Live tutorial steps we took during PEARC. See the PEARC video recording to follow along (with images and explanations!):
- Walkthrough tutorial
- Dashboard developer mode tutorial
- Jupyter App Development Tutorial
- Dynamic Batch Connect Fields
- Passenger App Tutorial
- XDMoD Integration Tutorial
These tutorial will be using the the hpcadmin
credentials listed in
Accessing the Applications.
Now you should login to Open OnDemand through https://localhost:3443. Note that you'll have to accept the self-signed certificates from both Open OnDemand and the identity provider.
At some points during this tutorial you'll need to execute commands in a shell session. You can use the shell app to get an ssh session in the web browser for this purpose.
Click to open or close tutorial details.
This tutorial walks through common features in Open OnDemand. There's no development involved. It simply walks through features as a user would interact with them to demonstrate what OnDemand can do.
- The dashboard landing page
- File management
- File viewing and editing
- The Job Composer
- Active Jobs
- Interactive Apps
- Profiles
The dashboard landing page is the first page users see. Administrators can customize what panels are displayed here as well as their position. Administrators can choose from predefined panels like the 'Message of the Day' and even create their own.
The panel welcoming you to this tutorial is a custom panel.
There is a panel with your recently used applications that may show up depending on if you've run any apps. Once you have started either the desktop or jupyter applications, you'll see buttons here to relaunch those applications.
The 'Message of the Day' can display your message of the day similar to how shell logins work. OnDemand supports many formats, and the one shown is in markdown.
Lastly you'll see panels for XDMoD. OnDemand integrates with XDMoD to show pertinant information about the jobs you've recently ran.
In the navigation bar you'll see a dropdown menu entitled Files
. The first
menu item is your $HOME
and this comes by default with every installation.
The second menu item has been added as a 'favorite path'. Administrators
can add many favorite paths to scratch or project spaces for example.
Click the link to HOME
and you'll be redirected to the file manager.
Here you'll see all the files & directories in your $HOME
directory.
You'll see several buttons for file management like making new files and directories,
deleting, downloading, and more.
Go ahead and:
- Make a new directory (you can call it
demo_dir
if you don't have a name handy). - Add a file to that directory (you can call it
demo_file.txt
if you don't have a name handy). - Download that file.
- Delete that file.
- Open a terminal to this new directory (use the 'open in terminal button').
You'll see that instead of starting in your
$HOME
directory, you're in this new directory that you've created.
Now that you know how to create files, go ahead and create a file and in the next section we'll edit it.
If you haven't already created a new file to edit, please do so now. It doesn't really matter where this file is.
Once you have a file you want to edit, click the drop down menu in the same
row as the file and you should see an option to Edit
.
Press Edit
in this menu and the file editor will open in a new tab.
In this view, you can edit the file in the web browser! Go ahead and
do that now, add something to this file. A simple hello world!
will
suffice. Once you've added something to the file, click the Save
button
in the top left.
Now that you've edited the file navigate back to the file browser where
this file exists. Click the same drop down menu you clicked to edit the file
but instead press View
. This will open a new tab with a read only copy
of the file you just edited.
The job composer let's users create and schedule batch jobs from templates.
To navigate there press the Jobs
menu button from the top level navigation
bar. Press the Job Composer
link in that dropdown menu and you'll be redirected
to the job composer.
There's a so called joy ride
that describes what all the buttons do. You can
click Next
to go through them all or dismiss it.
To create a job from a template click the New Job
button at the top left.
Next, select From Template
. This will fill the table with all the available
templates on the system. Only one has been provided in this tutorial, but
administrators at actual sites can supply as many as they wish.
Press the Create new job
button in panel on the right side of the screen titled
Create New "Basic Python Serial Job"
. Once selected, you've created your own
job from this template. You'll see it's placed in the
/home/hpcadmin/ondemand/data/sys/myjobs/projects/default/1
directory and you can open this directory with buttons on the bottom of the page.
Click the job's row in table in the center of the screen. When this job's row
is highlighted the button to Submit
the job becomes available. Press the submit
button and you'll submit this job.
The job should succesfully submit and you should see the state badge in the Status
column of the central table go from queued to running to completed.
Let's go ahead and edit the script we submit by pressing the Open Editor
button
at the bottom of the script's panel (you likely have to scroll down).
Add this sleep 1000
anywhere in the file (so long as it's not commented).
sleep 1000
Submit this job again and next we'll see another view where you can see your active jobs.
Now that you've got a job running that'll last a little bit from the previous section, let's navigate to the active jobs page to view it.
Navigate back to the main OnDemand page by pressing OnDemand
at the
top left of the navigation bar.
Now that we're back to the main OnDemand page, open the Jobs
drop down
menu at the top of the navigation bar and press Active Jobs
.
This will redirect you to our Active Jobs page. On this page you can see the details of all the active jobs running on your clusters. There aren't many jobs running here because we're looking at the cluster that's in these containers, but on a real system it would show all the jobs on that system.
Interactive apps are one of the main features of Open OnDemand. They allow users a click through interface to some of the most popular applications in HPC.
This tutorial will go over luanching the Jupyter application as well as generic Linux desktops
The Interactive Apps
dropdown menu on the top navigation bar lists all the
interactive applications on this system. Other sites can have many more for example
RStudio and MATLAB.
Open the Interactive Apps
menu and press the Desktop
link. This will redirect
you to a form for this application. This form can allow users to fill out different
settings to submit the job with. For example the Number of Hours
field will specify
how long the job can run for. Administrators can specify these fields. So for example
a real site may allow desktops with GPUs and a checkbox in the form for the user to
select a GPU.
There's no need to specify the account, so you can leave it blank. Fill out the rest
of the form (noting that there are only 2 nodes in this cluster) and press the Launch
button.
You'll be redirected to My Interactive Sessions
page where you will see a card for this
job. It should start in the queued state and eventually into the running state. When
it's in the running state a button will appear at the bottom of the card with the text
Launch HPC Desktop
. Press that button when it becomes available to connect to the desktop.
When you press Launch HPC Desktop
a new tab will open connecting you to the desktop.
Note that this desktop is running in a container on one of the compute nodes in the Slurm
cluster. You now have a desktop running on your compute cluster!
Open the applications menu and launch a terminal. Once inside the terminal issue the
glxgears
command and see the GUI for glxgears open up. Feel free to keep the session
open for a while and play around with the XFCE desktop.
Navigate back to the tab with Open OnDemand and open the Interactive Apps
menu
again. Now choose Jupyter instead of a desktop.
This will redirect you to a similar form as we saw before, only it's a form for
launching a Jupyter session instead of a desktop. Choose your settings and launch
by pressing the Launch
button.
Similar to the desktop launching, this will redirect you to My Interactive Sessions
where a new card for this Jupyter application should be.
You'll note on this card though, it has extra information on it. It displays the choices that you've made in the form, for example how much memory you've requested. Administrators, when creating applications, can choose to display certian choices users make in the form in these cards.
Again when the button to Connect to Jupyter
becomes available don't press it
just yet. Instead you can press the button near the top of the card labeled Host
.
This is the host that the job is running on. It's likely cpn01 but could also be
cpn02. Press this button and OnDemand will open a shell session on that compute
node in a new tab.
This allows users to not only run an interactive application they can connect to, but also shell access to the job as well.
Navigate back to Open OnDemand's My interactive sessions
page and press the
Connect to Jupyter
button. This will open a new tab to the Jupyter application
that's running on a compute node in your Slurm cluster!
Connect to the Jupyter session and navigate to the jupyter_notebook_data
directory.
Open the GUI-demo.ipynb
and this should open a new tab to this notebook. Run all
the cells in this notebook for a demonstration that this Jupyter does in fact work.
Open OnDemand 3.0 released with support profiles. Profiles are a way to change the look and feel of an Open OnDemand installation.
Open the Help
menu on the right hand side of the navigation bar and click
the Chemistry
profile. This will redirect you back to the starting page
and set the application into this new profile. You can select Default
from the same menu to get back to the original profile.
The first thing you may notice is that the navigation bar has changed. The main idea with profiles is to construct a view into the OnDemand system that limits the choices of users, so that they may more easily find the application they're interested in or so the system can gear itself towards a specific use case instead of being more general purpose.
We've changed the navigation bar to limit the choices a user can make
within this profile. The desktop application has been removed and only
Jupyter is available. Also the Jobs
menu has been removed along with
several other menu items on the right hand side.
The landing page has also changed. Mostly just re-arranged, but it demonstrates that different profiles can have different landing pages.
Lastly there's a new link entitled Chemistry Notes
. Press this link
and you'll be redirected to a custom page. This page is completely defined
by administrators. Administrators supplied every single panel on this page.
The idea here being that administrators can supply content to their own OnDemand
installation, thereby extending it's functionality by also supplying some
documentation.
Click to open or close tutorial details.
This tutorial covers:
- Starting the dashboard in development mode
- Changing the color of the navbar
- Pinning apps to the dashboard
- Changing the dashboard layout
- Add a custom widget to the dashboard
First we need to pull the source code from the Github Repository. Let's use the shell app for this.
Be sure to be on the ondemand
host because that container has node and ruby on it,
which we need to build the project.
If you are not using the shell app, use ssh
to connect to the ondemand
host from the frontend
host: ssh ondemand
Then, do the following:
git clone https://github.com/OSC/ondemand.git ~/ondemand-src-full
mkdir -p ~/ondemand/dev
cd ~/ondemand/dev
ln -s ../../ondemand-src-full/apps/dashboard/ dashboard
cd dashboard
git checkout release_3.0
bin/bundle config --local path vendor/bundle
bin/setup
** NOTE: M1 Mac users need to run the following commands BEFORE bin/setup
:
bundle config build.nokogiri --use-system-libraries
bundle config set force_ruby_platform true
bin/setup
Once you run bin/setup
you should see a bunch of output about getting Rugy gems and building
Node.js packages.
If you've successfully setup, then so you should be able to navigate to the development version of the dashboard where you'll have to click the button to 'Initialize App' to move forward.
That's it! At this point you should be viewing the dashboard in the development mode. This means that it's your own version of the dashboard. You can modify this as you see fit without having to escalate privileges (become root) or disrupt other users.
We'll need to create and edit an environment file for our development dashboard to read.
# /home/hpcadmin/ondemand/dev/dashboard/.env.local
# you can use pretty names like 'blue' or hex codes like '#5576d1' for royal blue
# OOD_BRAND_BG_COLOR='blue'
OOD_BRAND_BG_COLOR='#5576d1'
Now you may have to restart the server with the button at the top right to see the changes take place.
Now we're going to enable a new feature in 2.0 which is pinning app icons to the dashboard.
First we're going to have to reconfigure the OOD_CONFIG_D_DIRECTORY
environment variable.
It defaults to /etc/ood/config/ondemand.d
, but since we don't want to privilege escalate,
we're going to make a new directory in our home.
mkdir -p ~/ondemand/config/ondemand.d
touch ~/ondemand/config/ondemand.d/ondemand.yml
# /home/hpcadmin/ondemand/dev/dashboard/.env.local
OOD_CONFIG_D_DIRECTORY="/home/hpcadmin/ondemand/config/ondemand.d"
Now let's edit the ondemand.yml file that we initialized above to add the configuration.
# /home/hpcadmin/ondemand/config/ondemand.d/ondemand.yml
pinned_apps:
- 'sys/*'
Restart the dashboard and you should see pinned apps show up.
Now let's group them by their category
by adding this configuration to the same ondemand.yml
file.
# /home/hpcadmin/ondemand/config/ondemand.d/ondemand.yml
pinned_apps:
- 'sys/*'
pinned_apps_group_by: 'category'
Another restart of the webserver will pick up these configurations and you should see pinned apps are now grouped by the category of the application.
See the documentation on pinned apps for more information.
First we're going to enable the message of the day (MOTD)
Let's add these two environment variables to our ~/ondemand/dev/dashboard/.env.local
file.
# /home/hpcadmin/ondemand/dev/dashboard/.env.local
MOTD_PATH=/etc/motd
MOTD_FORMAT=markdown
Restart your webserver and you should now see the MOTD to the right of the page.
Now, just to demonstrate this feature, let's move the MOTD to the left of the page with pinned app icons being on the right.
# /home/hpcadmin/ondemand/config/ondemand.d/ondemand.yml
dashboard_layout:
rows:
- columns:
- width: 4
widgets: [ motd ]
- width: 8
widgets: [ pinned_apps ]
See the documentation on customizing the dashboard layout for more information.
Now that we've changed the layout of the dashboard, let's extend this feature to add a brand new widget.
First, we need to reconfigure where widgets are picked up from. By default they're in /etc/ood/config/apps/dashboard/views/widgets
,
but because we don't want to become root to do this, we're going to reconfigure this location.
So we're going to add these entries to our local environment file.
# /home/hpcadmin/ondemand/dev/dashboard/.env.local
OOD_LOAD_EXTERNAL_CONFIG=1
OOD_APP_CONFIG_ROOT="/home/hpcadmin/ondemand/config"
Next, in a shell, let's initialize some directories and the widget file.
mkdir -p ~/ondemand/config/views/widgets
touch ~/ondemand/config/views/widgets/_hello_world.html
Be sure to add the underscore prefix to this filename! This is a Rails convention for partials and not a mistype
it is indeed _hello_world.html
.
Now, we can use the file editor to edit our new widget. Let's add this very simple div to just thank you for being here. Of course, you can put any text you like here. Feel free to have fun with it!
<!-- /home/hpcadmin/ondemand/config/views/widgets/_hello_world.html -->
<div class='alert alert-info text-center' style='font-size:2.2rem;'>
<p>Thank you for attending the PEARC 2022 Open OnDemand Tutorial!</p>
</div>
Now that we have the widget, we need to add it to the layout. Let's make a new row for it and push everything
else to the second row. This new row will have only one twelve width column that has our new hello_world
widget.
# /home/hpcadmin/ondemand/config/ondemand.d/ondemand.yml
dashboard_layout:
rows:
- columns:
- width: 12
widgets: [ hello_world ]
- columns:
- width: 4
widgets: [ motd ]
- width: 8
widgets: [ pinned_apps ]
Now your dashboard should look something like this with a brand new widget we just creating showing up on the dashboard.
Click to open or close tutorial details.
This tutorial covers:
- Initializing the developer application.
- Debugging the app and getting it to run correctly.
- Changing the type of a form option.
- Adding limits for form options.
- Adding new form options.
- Using native scheduler arguements
- Explanations of the form.yml file.
- Editing the manifest.yml.
- Promoting the application to production.
Click on "My Sandbox Apps (Development)" from the dropdown menu "Develop" in the navigation bar to navigate to the sandbox app workspace.
Now create a new app from the button labeled "New App".
This will bring you to a page where you'll click "Clone Existing App" which will bring you to this form to fill out.
Fill in jupyter
as the directory name. /var/git/bc_example_jupyter
as the Git Remote and
check "Create a new Git Project from this?". Then click "Submit" to create a new development
application.
This copied what was in /var/git/bc_example_jupyter
to /home/hpcadmin/ondemand/dev/jupyter
.
You can navigate to these files through the Files app with this link
or simply Press the "Files" button in Jupyter's row of the sandbox applications table.
You'll also need to setup git
for the hpcadmin user at this point, so let's go ahead and do that
and make first commit to the jupyter app as the starting point.
git config --global user.email hpcadmin@localhost
git config --global user.name "HPC Admin"
cd ~/ondemand/dev/jupyter
git add .
git commit -m 'starting point'
The example application we've created does not use the correct cluster configuration, so we've got to modify it.
If you try to submit it as is, you'll get this error:
We need to edit the form.yml
in the appication's folder. We can navigate to the folder through the
files app. The URL is https://localhost:3443/pun/sys/files/fs/home/hpcadmin/ondemand/dev/jupyter/
.
Here you'll see the form.yml
file. We can edit it by clicking on the file and pressing the "Edit"
button. This will take us to the file editor app, with this file open
In the file Editor, specify hpc
as the cluster attribute on line 11 like so: cluster: "hpc"
. Save this file by clicking
the "Save" button at the top left.
Now when we navigate back to our interactive sessions, you'll see the "Interactive Apps [Sandbox]" menu with an item labeled "Jupyter Notebook".
Follow this link and we'll be presented with this form for specifying different attributes about the job we want to submit to the SLURM scheduler.
We don't need to change anything in this form, so simply press "Launch" at the bottom of the form. After pressing launch the job should have successfully launched the job and redirected us back the interactive sessions page where we'll see a panel showing our job.
This job is going to run and fail during startup. But don't worry! We're going to debug and fix it.
When the job completes, the panel still exists, so you can follow the link in the panel to the log directory of the job.
Follow the link and we'll be redirected to the job's working directory where an output.log
file is.
Let's open that file with the "View" button.
When you open the log file, you'll see the something like this where it says jupyter: command not found.
So you can see, we have PATH
issues.
TIMING - Starting jupyter at: Fri Jul 17 18:06:34 UTC 2020
+ jupyter notebook --config=/home/hpcadmin/ondemand/data/sys/dashboard/batch_connect/dev/jupyter/output/e16b9a77-1a4f-4c9e-95f3-d3c23e5e8d76/config.py
/home/hpcadmin/ondemand/data/sys/dashboard/batch_connect/dev/jupyter/output/e16b9a77-1a4f-4c9e-95f3-d3c23e5e8d76/script.sh: line 27: jupyter: command not found
Timed out waiting for Jupyter Notebook server to open port 16970!
So we know what the issue is, the job's script can't find the jupyter
executable in the PATH
.
Jupyter was installed in these containers through Python's virtual environment and that's
why it's not directly in the shell scripts PATH
.
We need to add this line to our job's shell script to enable it.
source /usr/local/jupyter/2.1.4/bin/activate
So let's open the template/script.sh.erb in the file editor and add this to line 27 of the shell script, just before we start jupyter.
Lines 24 - 31 of template/script.sh.erb
should now look like this.
# Benchmark info
echo "TIMING - Starting jupyter at: $(date)"
source /usr/local/jupyter/2.1.4/bin/activate
# Launch the Jupyter Notebook Server
set -x
jupyter notebook --config="${CONFIG_FILE}" <%= context.extra_jupyter_args %>
Now we can launch the application again and it should work.
When it is up and running and available to use the panel will show a "Connect to Jupyter" button. Click this button and OnDemand will redirect us to Jupyter.
Congratulations! We've now started development on the Jupyter Notebook batch connect application and successfully connected to it.
You may want to delete this job now by using the "Delete" button on the panels as we'll be iterating through developing the application and starting new jobs.
Now it's probably a good idea to save the modifications. They're small, but it'll still help if you
ever get into trouble and need to revert. A simplified version of the form.yml
is in the very next
section, and you may want to use and save it instead so that any git diff
you do will be much
smaller and easier to read.
You can use the shell app to login to this directory
In this shell you'll save in git with these commands:
git add .
git commit -m 'initial commit that correctly submits to the hpc cluster'
The items in the form.yml directly create what's shown to the users in the form they interact with.
Let's take a closer look at the form.yml
that created the form you just submitted to get an
understanding of how they relate to what's shown in the UI.
This is the form.yml
you should have at this point without all the comments.
cluster: "hpc"
attributes:
modules: "python"
extra_jupyter_args: ""
form:
- modules
- extra_jupyter_args
- bc_account
- bc_queue
- bc_num_hours
- bc_num_slots
- bc_email_on_started
All fields pre-pended with bc_
are special fields OnDemand provides for convenience. They are commonly
used fields that create corresponding script attribute. We'll talk more about script attributes later.
modules
Specifies the modules loaded. Since it's hard coded to "python" (in the attributes) we didn't see it in the form.extra_jupyter_args
Specifies the extra jupyter arguments but since it's hard coded to "" we didn't didn't see it in the form.bc_account
Creates the "Account" text field and submits the job with the given account.bc_queue
Creates the "Partition" text field and submits the job to the given partition.bc_num_hours
Creates the "Number of hours" integer field and submits the job with the given walltime.bc_num_slots
Creates the "Number of nodes" integer field and submits the job with the requested cores.bc_email_on_started
Creates the "I would like to receive an email when the session starts" checkbox and submits the job with a request to email when the job starts.
We have 2 partitions enabled in the SLURM containers (SLURM calls queues partitions, so we'll be switching
back and forth between the two terms in this tutorial). We've started with a field bc_queue
that
is a text field, but it's likely much easier for users to simply choose the partition out of a
select dropdown menu instead.
So let's replace the bc_queue
field in the form with a new field that we'll call custom_queue
.
We'll also add custom_queue
to the attributes section. Adding a field to the form section adds it to the form
in the UI. By default, this field will be a text field. If you want this field to be a different type of widget
(as we do) you'll configure the field in the attributes section. Also by default the label in the UI is the
same just the name of the field. In our case custom_queue
would turn into "Custom Queue". This is only
slightly correct, so we want to specify the label as "Partition" because that's what it is in SLURM parlance.
Here you can see that we specify the custom_queue
in the attributes as a select widget with two options.
and a new label. The first element in options arrays is what will be shown to the user (the capitalized version)
where the second element is the value what's actually used in the sbatch command.
# form.yml, with only this addition for brevity
attributes:
custom_queue:
widget: "select"
label: "Partition"
options:
- ["Compute", "compute"]
- ["Debug", "debug"]
form:
- custom_queue
# - bc_queue
Refresh the new session form and you should now see your updates.
But before we submit to test them out, we'll need to reconfigure the submit.yml.erb
to use this
new field. You can
edit the submit.yml.erb in the file editor app.
You'll need to specify the script's queue_name as the partition like so. The script
is the logical
"script" we're submitting to the scheduler. And the queue_name
is the field of the script that will
specify the queue. (OnDemand knows how to translate it from queue_name into partition for SLURM).
script:
queue_name: "<%= custom_queue %>"
The .erb file extension indicates this is embedded ruby file. This means that Ruby will template this file
and turn it into a yml file that OnDemand will then read. <%=
and %>
are embedded ruby tags to turn the
variable (or expression) into a string. Anything we've defined in the form.yml
can be used in this ERB file.
In this example we just defined custom_queue
in the form so we can use it directly here.
If you're not super comfortable with the terminology just remember this: custom_queue
is defined in the form.yml
(the file that defines what the UI form looks like) so it can be used in the submit.yml.erb
(the file
that is used to configure the job that is being submitted) as <%= custom_queue %>
.
When launch the application again you can login to a shell and confirm you chose a different queue with this command.
[hpcadmin@ondemand ~]$ squeue -o "%j %P"
NAME PARTITION
sys/dashboard/dev/jupyter debug
At this point, this should be the entirety of the submit.yml.erb
and form.yml
(without comments).
They're given here in full if you want to copy/paste them. And remember to save your spot!
# submit.yml.erb
script:
queue_name: "<%= custom_queue %>"
# form.yml
cluster: "hpc"
attributes:
modules: "python"
extra_jupyter_args: ""
custom_queue:
widget: "select"
label: "Partition"
options:
- ["Compute", "compute"]
- ["Debug", "debug"]
form:
- modules
- extra_jupyter_args
- bc_account
- custom_queue
- bc_num_hours
- bc_num_slots
- bc_email_on_started
SLURM is configured with only 2 nodes total. If you were now to submit this app
with say 3 or more bc_num_slots
it would sit in the queue forever because SLURM
cannot find a suitable host to run it on.
So, let's limit this field to a max of 2.
# form.yml
attributes:
bc_num_slots:
max: 2
That's it! Again, because bc_num_slots
is convenience field, it already has a minimum of 1
that you can't override, because it doesn't make sense to specify 0 or less nodes.
script.native
attributes are way for us to specify any arguments to the schedulers that
we can't pre-define or have a good generic definition like queue_name
above.
In this section we're going to put make OnDemand request memory through the sbatch's
--mem
argument.
First, let's add it to the form like so.
Here are descriptions of all the fields we'll apply to it. Note if the label was not not defined the default 'Memory' would have been OK. Also we don't really need the the help message here, it was really just for illustration.
widget
specifies the type of widget to be a numbermax
the maximum value, ~1 GB in this casemin
the minimum value, 200 MBstep
the step size when users increase or decrease the valuevalue
the default value of 600 MBlabel
the for UIs labelhelp
a help message
# form.yml, with only this addition for brevity
attributes:
memory:
widget: "number_field"
max: 1000
min: 200
step: 200
value: 600
label: "Memory (MB)"
help: "RSS Memory"
form:
- memory
Again, now to actually use the value we populate in the form, we need to use
it in the submit.yml.erb
. This is where script.native
attributes come in.
# submit.yml.erb
script:
native:
- "--mem"
- "<%= memory %>M"
Native attributes are an array and they're passed to the schedule just as they're defined here.
This would translate into a command much like: sbatch --mem 800M
. As you can see
native allows us to pass anything we wish into the scheduler command.
To confirm your job is running with the correct memory parameters, simply login to a shell and run the command below. You should see output like this.
[hpcadmin@ondemand /]$ squeue -o "%j %m"
NAME MIN_MEMORY
sys/dashboard/dev/jupyter 800M
At this point, this should be the entirety of the submit.yml.erb
and form.yml
(without comments).
They're given here in full if you want to copy/paste them. And remember to save your spot!
# script.yml.erb
---
script:
queue_name: "<%= custom_queue %>"
native:
- "--mem"
- "<%= memory %>M"
# form.yml
cluster: "hpc"
attributes:
modules: "python"
extra_jupyter_args: ""
custom_queue:
widget: "select"
label: "Partition"
options:
- ["Compute", "compute"]
- ["Debug", "debug"]
bc_num_slots:
max: 2
memory:
widget: "number_field"
max: 1000
min: 200
step: 200
value: 600
label: "Memory (MB)"
help: "RSS Memory"
form:
- modules
- extra_jupyter_args
- bc_account
- custom_queue
- bc_num_hours
- bc_num_slots
- bc_email_on_started
- memory
Jupyter ships with both Notebooks and JupyterLab. Some users may want to use JuypterLab instead of Notebooks, so let's give them that option.
First, let's add the checkbox to the form.
# form.yml, with only this addition for brevity
attributes:
jupyterlab_switch:
widget: "check_box"
label: "Use JupyterLab instead of Jupyter Notebook?"
help: |
JupyterLab is the next generation of Jupyter, and is completely compatible with existing Jupyter Notebooks.
form:
- jupyterlab_switch
Refresh the new session form and you should now see your updates.
For this change, there's no need to edit the submit.yml.erb
. This toggle happens in the
actual script that's ran during the job, so we have to edit template.sh.erb
. Note that
this is also an ERB script, so it gets templated in Ruby before being submitted to the
scheduler.
Line 31 is as follows:
jupyter notebook --config="${CONFIG_FILE}" <%= context.extra_jupyter_args %>
Replace the notebook
parameter with this new toggle.
jupyter <%= context.jupyterlab_switch == "1" ? "lab" : "notebook" %> --config="${CONFIG_FILE}" <%= context.extra_jupyter_args %>
If you're unfamiliar with Ruby ternary statements, you can read it them like
this: if true ? do this : else do that
. So this reads, if context.jupyterlab_switch is 1 use lab, else use notebook
.
Also note the use of context
here where we didn't have to use that in the submit.yml.erb
.
This is an important difference. To reference variables from the form in the template/*.sh.erb
files
you must reference them through the context
object.
Now you can submit the job with the checked box to use JupyterLab instead of Notebook and you can see the Jupyter UI is significantly different.
At this point, this should be the entirety of the form.yml
(without comments).
They're given here in full if you want to copy/paste them. And remember to save your spot!
# form.yml
cluster: "hpc"
attributes:
modules: "python"
extra_jupyter_args: ""
custom_queue:
widget: "select"
label: "Partition"
options:
- ["Compute", "compute"]
- ["Debug", "debug"]
bc_num_slots:
max: 2
memory:
widget: "number_field"
max: 1000
min: 200
step: 200
value: 600
label: "Memory (MB)"
help: "RSS Memory"
jupyterlab_switch:
widget: "check_box"
label: "Use JupyterLab instead of Jupyter Notebook?"
help: |
JupyterLab is the next generation of Jupyter, and is completely compatible with existing Jupyter Notebooks.
form:
- modules
- extra_jupyter_args
- bc_account
- custom_queue
- bc_num_hours
- bc_num_slots
- bc_email_on_started
- memory
- jupyterlab_switch
Now we're ready to deploy to production, let's clean up the form a little bit.
We want to remove some items because they're in the example for a real site, but for containers, they just don't apply.
Let's remove these items from the form. Note you'll also have to remove modules
and
extra_jupyter_args
from the attributes section too.
modules
becuase modules don't exist on these compute nodesextra_jupyter_args
because we're not passing anybc_account
because only 1 account is applied to each user, so there's no need to change it.bc_email_on_started
because containers can't email these fake users
Since we got rid of extra_jupyter_args
and modules
, we'll also have them remove it from the
template/script.sh.erb
as well.
Remove lines 13-22 to get rid of modules. And extra_jupyter_args is on line 29 of template/script.sh.erb
.
# remove this block from the 'unless' on line 13 to the 'end' at line 22.
<%- unless context.modules.blank? -%>
# Purge the module environment to avoid conflicts
module purge
# Load the require modules
module load <%= context.modules %>
# List loaded modules
module list
<%- end -%>
# ...
# and remove the last parameter given to jupyter on line 31
jupyter <%= context.jupyterlab_switch == "1" ? "lab" : "notebook" %> --config="${CONFIG_FILE}" <%= context.extra_jupyter_args %>
Now it should look like this:
jupyter <%= context.jupyterlab_switch == "1" ? "lab" : "notebook" %> --config="${CONFIG_FILE}"
At this point, this should be the entirety of the template/script.sh.erb
and form.yml
(without comments).
They're given here in full if you want to copy/paste them. And remember to save your spot!
#!/usr/bin/env bash
# Benchmark info
echo "TIMING - Starting main script at: $(date)"
# Set working directory to home directory
cd "${HOME}"
#
# Start Jupyter Notebook Server
#
# Benchmark info
echo "TIMING - Starting jupyter at: $(date)"
source /usr/local/jupyter/2.1.4/bin/activate
# Launch the Jupyter Notebook Server
set -x
jupyter <%= context.jupyterlab_switch == "1" ? "lab" : "notebook" %> --config="${CONFIG_FILE}"
# form.yml
cluster: "hpc"
attributes:
custom_queue:
widget: "select"
label: "Partition"
options:
- ["Compute", "compute"]
- ["Debug", "debug"]
bc_num_slots:
max: 2
memory:
widget: "number_field"
max: 1000
min: 200
step: 200
value: 600
label: "Memory (MB)"
help: "RSS Memory"
jupyterlab_switch:
widget: "check_box"
label: "Use JupyterLab instead of Jupyter Notebook?"
help: |
JupyterLab is the next generation of Jupyter, and is completely compatible with existing Jupyter Notebooks.
form:
- custom_queue
- bc_num_hours
- bc_num_slots
- memory
- jupyterlab_switch
The OnDemand UI pulls things from the manifest.yml
like the title of the application and where to
put it in the column of interactive applications.
Let's change the these fields. You can change any field except for role
. And you can change
them to something different than what's given here (have fun with it!). All fields besides role
are purely descriptive or relate to UI groups so we can freely change them without any behavior change.
Conversely, role
needs to be batch_connect
so don't change this!
---
# change the name, this is what shows up in the menu
name: HPC Tutorial Jupyter
# change the category just to differentiate from the system installed
# deskop application
category: Tutorial Apps
# change the subcategory
subcategory: Machine Learning
role: batch_connect
# change the description, this shows up when you hover over the menu item
description: |
This app will launch a Jupyter Lab or Notebook on one or more nodes.
If you want to change category
and subcategory
you can freely do so.
These attributes create groupings for applications. Since we will only have two
applications (the system installed "Interactive Apps/Desktops" and this app)
Now save your spot because the next thing we're going to do is deploy this development application to production.
Deploying to production is as easy as copying the files from your dev directory to the system's app directory.
If you don't already have a shell session get a shell session now and execute these commands.
ssh ondemand
cd ~/ondemand/dev
sudo cp -R jupyter/ /var/www/ood/apps/sys/
And that's it! All you have to do now is refresh the page and you should see your Jupyter system app in the menu along with your sandbox development app.
Since 2.0 sites can enable dynamic batch connect fields through setting the OOD_BC_DYNAMIC_JS
environment
variable. This has already been done within these containers.
# /etc/ood/config/apps/dashboard/env
OOD_BC_DYNAMIC_JS=1
With this feature - client side javascript can dynamically change the form fields based on user
choices. Sites only have to add more YAML to a form.yml
to enable this behaviour. Let's
see some examples.
Let's put some rules around the debug queue. We set a static min
and max
of 200 and 1000
respectively. But in this example, we want different min and max values for the debug queue.
We can configure this behaviour with these data-min-
and data-max-
directives attached
to a given option. When the debug
queue is choosen we'll automatically set the min and
maximum values of the memory
field.
Note that we're also setting the compute
min and maxes again. This is currently the only way
to reset back to defaults if there are any.
# form.yml, only showing custom_queue for brevity.
custom_queue:
widget: "select"
label: "Partition"
options:
- [
"Compute", "compute",
data-min-memory: 200, # set the compute queue back to static defaults
data-max-memory: 1000,
]
- [
"Debug", "debug",
data-min-memory: 400, # change min & max for debug queue
data-max-memory: 600,
]
Let's take this a little further. Now, when we choose compute
or debug
queue, let's automatically
set the Slurm account we want to use. Note we'll need to add bc_account
back, as it's what we'll be
setting.
We can add the data-set
directives on the same custom_queue
form options. When users choose the
debug
queue we'll automatically set the account to staff
. When we choose the compute
queue we
will set the sfoster
account.
# form.yml, only showing custom_queue for brevity.
attributes:
custom_queue:
widget: "select"
label: "Partition"
options:
- [
"Compute", "compute",
data-min-memory: 200,
data-max-memory: 1000,
data-set-bc-account: 'sfoster' # set the account to sfoster when using compute
]
- [
"Debug", "debug",
data-min-memory: 400,
data-max-memory: 600,
data-set-bc-account: 'staff' # set the account to staff when using debug
]
form:
- bc_account
To use the sfoster
account you need to run these commands to add the hpcadmin
user to
that account.
sudo sacctmgr add user hpcadmin account=sfoster
sudo sacctmgr modify user where user=hpcadmin set defaultaccount=staff
Lastly, we can use this feature to hide and show other form fields. This can be useful when some options are avaialbe for somethings. For example you may want to show CUDA versions as a form option for GPU nodes, but not for other nodes.
Add the data-hide-bc-account
line to our debug
form option and we'll start hiding that
field when the debug option is chosen.
- [
"Debug", "debug",
data-min-memory: 400,
data-max-memory: 600,
data-set-bc-account: 'staff',
data-hide-bc-account: true, # hide the bc_account field when this is chosen.
]
Click to open or close tutorial details.
Access OnDemand dashboard https://localhost:3443
Configure OnDemand to specify ssh dev host
- Open Shell app from Sandbox apps
- Notice the host is the ondemand
Use ondemand SCL
which ruby
. OnDemand uses SoftwareCollections for RHEL7.scl --list
shows the SCLs. To source the environment,source scl_source enable ondemand
.- For convenience, this was added to
.bash_profile
-cat ~/.bash_profile
- OnDemand configured to ssh to OnDemand host for development
cat /etc/ood/config/apps/dashboard/env
Create new app
- Access OnDemand dashboard https://localhost:3443
- Develop => My Sandbox Apps to see the list of apps
- Click Launch Files
- "New Dir" insert "df" then close
- Reload My Sandbox Apps
Edit app
- Click "Details" on df app to open in App Editor
- Click "Files" button
- "New File" => config.ru
- Select and "Edit"
- Copy app below into editor and click Save:
require 'sinatra'
get "/" do
"<h1>Hello</h1>"
end
run Sinatra::Application
Launch app
- App Editor tab: Click Launch
- App not initialized; click button to initialize. App displays
Notes:
- You can do the same steps through the shell - we are just editing files and accessing URLs.
- Sinatre gem is included in gem set already available with the ondemand deployment. The ondemand gem rpms are separate rpms with version in the name so they stick around until you remove it - no loss of dependencies due to yum update. See ondemand-gems rpms at https://yum.osc.edu/ondemand/latest/web/el7/x86_64/
Passenger native support for Ruby, NodeJS, Python
Example NodeJS app, create an app.js
file in the app directory with this content:
const http = require('http')
const server = http.createServer((req, res) => {
res.writeHead(200, { 'Content-Type': 'text/plain' })
res.write('Hello World from Open OnDemand')
res.end()
})
server.listen(3000, () => {
console.log('Listening on port :3000')
})
Example Python app using system python (v2), create a passenger_wsgi.py
file in the app directory with this content:
import sys
def application(environ, start_response):
start_response('200 OK', [('Content-type', 'text/plain')])
return ["Hello World from Open OnDemand (Python WSGI)!\n\n" + sys.version]
Can specify a different version of Python/Ruby/Node with wrapper script i.e. bin/python
and chmod 755
the file:
#!/bin/bash
# if using software collections:
#
# source scl_source enable rh-python35
#
# then use python instead of python3 below
exec /bin/env python3 "$@"
chmod 755 bin/python
after creating the file!
Example Python app using python3, create a passenger_wsgi.py
file in the app directory with this content:
import sys
def application(environ, start_response):
start_response('200 OK', [('Content-type', 'text/plain')])
return ["Hello World from Open OnDemand (Python WSGI)!\n\n" + sys.version]
Notes:
- Passenger detects what app by the presence of a startup file
- restart the PUN if you change the type of app (ruby => python)
- see https://www.phusionpassenger.com/ for Passenger documentation
- https://www.phusionpassenger.com/library/walkthroughs/start/python.html#the-passenger-wsgi-file
First go to app editor of df app and launch the app.
Reload via "Restart Web Server"
- In File editor, insert
<pre>#{`df`}</pre>
into response body and save - Access app and reload. Changes do not display.
- In App Editor/Dashboard, click Develop => Restart Web Server
- Access app and reload
Reload via App Editor
- In File editor, change title to "df"
- Access app and reload. Changes do not display.
- In App Editor click "Restart App". Notice the command it runs
- Access app and reload
Reload via touch tmp/restart.txt
-
In File editor, change title to "df - disk usage"
-
Access app and reload. Changes do not display.
-
In App Editor click Shell, then exectue command:
touch tmp/restart.txt
-
Access app URL
Notes:
- restarting only the app is beneficial when using the shell app with development so you don't lose your shell connection
- restarting only the app results in shorter reload time
Create manifest
- In App Editor, click Files.
- new file: manifest.yml. then select to edit
---
name: df
description: disk usage
icon: far://hdd
category: Files
subcategory: Utilities
Deploy app
-
In App Editor, click Shell
cd .. sudo cp -r df /var/www/ood/apps/sys/df
-
Reload dashboard/app editor and see app appear in dropdown. Launch it.
-
Initialize app. Notice shell connection lost.
Go to Sandbox App tab and notice URL: https://localhost:3443/pun/dev/df Production app is same URL except "sys" instead of "dev": https://localhost:3443/pun/sys/df
Open new private browser window. Login as sfoster. Try accessing both URLs.
Notes:
- dev apps are only accessible by the user that owns them
- prod apps are accessible to everyone, even if they don't appear in navbar
In App Editor, click Shell
cd /var/www/ood/apps/sys
sudo chmod 700 df
Notice hpcadmin does not have access
sudo setfacl -m u:hpcadmin:rx df
getfacl df
- Now hpcadmin has access
- Now sfoster does not have access
Notes
- authorization controlled through file permissions
- can use ACLs or group ownership
- My Sandbox Apps. Click New App.
- Git Remote:
/var/git/ood-example-ps
. - Launch
App is branded to look like an OnDemand app
Navbar contains link back to the dashboard.
You can make some changes without app restart
- File edit app.rb.
- Change title.
- Save & launch or reload app.
There is a unit test. You can change the test first, then change the code to verify.
- Open shell.
- Execute
rake
.
Many status apps will do the same thing - get data from a shell command, parse it into an intermediate object, use that to generate a view.
Notes:
- See tutorial for details: https://osc.github.io/ood-documentation/master/app-development/tutorials-passenger-apps/ps-to-quota.html
- As an exercise you could change the app to execute
df --output=target,pcent | tail -n+2
- https://github.com/OSC/ood-example-ps
- Open Shell app to ood-example-ps app
bundle install --path vendor/bundle
touch tmp/restart
Notes:
- you can use whatever dependencies you want
- app continues to work even if system libs change
- app specific dependencies adds a "build" step
- takes up more space (but space is cheap)
- very useful during app development to experiment with new packages
- Open Shell app to df app
mkdir public
cp /var/www/ood/apps/sys/jupyter/icon.png public/
- https://localhost:3443/pun/dev/df3/icon.png
Notes:
- when dealing with links to assets or pages in your app, prefix with app suburi
- app suburi is set in env var
PASSENGER_BASE_URI
set by Passenger
Subcategory specifies section in navbar dropdown
- Reload shell and
cd /var/www/ood/apps/sys/df
sudo vim manifest.yml
and remove subcategory and save. - reload dashboard and see effect.
- remove category too and save.
- reload dashboard and see effect.
- access app and reload.
- add back category and subcategory and save.
Icon can be an image or a font awesome icon:
- cp ../jupyter/icon.png .
- reload dashboard and see effect.
- rm icon.png.
- reload dashboard and see effect.
Notes
- app is still accessible even if navbar does not display it
Click to open or close tutorial details.
(Optional) submit a job from job composer to demonstrate XDMoD integration with Job Composer:
- Jobs => Job Composer
- Templates
- Create New Job (with python template)
- Edit Files
- Click
jupyter_notebook_data
in tree. - Select
plot_rbm_logistic_classification.py
and click Copy - Go "back" in browser and click Paste
- Select script.sh click edit
- change
hello.py
toplot_rbm_logistic_classification.py
and save - Back to Job Composer and submit job
Review integration steps (see dashboard MOTD)
- run command to update config
- run command to ingest
Review dashboard widgets - restart Web Server to see
- job efficiency report is based on both core and memory usage but these containers don't gather all the necessary information, which is why they display 100%
Review Job Composer links - access Job Composer
Next Step - Open XDMoD
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