More
+************
+
+**Want to learn how to adapt your existing model code to Determined?**
+
+The behavior of an experiment is configured via an experiment configuration, or YAML, file. A
+configuration file is typically passed as a command-line argument when an experiment is created with
+the :ref:`CLI <cli-ug>`.
+
+-  Visit the :ref:`experiment-config-reference` for a complete description of the experiment
+   configuration file.
+-  Visit the :ref:`api-core-ug` for a walk-through of how to adapt your existing model code to
+   Determined using the PyTorch MNIST model.

docs/model-dev-guide/dtrain/dtrain-implement.rst

@@ -22,6 +22,8 @@ training, as described in :ref:`master-config-reference-dtrain-network-interface
  Configuration
 ***************
 
+.. _slots-per-trial:
+
 Slots Per Trial
 ===============