restructured Querying and Starting sessions

docs/sessions_all/sessions_all.rst

@@ -3,75 +3,21 @@ Compute Sessions
 ================
 
 The most visited pages in the Backend.AI GUI Console would be the Sessions and
-Storage pages. On the Sessions page, you can view, create, and use
-container-based compute sessions, and on the Storage page, you can create a
-storage folder to keep important data. Here, you will learn how to query and
+Data & Storage pages. Here, you will learn how to query and
 create container-based compute sessions and utilize various web applications on
 the Sessions page.
 
-
-Querying compute sessions
--------------------------
-
-To see the list of compute sessions, click Sessions in the left sidebar. In the
-Running tab on the right, you can check the information on the currently running
-sessions. Click the Finished tab to see the list of terminated sessions.  In the
-OTHERS tab you can query for compute sessions with errors.  For each session,
-you can check information such as ID, created date, used time, allocated
-resources, resource usage, and etc.
-
-.. image:: session_list.png
-   :align: center
-   :alt: Session list
-
-As a superadmin, you can see the information of all sessions currently running
-(or ended) in the cluster. On the other hand, users can see their sessions only.
-
-The resource indicator is displayed at the top of the screen. You can check the
-amount of resources currently used and the total amount of resources
-that can be allocated. The display bar is divided into two parts: the upper and
-the lower. The upper part shows the resource allocation status in the current
-scaling group, and the lower part shows the allocation status of total
-accessible resources.
-
-* Upper: Allocated and available resources within the current scaling group
-
-   - (Resources allocated by the user in the current scaling group) /
-     (Total resources allocatable by the user in the current scaling group)
-
-* Lower: Total allocated and available resources
-
-   - (Resources allocated by the user) / (Resources allocated by the user +
-     Total resources allocatable by the user in the current scaling group)
-
-.. note::
-   If the GPU resource is marked as FGPU, this means that the server is serving
-   the GPU resources in a virtualized form. Backend.AI supports GPU
-   virtualization technology that a single physical GPU can be divided and
-   shared by multiple users for better utilization. Therefore, if you want to
-   execute a task that does not require a large amount of GPU computation, you
-   can create a compute session by allocating only a portion of a GPU. The
-   amount of GPU resources that 1 FGPU actually allocates may vary from system
-   to system depending on the administrator's setting. For example, if
-   administrator has set to split one physical GPU into five pieces, 5 FGPU
-   means 1 physical GPU, or 1 FGPU means 0.2 physical GPU. At this
-   configuration, if you create a compute session by allocating 1 FGPU, you can
-   utilize SM (streaming multiprocessor) and GPU memory corresponding to 0.2
-   physical GPU for the session.
-
-
 Start a new session
 -------------------
 
-In addition to see the list of compute sessions, Sessions tab lets you start new
-sessions or use and manage already running sessions. After logging in with a
-user account, click Sessions on the left menu to visit the Sessions page.
+After logging in with a user account, click Sessions on the left menu to visit the Sessions page. 
+Sessions page lets you start new sessions or use and manage existing running sessions. 
 
 .. image:: sessions_page.png
 
 Click the START button to start a new compute session. The following setup
-dialog will appear. You can specify the language environment (Environments,
-Version) and resources you want to allocate. Set the CPU and memory as shown in
+dialog will appear. You can specify the language environment (Environments and
+Version) and the amount of resources you want to allocate. Set the CPU and memory as shown in
 the following figure and click the LAUNCH button.
 
 .. image:: session_launch_dialog.png
@@ -80,67 +26,67 @@ the following figure and click the LAUNCH button.
 
 If you need more detailed settings, refer to the meaning of each items.
 
-* Environment: Specify the default environment for compute sessions such as
-  TensorFlow, PyTorch, C++, and etc. When you select a TensorFlow environment,
+* Environments: Specify the default environment for compute sessions such as
+  TensorFlow, PyTorch, C++, etc. When you select a TensorFlow environment,
   your compute session will automatically include the TensorFlow library.
   If you select another environment, the corresponding environment is installed
   by default.
-* Version: Select the version of the environment. For example, for TensorFlow
-  environment, you can select different versions such as 1.15, 2.3, etc.
-* Resource Group: Specify the resource group in which to create the compute
+* Version: Selects the version of the environment. For TensorFlow
+  environment, for example, you can select different versions such as 1.15, 2.3, etc.
+* Resource Group: Specifies the resource group in which to create the compute
   session. If there are multiple resource groups, you can select the desired
-  value, but if there is only one resource group, it cannot be changed.
+  one, but if there is only one resource group, it cannot be changed.
 * Session name (optional): Specifies the name of the compute session to be
   created. If specified, this name appears in Session Info, making it easy to
-  distinguish from other compute sessions. If not specified, a
-  randomly-generated name is used. You can set the session name up to 4 to
-  64 characters only with alphabetical character or numbers, and no spaces
+  distinguish it from other compute sessions. If not specified, a
+  randomly-generated name is assigned. You can set the session name up to 4 to
+  64 characters only with alphabetical characters or numbers and no spaces
   are allowed.
-* Folder to mount: Specifies the data folder to be mounted in the compute
-  session. When a compute session is deleted, by default all data is deleted
-  altogether, but the data stored in the folder mounted here is not deleted.
+* Folder to mount: Specifies the data folders to be mounted in the compute
+  session. When a compute session is deleted, all data is deleted
+  altogether by default, but the data stored in the folder mounted here is not deleted.
 * Resource allocation: This is a template that has predefined resources to be
   allocated to the compute session. You can save and use frequently used
   resource settings in advance. Resource templates can be managed in a dedicated
   admin hub.
 * CPU: The number of CPU cores to allocate to the compute session. The maximum
   value depends on the resource policy applied to the user.
-* RAM: The amount of memory (GB) to allocate for the compute session. The
+* RAM: The amount of memory (GB) to allocate to the compute session. The
   maximum value depends on the resource policy applied to the user.
-* Shared Memory: The amount of shared memory (GB) to allocate for the
-  compute session. It can only be set up to 2 GB, and cannot be greater than the
+* Shared Memory: The amount of shared memory (GB) to allocate to the
+  compute session. It can be set up to 2 GB and cannot be greater than the
   amount specified in RAM.
 * GPU: The unit of GPU to allocate to the compute session. The maximum value
   depends on the resource policy applied to the user.
 * Sessions: The number of compute sessions to be created with the specified
-  settings. You can specify when you need to create the same computational
+  settings. You can specify this value when you need to create the same computational
   sessions at once.
 
-If no mount folder is specified in "Folders to mount", a warning dialog may
-appear indicating that no storage folder is mounted. It is recommended that one
-or more storage folders to be mounted because terminating compute session by
-default deletes all the data inside the session. If you specify a mount folder
-and save your data in that folder, you can keep the data even if the compute
-session is terminated. Data preserved in the storage folder can also be reused
-by re-mounting it when creating another compute session. You can ignore the
-alarm and create a session. However, it's a good idea to mount a folder if
-you're working on a job that requires you to keep data. For information on how
-to mount a folder and run a compute session, see
-:ref:`Related Content <session-with-mounts>`.
+If no folder is specified in "Folders to mount", a warning dialog may
+appear indicating that no storage folder is mounted. 
 
 .. image:: no_vfolder_notification_dialog.png
    :width: 350
    :align: center
    :alt: Notification dialog when no storage folder is mounted to the session
 
-Notice that a new compute session is created in the Running tab.
+You may ignore the warning, but it is recommended to mount 
+at least one storage folder because terminating a compute session by
+default deletes all the data inside the session. If you specify a folder to mount
+and save your data in that folder, you can keep the data even if the compute
+session is terminated. Data preserved in the storage folder can also be reused
+by re-mounting it when creating another compute session. For the information on how
+to mount a folder and run a compute session, see
+:ref:`Mounting Folders to a Compute Session <session-with-mounts>`.
+
+Notice that a new compute session is created in the Running tab. 
 
 .. image:: session_created.png
 
-You can check information such as ID, start date, usage time, resource setting,
-and resource usage for each session. In particular, check the allocated
-resources in the Configuration column. Note that the amounts of resources you
-specified in creating the compute session are displayed.
+In the RUNNING tab, you can check the information on the currently running
+sessions. FINISHED tab shows the list of terminated sessions and OTHERS tab shows the compute sessions with errors. 
+For each session, you can check the information such as session environments, the amount of allocated
+and used resources, session starting time, etc.
 
 .. note::
    Superadmins can query all compute session information currently running (or
@@ -152,6 +98,34 @@ specified in creating the compute session are displayed.
    network connection problems, and etc. This can be solved by refreshing the
    browser page.
 
+The resource statistics are displayed at the top of the screen. You can check the
+amount of resources currently used and the total amount of resources
+that can be allocated. The display bars are divided into upper and
+lower parts. The upper part shows the resource allocation status in the current
+scaling group and the lower part shows the allocation status of total
+accessible resources.
+
+* Upper: (Resources allocated by the user in the current scaling group) /
+  (Total resources allocatable by the user in the current scaling group)
+
+* Lower: (Resources allocated by the user) / (Resources allocated by the user +
+  Total resources allocatable by the user in the current scaling group)
+
+.. note::
+   If the GPU resource is marked as FGPU, this means that the server is serving
+   the GPU resources in a virtualized form. Backend.AI supports GPU
+   virtualization technology that a single physical GPU can be divided and
+   shared by multiple users for better utilization. Therefore, if you want to
+   execute a task that does not require a large amount of GPU computation, you
+   can create a compute session by allocating only a portion of a GPU. The
+   amount of GPU resources that 1 FGPU actually allocates may vary from system
+   to system depending on the administrator's setting. For example, if
+   administrator has set to split one physical GPU into five pieces, 5 FGPU
+   means 1 physical GPU, or 1 FGPU means 0.2 physical GPU. At this
+   configuration, if you create a compute session by allocating 1 FGPU, you can
+   utilize SM (streaming multiprocessor) and GPU memory corresponding to 0.2
+   physical GPU for the session.
+
 
 Using Jupyter Notebook
 ----------------------