The RDHPCS Cloud Platform allows NOAA users to create an custom HPC
cluster on an as-needed basis, with the type of resources that are
appropriate for the task at hand.
NOAA Cloud Computing uses the Parallel Works computing platform to allow users to
manage their cloud computing resources across Amazon Web Services
(AWS), Google Compute Platform (GCP), and Microsoft Azure Cloud
Computing Services (Azure) via the NOAA RDHPCS Portal, customized for NOAA.
The Parallel Works User Guide is their standard documentation. NOAA
users will find minor differences, for example, the login
authentication, and project allocation, between the standard and
customized applications.
Your username is your RDHPCS NOAA username.
Your password is your RSA PIN plus the 8 digit code from your RSA token.
When you are logged in, click Compute.
On the Compute tab, notice the following:
Power button: Used to start and stop clusters.
Node Status indicator: Displays resources currently in use.
Status indicator: Displays the cluster status (Active/Stopped)
Gear: This button opens a new tab to configure a cluster.
“i” button: Opens a status window with the login node IP address.
Users can install and use a Globus Connect Personal endpoint to transfer larger
files. The RDHPCS reminds all users who perform transfers out of the cloud of
using a Globus endpoint that all egress charges will be applied to the project.
This includes data stored in a CSP public, free to access repositories, like
the NOAA Open Data Dissemination (NODD) program.
NOAA Cloud Computing uses the Parallel Works ACTIVATE platform. ACTIVATE allows
users to manage their cloud computing resources across Amazon Web Services
(AWS), Google Compute Platform (GCP), and Microsoft Azure Cloud Computing
Services (Azure). Users access ACTIVATE via the customized NOAA RDHPCS Portal.
Note
The Parallel Works User guide provides comprehensive
information for using the ACTIVATE control plane.
The certified browser for Parallel Works is Google Chrome. To use the ACTIVATE
platform, you must have a NOAA user account and password, and a valid RSA
token. Click the links for instructions for Applying for a user account
and obtaining RSA Tokens.
You must also be assigned to a Cloud project account. To join a Cloud project,
first request the project name from your PI, TL, or Portfolio Manager. Then use
the AIM tool to request access to that project.
See the Workflow diagram for an overview of the process.
Users access the ACTIVATE platform through the Parallel Works NOAA Portal,
using the RSA Token authentication method. On the landing page, enter your
NOAA user name, and your PIN and SecurID OTP.
Lustre is a parallel file system, available as ephemeral and persistent storage
on the AWS, Azure, and GCP cloud platforms. A lustre file system can be
attached and mounted on a cluster, and is accessible only from an active
cluster. To create a lustre file system, access the Storage tab, and click Add
Storage. You can create any number of lustre file systems. See this article for
information on creating a storage link.
Bucket storage and Block blob storage are containers for objects. An object is
a file and any metadata that describes that file. Metadata can include use
cases, such as data lakes, websites, mobile applications, backup and restore,
archive, enterprise applications, IoT devices, or big data analytics. On AWS
and GCP, the storage is called S3 bucket, and bucket respectively, whereas in
Azure, the storage used is Blob storage, which functions as a bucket storage,
which functions as a bucket and an NFS storage. Pricing information is
available at this link . Projects using
AWS, and GCP platforms can create as many buckets as needed, and mount them on
a cluster. The project’s default bucket is accessible from the public domain
using the keys.
The Contrib file system concept is similar to on-premise contrib. It is used to
store files for team collaboration. You can use this storage to install custom
libraries or user scripts.
The contrib filesystem is built on the cloud provider’s native NFS service,
which is EFS in AWS, Azure Files in Azure, and GFS in GCP. The pricing on the
AWS EFS is based on the amount of storage used, whereas Azure and GCP pricing
is based on the provisioned capacity. This makes the AWS contrib cost
lower than Azure and GCP, comparatively. To find the pricing from the
Parallel Works Home, click on the NFS link and enter a storage size. The
provisioned storage can be resized to a higher size anytime.
AWS Contrib storage charge is $0.30 per GB per Month. The cost is calculated
based on the storage usage. Both AWS and Azure charge based on usage, with a
pay-as-you-go model like your electricity bill.
GCP charges on allocated storage, so whether the storage is used or not, the
project pays for the provisioned capacity. The default provisioned capacity of
Google Cloud contrib file system is 2.5 TiB, costs $768.00 per month. The
contrib volume can be removed from a project by request. Send email to
rdhpcs.cloud.help@noaa.gov, with Remove Contrib Volume in the subject.
Cloud projects are specific to a Cloud platform. The platform is indicated by the
prefix in the project name (ca- for AWS, cz- for Azure, cg- for GCP).
Cloud projects are defined through the AIM system. Before you can create a
project in AIM, it must have assigned allocation. Allocations are approved by
the NOAA RDHPCS allocation committee.
If your project is large in size and requires assistance in capacity planning,
planning and porting, open a help desk ticket. Send email to
rdhpcs.cloud.help@noaa.gov, with Allocation for <Project> in the subject line.
A PI or Portfolio Manager can request a new project by creating a cloud
help desk ticket including the following information:
Project short name, in the format: <cloud platform abbreviation>-<project
name> For example ca-epic stands for AWS Epic, cz-epic for Azure epic, and
cg-epic for Google cloud Epic.
Brief description of your project.
Portfolio name.
Principal Investigator [PI] name.
Technical lead name [TL]. (If the project’s PI and TL are the same, repeat
the name.)
Allocation amount.
Using this information, the AIM system administrator can create a project on
the Parallel Works platform. This can take up to two days. Upon the project
creation, the AIM administrator will email back with the project status.
Parallel Works offers seamless authentication with on-premise HPC systems. The
access method through Parallel Works is the same as for any other HPC
systems.
You may use the default template of an HPS system from the Parallel Works
Marketplace.
From the login portal, click on the user Name.
Select MARKETPLACE from the drop down list box.
Click on the Fork sign and click the Fork button when prompted. Exit the
page.
Access the head node from the Parallel Works [PW]
web interface. You can connect to the head node from the PW portal, or Xterm
window, if you have added your public key in the resource definition prior to
launching a cluster. If you have not yet added a public key, you can login to
the head node by IDE and update the public key in ~/.ssh/authorized_keys file.
From the PW Compute dashboard, click on your name with an IP address and
make a note of it. Otherwise, click the i icon of the Resource monitor to
get the head node IP address.
Click the IDE link (located on the top right side of the PW interface) to
launch a new terminal.
From the Terminal menu, click New Terminal. A new terminal window opens.
From the new terminal, type $ ssh <username with IP address> and press
Enter.
This will let you login to the head node from the PW interface.
Running a Jupyterlab Workflow on an On-Prem Controller Node
The Parallel Works ACTIVATE platform includes a Jupyterlab workflow that can
run on on-premise controller nodes. This workflow is available in the ACTIVATE
Marketplace. (See Where do I get detailed Workflow instructions? for an overview.)
Jupyterlab is a great tool. To use it, you will need access to your project
files, and to your virtual environment. Follow these steps to get started:
Start a session on the on-prem cluster you want to use.
Install the Jupyterlab workflow into your workspace. (You can find the
Jupyterlab workflow in the Marketplace.) Once that is installed, you will
see your Jupyterlab workflow icon when you return to the Parallel Works
Home page. Click this icon.
In this dialog select your on-prem cluster session. Click Execute.
You should now see the Jupyterlab interface. Click on the Terminal.
You should see a terminal interface on the on-prem cluster session. In this
session, you can enter a command that will make any virtual environment you
have on this cluster available within Jupyterlab. This command is:
ipythonkernelinstall--user--name=YOUR_ENV_NAME
where YOUR_ENV_NAME = My_venv.
When you return to the Launcher tab in Jupyterlab, you should now see
options in both the Notebook section and the Console section that
contain the name of the virtual environment you just added (My_venv, in this
example).
Click the Notebook icon that contains your environment name.
Select File from the top command bar, then select
Open from Path…
Enter the path to the project you want to work with.
You can use a node’s hostname to ssh to compute nodes in your cluster from the
head node. You do not need to have a job running on the node, but the node must
be in a powered-on state.
Note
Most resource configurations suspend compute nodes after a period of inactivity.
Occasionally, a user user trying to run a workflow received a warning about
exceeding quota in the home file system. For example, if you try to run VSCode
workflow on Hera, it will try to install a bunch of software in the $HOME/pw
directory where quota is limited.
If you receive the warning, try the following:
1. Check whether the following directory exists on the on-prem
system where you are getting the quota error from: $HOME/pw 2. If it does, move
it to your project space and create a symlink as shown below:
Running a Jupyter workflow on a Slurm compute node
The Parallel Works ACTIVATE platform provides standard scripts, called
workflows, to complete tasks on the platform. A Jupyter workflow is available
in the ACTIVATE Marketplace. (See the Parallel Works documentation for
directions to add workflows.)
To use the Jupyter workflow on a Slurm compute node, first set a default
working directory for the session. Set the Directory To Start Jupyter Lab
GUI value to the path for your session default.
Note the directory listing in Jupyter, as compared to an ssh session:
You will also need to configure your AWS cluster with a partition, using GPU
nodes. Worker nodes in Slurm are divided into partitions based on
instance type, and are provisioned on demand when a job is submitted to the
queue. The default AWS configuration from the marketplace includes two
partitions as a base, “compute” and “batch”, as shown below:
You can either reconfigure one of these partitions with an alternate instance
type that has a GPU, or add a new partition to configure from scratch. If you
know you won’t use these starter partitions on your cluster, edit the
‘compute’ partition as needed, then remove the extra ‘batch’ partition.
Consider the following when you modify the partition:
Partition name, if you choose something other than ‘compute’.
Instance Type, selecting a GPU node appropriate for your needs. If you’re
uncertain, check the AWS documentation for a summary
of the different GPU instance families available.
Zone. Select the zone you want to provision the cluster to. This parameter is
two-pronged and configures both the region (us-east-1) and availability zone
(b). It’s prudent to stay in the us-east-1 region, as you are likely to incur
egress charges if you are passing data between your contrib storage (located
in us-east-1), and a cluster located in a different region. The zone is less
important, unless you have other storages attached to the cluster and you
need to minimize your latency. Note that AWS tends to have different instance
availability in different regions and zones, so this might take some trial
and error. Also consider that on-demand GPU availability is heavily
constrained. It’s possible that your workflow will fail to start if there’s
not enough capacity to meet your request. If that happens, either
configure your cluster in a different zone, or just try again
later.
Once you have your cluster started with the partition configured, you can edit
the workflow form to direct the job to the compute partition instead of the
controller node. This will submit a job to the Slurm scheduler and trigger a
node start.
See Configuring clusters
for complete information on configuring clusters and partitions.
Authentication to the PW system can fail for a number of
reasons.
Note
Remember that userIDs are case sensitive. Most are First.Last, with the first
letter capitalized. Use the correct format, or your login will fail.
Note
If you enter an incorrect username or PIN and token value three times during
a login attempt, your account will automatically lock for fifteen minutes.
This is a fairly common occurrence.
To resync your token:
Use ssh to login to one of the hosts such as one of Hera/Niagara/Jet, using
your RSA Token. After the host authenticates once, it will ask you wait for
the token to change.
Enter your PIN + RSA token again after the token has changed. After a
successful login your token will be re-synched and you should be able
to proceed.
Note
If you still have issues with your token, open a help
request with the subject Please check RSA token status. To expedite
troubleshooting, include the full terminal output you received when you
tried to use your token.
If the RSA token is working and you still cannot login to the PW system, check
whether your workstation is behind a firewall that is blocking access.
If you are connected to a VPN, disconnect the VPN and try again. You may also
experience connection failure if you are trying to access from outside the
United States. If you continue to experience connection issues, open a help
request.
Note
Occasionally, a valid user login attempt will receive an
Invalid name or password error. This can happen when a user token is out of
sync with the SSO system. Try logging in to an on-prem HPC system like Niagara
or Hera. If the login fails, log into the account URL to check whether “single
sign on” is working. If your login still fails, open a cloud help desk case.
Send email to rdhpcs.cloud.help@noaa.gov, with Login Error in the Subject. In
the case, include the information that you have attempted the “single sign on”
login test.
Failed to authenticate agent on remote host for on-prem HPC system login
it may be related to an issue in user’s environment.
First, ensure there is a minimum 100 MB free space in the home directory
for the PW agent file to install. If there’s enough space, perform one of the
following checks:
Remove the https_proxy setting from the .bashrc file. This will stop using
the proxy for all https traffic.
When you make proxy settings in the .bashrc file, add
exportNO_PROXY=noaa.parallel.works
This should bypass the proxy for anything on the platform.
Either of these changes should allow the agent to connect back to the platform
to create the connection.
If neither scenario applies, please open a help desk case for
assistance.
The Parallel Works cost dashboard will
show your project’s current costs, and a breakdown of how those costs were
used.
The cloud team also produces a monthly usage report
that has an overview of costs for all cloud projects. Those reports are useful
for portfolio managers (PfM) and principal investigators (PI) to monitor
multiple projects in a single spreadsheet.
Occasionally the RDHPCS cloud team and other cloud users give presentations
that we record. These presentations are available for RDHPCS user consumption
on an RDHPCS internal site.
Send an email to rdhpcs.cloud.help@noaa.gov. Your email automatically
generates a case in the OTRS system. The OTRS system does not have the
option to set a priority level. Typically, there is a response
within two hours.
To close a project, email rdhpcs.aim.help@noaa.gov to create an AIM
ticket. Make sure that all data are migrated, and custom snapshots are
removed before you send the request to the AIM. If you do not need
data from the referenced project, be sure to include that information
in the ticket so that the support can drop the storage services.
How do I connect the controller node from outside the network?
What are the project allocation usage limits and actions?
Used allocation at 85% of the budget allocation:
When an existing project usage reaches 85% of the allocation, the
Parallel Works [PW] platform sends an email message to principal
investigator [PI], tech lead [TL] and admin staff.
Users can continue to start new clusters and continue the
currently running clusters.
A warning message appears on the PW compute dashboard
against the project.
PI should work with the allocation committee on
remediation efforts.
Used allocation at 90% of the budget allocation:
When an existing project usage reaches 90% of the allocation, the
Parallel Works platform sends an email message to principal
investigator, tech lead and admin staff.
Users can no longer start a new cluster and may continue the
currently running clusters, but no new jobs can be started.
Users must move data from the contrib and object storage to
on-premise storage.
A “Freeze” message appears on the PW compute dashboard against the
project.
PI should work with the allocation committee on remediation
efforts.
Used allocation at 95% of the budget allocation:
When an existing project usage reaches 95% of the allocation, the
Parallel Works platform sends an email message to principal
investigator, tech lead and admin staff.
Terminate and remove all computing/cluster resources.
Data at buckets will remain available as will data in
/contrib. However, only data in the object storage will
be directly available to users.
Notify all affected users, PI, Tech Lead, Accounting Lead
via email that all resources have been removed.
Disable the project.
Used allocation at 99.5% of the budget allocation:
Manually remove the project resources.
Notify COR/ACORS, PI and Tech Lead, Accounting Lead via
email all resources have been removed.
How do I request a project allocation or an allocation increase?
RDHPCS System compute allocations are determined by the RDHPCS
Allocation Committee (AC). To make a request, complete the
Allocation Request Form
After you complete the form, create a
Cloud help ticket to track the issue. Send email to
rdhpcs.cloud.help@noaa.gov, copy to gonzalo.lassally@noaa.gov, using
Cloud Allocation Request in the subject line.
A cluster owner can set up to send an email notification
based on the number of hours/days a cluster is up. You can
enable the notification from the Parallel Works resource
configuration page and apply it on a live cluster or set as
a standard setting on a resource configuration, so that will
take effect on clusters started using the configuration.
Your project’s permanent storage [AWS s3 bucket, Azure’s
Block blob storage, or GCP’s bucket] can be mounted on an
active cluster, or set to attach a bucket when starting a
cluster, as a standard setting on a resource configuration.
Having the permanent storage mounted on a cluster allows a
user to copy files from contrib or lustre to a permanent
storage using familiar Linux commands.
Sharing storage between the projects, enhanced capacity, and configuration
Note that the permanent storage and persistent storage must
be started separately before it can be attached to a
cluster. Storage resources can be started from the Compute
dashboard, Storage Resources section.
If you are a user belonging to more than one project, now
you can share storage between the projects. You can attach
other project storage from the resource configuration page.
Note that, a persistent lustre file system must be started
separately before it can be attached to a cluster.
Users may create as many permanent object storage [AWS S3
bucket, Azure’s block blob storage, and GCP’s bucket], and
lustre file system [ephemeral and persistent storage] on
your Cloud platform.
Open up the resource name definition, click on the _JSON
tab, add a parameter “root_size” with a value in the
cluster_config section, that fits your need, save and
restart the cluster.
In the below example, the root disk size is set to 256 GiB
If you’re running a workflow for the first time, you will
need to add it to your account first. From the Parallel
Works main page, click the workflow Marketplace button
located on the top right menu bar, looks like an Earth icon.
What different storage types and costs are available on the PW platform?
There are three types of storage available on a cluster,
those are lustre, object storage [ for backup & restore,
output files], and contrib file system [a project’s custom
software library].
Lustre file system
Parallel file system, available as ephemeral, and persistent
storage on the AWS and Azure cloud platforms. You can
create as many lustre file systems as you want from the PW
Storage tab by selecting the “add storage” button.
Cost for lustre storage can be found at the definition
page when creating storage.
Lustre file system can be attached and mounted on a
cluster. It is accessible only from an active cluster.
Bucket/Block blob storage
A bucket or Block blob storage is a container for objects.
An object is a file and any metadata that describes that
file.
Use cases, such as data lakes, websites, mobile
applications, backup and restore, archive, enterprise
applications, IoT devices, and big data analytics.
On AWS, and GCP, the storage is called S3 bucket, and
bucket respectively, whereas in Azure, the storage used is
Block blob storage, which functions as a bucket and an NFS
storage.
AWS S3 bucket pricing [us-east-1]: $0.021 per GB per
Month. The cost is calculated based on the storage usage.
For example, 1 PB storage/month will cost $21,000.
Azure object storage and contrib file system are the
storage type. The pricing for the first 50 terabyte (TB) /
month is $0.15 per GB per Month. The cost is calculated
based on the storage usage. See: Azure Pricing
Google cloud bucket storage pricing: Standard storage
cost: $0.20 per GB per Month. The cost is calculated based
on the storage usage. See: Cloud Bucket pricing
Projects using AWS, and GCP platforms can create as many
buckets as needed, and mount on a cluster. Project’s
default bucket is accessible from the public domain using
the keys.
Contrib file system
Contrib file system concept is similar to on-prem contrib,
used to store files for team collaboration. This storage can
be used to install custom libraries or user scripts.
AWS Contrib storage [efs] pricing [us-east-1]: $0.30 per
GB per Month. The cost is calculated based on the storage
usage. See: AWS Pricing
Azure contrib cost is explained above in the block blob
storage section.
Both AWS and Azure charge based on the usage, as a
pay-as-you-go model like your electric bill. GCP charges
on allocated storage, so whether the storage is used or not,
the project pays for the provisioned capacity.
The default provisioned capacity of Google Cloud contrib
file system is 2.5 TiB, costs $768.00 per month. The contrib
volume can be removed from a project by request, email to
rdhpcs.cloud.help@noaa.gov [ OTRS ticket on RDHPCS help.]
Traffic between regions will typically have a $0.09 per GB
charge for the egress of both the source and destination.
Traffic between services in the same region is charged at
$0.01 per GB for all four flows.
AWS’s monthly data transfer costs for outbound data to the
public internet are $0.09 per GB for the first 10 TB,
dropping to $0.085 per GB for the next 40 GB, $0.07 per GB
for the next 100 TB, and $. 05/GB greater than 150 TB.
P5 [Nvidia H100]: available in the following availability zones
us-east-1f
us-east-2c
us-east-2a
us-east-2b
P4 [Nvidia A100]: available in the following availability zones:
us-east-1c
us-east-1b
us-east-1a
us-east-2a
us-east-2b
P3 [Nvidia Tesla V100] : available in the following availability zones:
us-east-1d
us-east-1b
us-east-1e
us-east-1c
us-east-1a
us-east-1f
us-east-2c
us-east-2b
us-east-2a
G3 [Nvidia Tesla M60] (graphics processing) available in the following
availability zones:
us-east-1e
us-east-1c
us-east-1b
us-east-1f
us-east-1d
us-east-1a
G4ad [AMD Radeon Pro V520] for graphics processing available in the
following availability zones:
us-east-1c
us-east-1a
us-east-1b
us-east-1d
us-east-2a
us-east-2b
us-east-2c
G5 [Nvidia A10G Tensor Core] for graphics and machine learning, available in
the following availability zones:
us-east-1d
us-east-1b
us-east-1c
us-east-1a
us-east-1f
us-east-2b
us-east-2c
us-east-2a.
G6 [Nvidia L4 Tensor Cores] for graphics and machine learning available in
the following availability zones:
us-east-1a
us-east-1c
us-east-1b
us-east-1d
us-east-2c
us-east-2a
us-east-2b
Note
We currently have a quota for 2,400 vCPUs. On-demand availability depends on
availability at a given time in the market, and is outside our control.
Users may want to try different availability zones to acquire GPUs.
Why does the remote desktop show multiple xterm terminals, and/or xclocks?
This issue can be caused by an error in the $HOME/.vnc/xstartup file.
To correct it, edit the file, keeping the following lines:
If user doesn’t want xclock or the terminal to start automatically, run the
following to reset:
touch~/.Xclients
A PW session that shows “Running” isn’t accessible and there’s no log error
This typically occurs when the system runs out of resources, usually due
to an out-of-memory situation. The display rolls back to requested since the
instance is no longer reachable, and it’s waiting for status updates from the
instance. Sometimes the out-of-memory killer will kick in and clean up some
processes to allow the system to continue functioning, but this event isn’t
guaranteed to clean up quickly, or to leave the system in a functional state
after cleanup when it does run.
To work around this, if your workflow allows it,
increase the size of the instance, or add a compute
partition and send the work off to worker nodes.
How do I get access to the Parallel Works Platform?
Pre-requisite for getting an account access to the Parallel Works
platform is to have a NOAA email address.
The next step is to request access to a project and RSA token from
the “Account Management Home”.
Access AIM to request a project and RSA token. No CAC is necessary
to access the Parallel Works platform.
From the Account Management Home, click on “Click here to
Request Access to a Project” and select a project the list of
projects.
The drop-down list is long. You can type the first character
to move the cursor towards your project name.
The nomenclature on cloud project names are, AWS projects
start with letters “ca-“, Azure projects start with letters
“cz-“, and GCP projects with “cg-”
Example cloud project names are: ca-budget-test: This is the
AWS platform project used for cost specific tests.
cz-budget-test: This is the Azure platform project used for
cost specific tests. cg-budget-test: This is the GCP
platform project used for cost specific tests.
After selecting the project, click “Submit Request”.
Click the link: “Make a request for an RSA token”
After your request is approved, you can login on to the
platform.
How is a new user added to a project on Parallel Works?
If you would like to join an existing project, ask your PI,
TL, or Portfolio manager the project name. The cloud project
name starts like ca, cz, or cg implying AWS, Azure, or
Google platform, and followed by the project name. An
example, ca-budget-test implies that project budget-test
runs from the AWS platform.
Use the AIM link and click on”Request new access to a project” to add
yourself to a project.
Access to the project is contingent on PI’s approval.
To set up your project in Parallel Works follow the
below steps.
Get your project’s allocation approved by NOAA RDHPCS
allocation committee.
If you are unsure of an allocation amount for your project,
create a cloud help desk ticket by emailing to
rdhpcs.cloud.help@noaa.gov to schedule a meeting. An SME can
help you translate your business case into an allocation
estimate.
Email to POC for allocation approval.
Create an AIM ticket to create your project by
emailing to the AIM administrator.
A Portfolio Manager or Principal Investigator can send a
request to AIM administrator rdhpcs.aim.help@noaa.gov, by
providing the following information:
Project short name. Please provide in this format: <cloudplatformabbreviation>-<projectname>
Example ca-epic stands for AWS Epic, cz-epic for Azure epic,
and cg-epic for Google cloud Epic.
Brief description of your project.
Portfolio name.
Principal Investigator [PI] name.
Technical lead name [TL]. In some case, a project’s PI
and TL may be the same person. If that is the case, repeat
the name.
Allocation amount [optional].
Setting up a project in AIM can take two days.
AIM system administrator creates a cloud help desk ticket to
create a project on the Parallel Works platform.
Setting up a project in Parallel Works can take a day. Upon
the project creation, the AIM administrator will email back
with the project status.
Read the cloud FAQ to learn on adding users to a project.
What is the certified browser for Parallel Works Platform?
Google Chrome browser.
How do I handle a Login error - Invalid username or password?
This error can happen when a user token is out of sync with the single sign on
system. Try logging in to an on-prem HPC system like Niagara or Hera, then try
the Parallel Works system. If the login fails, log into the <account URL to check whether
“single sign on” is working. If your login still fails, open a cloud help desk
case. Send email to rdhpcs.cloud.help@noaa.gov, with Login Error in the
Subject. In this case, include the information that you have attempted the
“single sign on” login test.
How do I access on-prem HPS Systems from Parallel Works?
Parallel Works is working on seamless authentication with on-prem HPC
systems.
Note
The following access method does not work on Gaea.
Follow the steps to access other HPC systems.
From the login portal, click the user Name. Select Account
from the drop down list.
Click the Authentication tab.
Click on the “SSH Keys” line.
Copy the “Key” from the “User Workspace”.
Append the public SSH key in the on-prem HPC system’s controller
node’s ~/.ssh/authorized_keys file. Save and exit the file.
Repeat this process on all on-prem HPC systems’ controller nodes
to establish connections from Parallel Works.
Subscribe the default template of HPC systems from the Parallel
Works Marketplace
From the login portal, click on the user Name. Select
“MARKETPLACE from the drop down list box.
Click on the Fork sign and click the Fork button when prompted.
Exit the page.
Access allowed countries
USA, India, Mexico, China, Canada, Taiwan, Ethiopia, France, Chile,
Greece, United Kingdom, Korea, Spain, Brazil, Malaysia, Colombia,
Finland, Lebanon, Denmark, Palestinian Territory Occupied,
Netherlands, Japan, and Estonia.
Warning messages from the on-prem system about exceeding quota
Question: I am getting warning messages from the on-prem system about
exceeding my quota in my home filesystem when I try to run a workflow. What
should I do?
You may run into file quota issues when you try
to run a workflow on an on-prem system.
For example, if you try to run VSCode workflow on Hera, it will try to install
a bunch of software in the $HOME/pw directory where you have a very limited
quota. To address this issue follow the steps below:
1. Check whether the following directory exists on the on-prem system where you
are getting the quota error from:
$HOME/pw
If it does, move it to your project space and create a symlink as shown
below:
You can estimate an hourly cost of your experiment’s from
the Parallel Works(PW) platform. After login on the
platform, click on the “Resources” tab, and double click on
your resource definition. There is a definition tab, where
when you update the required compute and lustre file system
size configuration, the form dynamically shows an hourly
estimate.
You can derive an estimated cost of a single experiment by
multiplying the run time with the hourly cost.
For example, if the hourly estimate is $10, and your
experiment would run for 2 hours then the estimated cost
for your experiment would be $10 multiplied by 2, equals
to $20.
You can derive project allocation cost by multiplying the
run time cost with the number of runs required to complete
the project.
For example, if your project would require a model run 100
times, then multiply that number by a single run cost, the
cost would be 100x$20 = $2,000.00.
Note that there are costs associated with maintaining your
project, like contrib file system, object storage to store
backup, and egress.
How do I find a real time cost estimate of my session?
Cloud vendors publish the cost once every 24 hours, that is
not an adequate measure in an HPC environment. PW Cost
dashboard offers an almost real time estimate of your
session.
Real time estimate is refreshed every 5 minutes on the Cost
dashboard. Click on the Cost link from your PW landing page.
Under the “Time Filter”, choose the second drop down box and
select the value “RT” [Real time]. Make sure the “User
Filter” section has your name. The page automatically
refreshes with the cost details.
An example, your project requests a dedicated number of HPC
compute nodes or has an HPC system reservation for some
number of HPC compute nodes. Let’s say that the
dedicated/reserved nodes have 200 cores and the length of
the dedication/reservation is 1 week (7 days), then the
core-hours used would be 33,600 core-hours (200 cores * 24
hrs/day * 7 days).
GCP’s GPU to vCPUs conversation can be found here
In GCP, two vCPUs makes one physical core.
So, a2-highgpu-1 has 12 vCPUs that means 6 physical core. If
your job is taking 4 hours to complete so that means the
number of core hours = number of nodes x number of hour x
number of cores = 1 x 4 x 6 = 24 core hours.
PW’s cost dashboard is a good tool to find unit cost, and
extrapolate it to estimate usage for PoP.
How do I access the head node from the Parallel Works [PW] web interface?
You can connect to the head node from the PW portal, or
Xterm window if you have added your public key in the
resource definition prior to launching a cluster.
If you have not added a public key at the time of launching
a cluster, you can login to the head node by IDE and update
the public key in ~/.ssh/authorized_keys file.
From the PW “Compute” dashboard, click on your name with an IP
address and make a note of it. You can also get the head node IP
address by clicking the i icon of the Resource monitor.
Click on the IDE link located on the top right side of
the PW interface to launch a new terminal.
From the menu option “Terminal”, click on the “New
Terminal” link.
From the new terminal, type
$ssh<PastetheusernamewithIPaddress>
and press the enter key.
This will let you login to the head node from the PW
interface.
Example:
$sshFirst.Last@54.174.136.76
Warning: Permanently added ‘54.174.136.76’ (ECDSA) to the
list of known hosts.
You can use the toggle button to restore lustre file system
setting. You can also resize the LFS at a chunk size
multiple of 2.8 TB.
If you’re running a workflow for the first time, you will
need to add it to your account first. From the PW main page,
click the workflow Marketplace button on the top menu bar.
This button should be on the right side of the screen, and
looks like an Earth icon.
It is possible to ssh to compute nodes in your cluster from
the head node by using the node’s hostname. You do not
necessarily need to have a job running on the node, but it
does need to be in a powered on state (most resource
configurations suspend compute nodes after a period of
inactivity)
Use sinfo` or squeue to view active nodes:
$ sinfo
PARTITION AVAIL TIMELIMIT NODES STATE NODELIST
compute* up infinite 4 idle~ compute-dy-c5n18xlarge-[2-5]
compute* up infinite 1 mix compute-dy-c5n18xlarge-1
$ squeue
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
2 compute bash Matt.Lon R 0:33 1 compute-dy-c5n18xlarge-1
How do I request a new feature or report feedback?
You may request a new feature on the PW platform or provide
a feedback to the NOAA RDHPCS leadership using the link TBD
How can I address an authentication issue on the Parallel Works [PW] login?
Authentication to the PW system can be due to an expired RSA Token or
inconsistent account status in the PW system. If you have not accessed
on-prem HPC system last 30 days, it is likely your RSA token is
expired, in such cases open a help request for
assistance.
Note
Remember that userIDs are case sensitive. Most user names are
First.Last, with the first and last name capitalized,
and not first.last! Be sure to use the correct format.
To verify RSA Token issue, follow the steps:
If you enter an incorrect username or PIN and token value
three times during a login attempt, your account will
automatically lock for fifteen minutes. This is a fairly
common occurrence. Wait for 15 minutes and resync as
follows:
Use ssh to login to one of the hosts such as one of
Hera/Niagara/Jet, using your RSA Token.
After the host authenticates once, it will ask you wait
for the token to change. Enter your PIN + RSA token again
after the token has changed.
After a successful login your token will be resynched and
you should be able to proceed.
If you are still experiencing issues with your token, open a
help request with the title Please check RSA
token status. To expedite troubleshooting, please include the full
terminal output you received when you tried to use your token.
If RSA token is working and still unable to login to the PW system,
check whether your workstation is behind a firewall that is blocking
access.
If you are connected to a VPN, disconnect the VPN and try again.
You may also experience connection failure if you are trying to access
from outside the United States.
If you continue to experience connection issues, open a help
request.
There are several resource types that are part of a user
cluster.
We are working on adding more clarity on the resource cost
type naming and cost. Broadly, the following cost types are
explained below.
UnknownUsageType:
Network costs related virtual private network. See
the Google CSP
and Amazon AWS
documentation for more information.
Other Node:
Controller node cost.
Storage-BASIC_SSD:
On the Google cloud, “contrib” volume billing is
based on the allocated storage. Contrib volume allocated storage
2.5TB. On other cloud platforms, the cost is based on the storage
used.
The default CSP resource definition in the platform is
fv3gfs model at 768 resolution 48-hours best performance
optimized benchmark configuration.
From the PW platform top ribbon, click on the “Resources”
link.
Click on the edit button of a PW v2 cluster [aka elastic
clusters, CSP slurm] resource definition.
By default, there are two partitions, “Compute” and “batch”
as you can see on the page. You can change the number of
partitions based on your workflow.
From the resource definition page, navigate to the compute
partition.
Max Node Amount parameter is the maximum number of nodes in
a partition. You can change that value to a non-zero number
to resize the compute partition size.
You may remove the batch partition by clicking on the
“Remove Partition” button. You can also edit the value for
Max Node Count parameter to resize this partition.
Lustre filesystem is an expensive resource. You can disable
the filesystem or resize it. The default lustre filesystem
size is about 14TiB.
Keeping the bucket and cluster within the same region to lower latency and Cost
Moving data between regions within a cloud platform will incur cost.
For example, if the cluster and the bucket you were copying to exist in
different regions, the cloud provider will charge for every bite that
leaves.
It is possible to provision your own buckets from the PW
platform storage menu. This would also have the benefit of reducing
the overall time you spend transferring data, since it has less
distance to travel. If you have any further questions about this,
please open a help desk ticket. We’d also be happy to work with you.
Join one of the cloud office hours to ask questions.
How do I create a custom [AMI, Snapshot, Boot disk, or machine] image?
If a user finds specific packages are not present in the
base boot image, the user can add it by creating own custom
image. Follow the steps to create a custom snapshot.
After a snapshot is created, the next step is to reference
it in the cluster Resource configuration.
From the Parallel Works banner, click on the “Compute” tab,
and double click on the resource link to edit it.
From the Resource Definition page, look for the “Controller
Image” name. Select your newly created custom snapshot name
from the drop down list box.
Scroll down the page to the partition section. Change the
value of “Elastic Image” to your custom image. If you have
more than one partitions, then change “Elastic Image” value
to your custom image name.
Click on the “Save Resource” button located on the top right
of the page.
Now launch a new cluster using the custom snapshot from the
“Compute” page. After the cluster is up, verify the
existence of custom installed packages.
How can I automatically find the hostname of a cluster?
By default, the host names are always going to be different
each time you start a cluster.
You can find CSP information using the PW_CSP variable, as
in the example:
$echo$PW_CSP
google
There are a few other PW_* vars that you may find useful:
ssh tunnels are a useful way to connect to services running
on the head node when they aren’t exposed to the internet.
The Jupyterlab and R workflows available on the PW platform
utilize ssh tunnels to allow you to connect to their
respective web services from your local machine’s web
browser.
Before setting up an ssh tunnel, it is probably a good idea
to verify standard ssh connectivity to your cluster (see how
do I connect to my cluster). Once connectivity has been
verified, an ssh tunnel can be setup like so:
In this example, I am tunneling port 8888 from the host
‘userid-gclustera2highgpu1g-00012-controller’ to port 8888
on my local machine. This lets me direct my browser to the
URL ‘localhost:8888’ and see the page being served by the
remote machine over that port.
How do I turn off Lustre filesystem from the cluster?
From the Resources tab, select a configuration and click the
edit link.
Scroll down the configuration page to the “Lustre file
system” section. Use the toggle button to “No” to turn off
the lustre file system [LFS]. This setting lets you create a
cluster without a lustre file system.
Running conda init bash will setup the ~/.bashrc file so it
will activate the default environment when you login.
If you want to use a different env than what is loaded by
default, you could run this to change the activation:
$echo"conda activate <name_of_env>">>~/.bashrc
Since your .bashrc shouldn’t really change much, it might be
ideal to set the file up once and then back it up to your
contrib (somewhere like
/contrib/First.Last/home/.bashrc), then your user boot
script could simply do:
If your cluster requires lustre file system [ephemeral or
persistent], or additional storage for backup, start at the
“Storage” section and then use the “Resource” section.
You can enable this functionality on your active or new
cluster. This setup will help you send a reminder when your
cluster is up a predefined number of hours.
You can turn on this functionality when creating a new
resource name. When you click on the “add resource” button
under the “Resource”, you find the run time alert option.
You can enable this functionality on a running cluster, by
navigating to the “properties” tab of your resource name
under the “Resource” tab.
Missing user directory in the group’s contrib volume
A user directory on a group’s contrib volume can only be
created by an owner of a cluster, as the cluster owner only
has “su” access privilege. Follow the steps to create a
directory on contrib.
Start a cluster. Only the owner has the sudo su
privilege to create a directory on contrib volume.
Start a cluster, login to the controller node, and
create your directory on the contrib volume.
Start a cluster by clicking on the start/stop button
When your cluster is up, it shows your name with an IP
address. Click on this link that copies username and IP
address to the clipboard.
Click on the IDE button located top right on the ribbon.
Click on the ‘Terminal’ link and select a ‘New Terminal’
SSH into the controller node by pasting the login
information from the clipboard.
$ ssh User.Name<IP address>
List your user name and group:
$ id
uid=12345(User.Id) gid=1234(grp)
groups=1234(grp)
context=unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023
$ sudo su -
[root@awsv22-50 ~]$
[root@awsv22-50 ~]$ cd /contrib
[root@awsv22-50 contrib]$
[root@awsv22-50 contrib]$ mkdir User.Id
[root@awsv22-50 contrib]$ chown User.Id:grp User.Id
[root@awsv22-50 contrib]$ ls -l
drwxr-xr-x. 2 User.Id grp 6 May 12 13:06 User.Id
Your directory with access permission is now complete.
Your directory is now accessible from your group’s clusters.
Contrib is a permanent storage for your group.
You may shutdown the cluster if the purpose was to create
your contrib directory.
Why does the owner’s home directory differ from the shared users’ directory?
Every cluster is set up where the owner of it has an
ephemeral home directory that isn’t linked from contrib, but
on multi-user clusters, all additional users that are added
do get home linked from contrib.
The projects using Google cloud can request to drop their
contrib volume to save cost. Google charges on provisioned
nfs capacity, whereas others charge on the used storage.
So when people start clusters in some cases they may not
have a contrib dir so owners don’t want to link home
directory to their contrib directory.
What are “Compute” and “Batch” sections in a cluster definition?
The sections “Compute” and “Batch” are partitions. You may
change the partition name at the name field to fit your
naming convention. The cluster can have many partitions with
different images and instance types, and can be manipulated
at the “Code” tab.
You may resize the partitions by updating “max_node_num”, or
remove batch partition to fit your model requirements.
In this case, there are two nodes that are on and idle
(userid-gcp-00141-2-[0001-0002]) You can ignore the
nodes with a ~ next to their state. That means they are
currently powered off.
How to sudo in as root or a role account on a cluster?
The owner of a cluster can sudo in as root and grant sudo
privilege to the project members by adding their user id in
the sudoers file.
Only the named cluster owner can become root. If the cluster
owner is currently su’d as another user, they will need to
switch back to their regular account before becoming root.
Sudoers file is: ls -l /etc/sudoers
Other project members’ user id can be found at /etc/passwd
file. You may update this file manually or by bootstrap
script, the change is taken effect immediately.
A role account is a shared workspace for project members on
a cluster. By su’d to a role account, project members can
manage and monitor their jobs.
There are two settings that must be enabled prior on a
resource definition in order to create a role account in a
cluster. On the resource definition page, select the “Multi
User” tab to “Yes”, and from the “Sharing” tab, check the
“View and Edit” button.
The command to find the name of your project’s role account
from /etc/passwd is.
By default bootstrap script changes only runs on the MASTER
node of a cluster.
To run on all nodes (master and compute) have your user
script first line be ALLNODES.
The following example script installs a few packages, and
reset the dwell time from 5 minutes to an hour on the
controller and compute nodes. Do not add any comments on the
bootstrap script, as that would cause in code execution
failure.
ALLNODES
set+xset-e
echo"Starting User Bootstrap at $(date)"
sudorm-fr/var/cache/yum/\*
sudoyumcleanall
sudoyumgroupsmarkinstall"Development Tools"-y
sudoyumgroupinstall-y"Development Tools"
sudoyum--setopt=tsflags='nodocs'\--setopt=override_install_langs=en_US.utf8\--skip-broken\install-yawsclibison-develbyaccbzip2-devel\ca-certificatescshcurldoxygenemacsexpat-develfile\flexgitgitflowgit-lfsglibc-utilsgnupggtk2-develksh\lesslibcurl-devellibX11-devellibxml2-devellynx\lz4-develkernel-develmakeman-dbnanoncurses-devel\neditopenssh-clientsopenssh-serveropenssl-develpango\pkgconfigpythonpython3python-develpython3-devel\python2-asn1cryptopycairo-develpygobject2\pygobject2-codegenpython-boto3python-botocore\pygtksourceview-develpygtk2-develpygtksourceview-devel\python2-netcdf4python2-numpypython36-numpy\python2-pyyamlpyOpenSSLpython36-pyOpenSSLPyYAML\python-requestspython36-requestspython-s3transfer\python2-s3transferscipypython36-scipypython-urllib3\python36-urllib3redhat-lsb-corepython3-pycurlscreen\snappy-develsquashfs-toolsswigtcltcshtexinfo\texline-latex\*tkunzipvimwget
echo"USER=${USER}"echo"group=$(id-gn)"echo"groups=$(id-Gn)"
sudosed-i's/SuspendTime=300/SuspendTime=3600/g'/mnt/shared/etc/slurm/slurm.conf
if[$HOSTNAME==mgmt\*];thensudoscontrolreconfigure
fi
sudosacctmgraddclustercluster-i
sudosystemctlrestartslurmdbd
sudoscontrolreconfig
echo"Finished User Bootstrap at $(date)"
How can I configure a CentOS Cluster to use Rocky 8 (latest)
If you have already made extensive modifications to your cluster’s definition,
you may prefer to revert the required settings by hand without loading a config
from the Marketplace. There are two primary settings that need to be updated,
the OS image Rocky 8 (latest), and the /apps disk snapshot. Keep in mind
that the OS image will need to be set on the controller and every partition you
have configured on the cluster.
From the CentOS cluster configuration, find the Image* dropdown under the
Controller settings and select the image.
Follow the same procedure on each compute partition to select the
Rocky 8 (latest) image under the ElasticImage* dropdown:
The software and modules under /apps were built specifically for their
target operating systems, so the Rocky 8 disk also needs to be selected.
Click Save Changes.
We recommend that you also replace any existing CentOS 7 based persistent
Lustre resources to use Rocky 8 as well. The suggested method to do this is to
duplicate your existing storage configuration, and copy your data to the new
Lustre, either by copying directly from the old storage, or by syncing it with
a bucket. Once you have verified that all of your data has been migrated, you
can shut down the old file system. If your data is backed up to a bucket
already, you can also re-provision your existing Lustre configuration and
re-sync the data.
Locate your project’s access and secret keys and access instructions
From PW’s home page, inside the “Storage Resources” section, locate
your project’s bucket. Click on the key icon to find the bucket name,
keys and sample command to access the bucket.
Azure azcopy install on an on-prem system. Files transfer to a cloud bucket
Over time, the AzCopy download link will point to new versions of
AzCopy. If your script downloads AzCopy, the script might stop working
if a newer version of AzCopy modifies features that your script
depends upon.
To avoid these issues, obtain a static (unchanging) link to the
current version of AzCopy. That way, your script downloads the same
exact version of AzCopy each time that it runs.
This will leave the azcopy tool in the current directory, which
you can then copy to any directory.
Locate your project’s credentials and access instructions
From PW’s home page, inside the “Storage Resources” section locate
your project’s bucket. Click on the key icon to find the bucket name,
keys and sample command to access the bucket.
Please refer to the AzCopy guide for information on how to use AzCopy.
GCP gcloud install on an on-prem, and files transfer to a cloud bucket
Add the gcloud CLI to your path. Run the installation script from the
root of the folder you extracted to using the following command:
$./google-cloud-sdk/install.sh
Start a new terminal and check gcloud tool in the access path:
$whichgcloud
~/google-cloud-sdk/bin/gcloud
From PW’s home page, inside the “Storage Resources” section locate
your project’s bucket. Click on the key icon to find the bucket name,
keys and sample command to access the bucket.
The recommended system for data transfers to/from NOAA RDHPCS systems
is the Niagara Untrusted DTN especially if the data transfers is being
done from/to the HPSS system.
If data is on Hera, the user will have to use 2-copy transfers, by
first transferring to Niagara and then pulling the data from the
Cloud, or use the utilities mentioned in the next section.
AWS CLI, available on Hera/Jet/Niagara, can be used on RDHPCS systems
to push and pull data from the S3 buckets. Please load the
“aws-utils” module.
moduleloadaws-utils
How do I use scp from a Remote Machine to copy to a bucket?
1. Create a cloud cluster configuration, and in the attached storage
section include bucket storage, note the mounted file system name
given for the bucket.
Azure uses the azcopy utility to push and pull data into their cloud
object store buckets. The azcopy utility can be installed standalone
or as part of the larger az cli. The “azcopy” command can run either
from the user’s local machine or the RDHPCS systems, such as Niagara,
mentioned in the next section. The gsutil utility is already
preinstalled on clusters launched through Parallel Works.
The azcopy utility becomes available on RDHPCS systems once the module
“azure-utils” has been loaded. To do that, run the command:
moduleloadazure-utils
It can be installed on your local machine/desktop by installing the
binary at the link below as documented below:
wget-Oazcopy.tgzhttps://aka.ms/downloadazcopy-v10-linux
tarxzvfazcopy.tgz
# add the azcopy directory to your path or copy the “azcopy”
executabletoadesiredlocationexportPATH=$PATH:$PWD/azcopy_linux_amd64_10.9.0</pre>
GCP command line utility is gsutil. PW OS image has the GCP utility
“gsutil’ installed. Follow the instructions from the link to copy
files to Google bucket.
How do I access Azure Blob from a Remote Machine?
The following instruction uses the long term access key available
from the PW file explorer: storage/project keys section, which is
going to be discontinued. We recommend using the short term access key
from the home:storage bucket as suggested in the link above.
Obtain the Blob bucket keys from the PW platform, as mentioned in the
section below, getting project keys. Then set the following
environment variables based on the keys there:
Obtain the Azure object store keys from the PW platform, as mentioned
in the section below, getting project keys. Then set the following
environment variables and activation command based on the keys there
(you should be able to copy and paste these). Once you run this once
on a host machine, it should store the credentials in your home
directory:
# project-specific credentialsexportAZURE_CLIENT_ID=<projectclientid>
exportAZURE_TENANT_ID=<projecttenantid>
exportAZCOPY_SPA_CLIENT_SECRET=<projectsecret>
# activate the project-specific keys for azcopy
azcopylogin--service-principal--application-id$AZURE_CLIENT_ID--tenant-id$AZURE_TENANT_ID
If following messages return at the login, the issue is likely from
the key ring propagation bug. In that case, type the following command and
re-try azcopy login.
Azure object store works differently than AWS and GCP in that objects
pushed or pulled into the object store container will immediately show
up in the /contrib directory on the clusters (ie the object store is
NFS mounted to /contrib). Buckets can only be used based on the user’s
assigned project space. Create sub-directories with the user’s
username at the top level.
Data Transfer between Compute Node and Azure Blob
The Azure blob storage is slightly different from AWS and GCP
clusters in that the blob storage automatically mounts directly to the
cluster’s /contrib directory. This means that as soon as files are
uploaded to the Azure blob storage using azcopy command, these files
directly appear in the NFS mounted /contrib directory without any
additional data transfer steps. The reverse is true as well in that
when files are placed into a cluster’s /contrib directory, these files
will be available for immediate download using azcopy on remote hosts.
When a file is copied to Azure blob, the ownership is changed to “nobody:root”.
Change the ownership of the file using “chown” command to access the file(s).
Example:
How do I get AMD processor resources configuration?
AMD processor based instances or VMs are relatively less
expensive than Intel. Cloud services providers have
allocated processor quota on the availability zones where
AMD processors are concentrated. In Parallel Works, the AMD
configurations are created pointing to these availability
zones.
To create an AMD resource configuration, follow the steps
explained in the link below. The instructions will direct
you to restore configuration, then choose the AMD Config
option from the list.
You may resize the cluster size by adjusting max node count,
and enable or disable lustre as appropriate to your model.
You can restore a configuration by navigating to the
“Resources” tab, double click on a resource name, shows up
it’s “Definition” page. Scroll down on the page and click on
the “(restore configuration)” link, then select a resource
configuration from the drop down list, click on the
“Restore” button, and then click “Save Resource”.
How do I transfer files from one project to another?
You may use Globus file transfer or the following method to transfer files.
If you are a member of a source and target cloud projects then
transferring of files is easy:
Create a small size cluster definition with just one node in the
compute batch. From the resource definition, click on the “Add a
Attached storage” button then add both source and destination
buckets by selecting “Shared Persistent Storages” option from the
drop down list box one at a time. Make sure the bucket’s mount
point names are easily distinguishable, for example /source and
/destination. You do not need a lustre file system in this
cluster. Save the definition.
Start a cluster using the saved definition, and when the cluster is
up, ssh into the controller node.
Change ownership to root to copy all project members files:
sudo-
Use the Linux “cp” recursive command, copy files from the source
contrib and bucket to the target bucket.
By “default instance/vm type” we refer to the instance/vm
types in a pre-created cluster configuration. This
configuration is included when an account is first setup,
and also when creating a new configuration by selecting a
configuration from the “Restore Configuration” link at the
resource definition page.
The Lustre solution on AWS uses their FSx for Lustre service on the
backend. The default deployment type we use is ‘scratch_2’. The
‘persistent’ options are typically aimed at favoring data resilience
over performance, although ‘persistent_2’ does let you specify a
throughput tier. Note that the ‘scratch’ and ‘persistent’ deployment
types in this context are AWS terminology, and are not related to PW’s
definition of ‘persistent’ or ‘ephemeral’ Lustre configurations. You
can choose whatever deployment type you prefer and configure it as
‘persistent’ or ‘ephemeral’ in PW.
scratch_2 FSx file systems are sized in 1.2TB increments, so you’ll
want to set the capacity to ‘2400 GB’ if you stick to the scratch_2
deployment type. The estimated cost of the config JSON shown below is
showing as $0.46 per hour for me. Different deployment types might
have different size increments.
Copy files from a public AWS bucket without authentication keys
You can use the aws CLI on a Cloud cluster by
adding an option to the command that skips authentication. This method should
work for public buckets. It has also worked to copy a file to a personal cluster.
Edit the command as follows:
aws--no-sign-requests3...
# list files[First.Last@abcd8-173~]$aws--no-sign-requests3lss3://noaa-nws-global-pds
PREdata/
PREfix/
2024-11-2216:36:3137683index.html
# copy a file
$aws--no-sign-requests3cps3://noaa-nws-global-pds/index.html./index.html
download:s3://noaa-nws-global-pds/index.htmlto./index.html
We’re in the process of integrating Azure’s own managed Lustre file
system service to the platform, but for now it is deployed similarly
to Googles. This also means that the cost of Lustre on Azure is
significantly higher than it will be on AWS.
On Azure, the usable capacity of the file system will mostly
be determined by the number of OSS nodes you use, and the type of
instances you select. We default to ‘Standard_D64ds_v4’ instances for
Azure Lustre. Regardless of the node size you choose, you will want to
stick to the ‘Standard_D*ds’ line of instances. the ‘ds’ code in
particular indicates that the instance will have an extra scratch disk
on it (used for the fs), and that the disk will be in their premium
tier (likely a faster SSD)
‘Standard_D64ds_v4’ instances should get you about 2.4TB per OSS, so a
single node should get you the capacity you need. However, I can
envision some use cases where it would be more beneficial to have
smaller nodes in greater numbers, so you might want to fine tune this.
The Azure Lustre config below is being estimated at $4.53
How do I restore customization after the default configuration restore?
The Parallel Works default configuration release updates
depend on the changes made to the platform. You can protect
your configuration customization by backing up changes prior
to restoring the default configuration.
From the Parallel Works Platform click on the “Resources”
tab, select the chicklet, and click on the “Duplicate
resource” icon, and create a duplicate configuration.
Use the original configuration for restoring the default
configuration to bring the latest changes. Manually update
customization on the original configuration from the backup
copy.
You can drop the backup copy or hide it from appearing from
the “Compute” dashboard. Hide a resource configuration
option can be found on the “Settings” box on the Resource
definition page.
What is NOAA RDHPCS preferred container solution?
On security issues and capabilities to run the weather model
across the nodes, NOAA’s RDHPC systems chose Singularity as
a platform for users to test and run models within
Containers.
Accessing bucket from a Remote Machine or Cluster’s controller node
Obtain your project’s keys from the PW platform. The project
key can be found by navigating from the PW banner.
Click on the IDE box located on the top right of the page,
navigate to PW/project_keys/gcp/<project key file>.
Double click the project key file, and copy the json
file content.
Write the copied content into a file in
your home directory file. Example:
Write json to ~/project-key.json (or another filename)
Source the credential file in your environment.
source~/.bashrc
Test access
Once these variables are added to your host terminal
environment, you can test gsutils is authenticated by
running the command:
1. Maintain SSH authentication key under account, and use
it in all clusters.
The resource configuration has an “Access Public Key” box,
to store your SSH public key, and the key stored there is
only available in a cluster launched with that
configuration. Instead store your key under “account” ->
“Authentication” tab that automatically populates into your all clusters.
User bootstrap script**
In the resource config page, user bootstrap script pointing
to a folder in contrib fs is a good idea. This helps to
share it in a centralized location and allows other team
members to use it.
Configuration page has a 16k metadata size limitation.
Following these settings can reduce your possibility of a
cluster provisioning error.
An example Singularity Container build, job array that uses bind mounts
This example demonstrates a Singularity container build, and
a job array that uses two bind mounts (input and output
directories ) and creates an output file for each task in
the array.
Below is an example of a job script with a couple sbatch
options that should notify you when a job starts and ends
(you will want to replace the email address with your own of
course):
!/bin/bash
SBATCH-N1
SBATCH--mail-type=ALL
SBATCH--mail-user=<yournoaaemailaddress>
hostname# Optional, this will include the hostname of the# controller noder.
The emails are simple, with only a subject line that looks
something like this:
Slurm Job_id=5 Name=test.sbatch Ended, Run time 00:00:00,
COMPLETED, ExitCode 0
This email may go to your spam folder as it is not domain
validated, that is one downside.
The compute nodes can take several minutes to provision.
These nodes should automatically shut down once they’ve
reached their “Suspend Time”, which defaults to 5 minutes
but can be adjusted. If you submit additional jobs to the
idle nodes before they shut down, the scheduler should
prefer those ones (if they are sufficient for the job) and
the jobs would start a lot quicker. Below is a
list/description of the possible state codes that a slurm
node might have. Bolded the ones that you are most likely to
see while using the cluster:
*:
The node is presently not responding and will not be
allocated any new work. If the node remains non-responsive, it
will be placed in the DOWN state (except in the case of
COMPLETING, DRAINED, DRAINING, FAIL, FAILING nodes).
~:
The node is presently in a power saving mode (typically running at
reduced frequency).
#:
The node is presently being powered up or configured.
%:
The node is presently being powered down.
$:
The node is currently in a reservation with a flag value of
“maintenance”.
@:
The node is pending reboot.
You can manually start with sudoscontrolupdatenodename=<nodename>state=resume
In order to get non-exclusive scheduling to work with Slurm,
you need to reconfigure the scheduler to treat memory as a
“consumable resource”, and then divide the total amount of
available memory on the node by the number of cores.
Since Parallel Works platform doesn’t currently support
automating this, we have to do it manually, so the user
script below only works as is on the two instance types
you’re using on your clusters ( AWS p3dn.24xlarge &
g5.48xlarge). If you decide to use other instance types
the same base script could be used as a template, but the
memory configurations would have to be adjusted.
The script itself looks like this:
#!/bin/bash
# configure /mnt/shared/etc/slurm/slurm.conf to add the realmemory to every node
sudo sed -i '/NodeName=/ s/$/ RealMemory=763482/' /mnt/shared/etc/slurm/slurm.conf
sudo sed -i '/PartitionName=/ s/$/ DefMemPerCPU=15905/' /mnt/shared/etc/slurm/slurm.conf
# configure /etc/slurm/slurm.conf to set memory as a consumable resource
sudo sed -i 's/SelectTypeParameters=CR_CPU/SelectTypeParameters=CR_CPU_Memory/' /etc/slurm/slurm.conf
export HOSTNAME="$(hostname)"
if [ $HOSTNAME == mgmt* ]
then
sudo service slurmctld restart
else
sudo service slurmd restart
fi
How do I change the slurm Suspend time on an active cluster?
You can modify a cluster’s slurm suspend time from the
Resource Definition form prior to starting a cluster.
However if you want to modify the suspend time after a
cluster is started, the commands must be executed by the
owner from the controller node.
You can modify an existing slurm suspend time from the
controller node by running the following commands. In the
following example, the Suspend time is set to 3600 seconds.
In your case, you may want to set it to 60 seconds.
sudosed-i's/SuspendTime=.*/SuspendTime=3600/g'/mnt/shared/etc/slurm/slurm.conf
if[$HOSTNAME==mgmt\*]thensudoscontrolreconfigure
fi
What logs are used to research slurm or node not terminated issues?
The following four log files required to research the root
cause. Please copy the following log files from the
controller node [a.k.a head node] to the project’s permanent
storage and share the location in an OTRS help desk ticket.
In the case, also include the cloud platform name, and the
resource configuration pool name in the ticket description.
These files are owned by root. The cluster owner should
change user as root when copying the files, for example.
$sudosu-root
/var/log/slurm/slurmctld.log:
This is the Slurm control daemon log. It’s useful for scaling
and allocation issues, job-related issues, and any scheduler-related launch
and termination issues.
/var/log/slurm/slurmd.log:
This is the Slurm compute daemon log. It’s useful for
troubleshooting initialization and compute failure related issues.
/var/log/syslog:
Reports global system messages.
/var/log/messages:
Reports system operations.
How do I distribute slurm scripts on different nodes?
By default the slurm sbatch job lands on a single node. You can
distribute the scripts to run on different nodes by using the sbatch--exclusive flag. The easiest solution would probably be to submit
the job with an exclusive option, for example,
A recent modification on the cluster provisioning starts
compute and lustre clusters execution in parallel to speed
up the deployment. Previously this was a sequential step,
and took longer to provision a cluster. Since the compute
cluster comes up earlier than lustre, any user bootstrap
command to copy files to lustre will fail.
For example, this step may fail when included as part of the
user-bootstrap script:
cp-rf/contrib/User.Id/psurge_dev/lustre
You can use the following code snippet as a workaround.
LFS="/lustre"untilmount-tlustre|grep${LFS};doecho"User Bootstrap: lustre not mounted. wait..."sleep10done
cp-rf/contrib/Andrew.Penny/psurge_dev/lustre
What is the command to get max nodes count on a cluster?
Default sinfo output (including a busy node so it shows
outside of the idle list)
Error launching source instance: InvalidParameterValue: User data is
limited to 16384 bytes
Resource configuration page has a 16k metadata size
limitation. Recent feature updates on the configuration page
has reduced the free space available for user data, that
includes SSH public key stored in “Access Public Key”, and
“User Bootstrap”.
Below settings can lower the user data size, and avoid a
provisioning error due to page size limit.
Maintain SSH authentication key under the account, and as it
is shared across all your clusters.
Click on the “User” icon located at the top right of the
page, then navigate to the “account” -> “Authentication”
tab, and your SSH public keys.
Remove the SSH key from the “Access Public Key” box, and
save your configuration.
Where do I enter my public SSH key in the PW platform?
Navigate to your account, the Account -> Authentication,
then click on the “add SSH key” button to your public SSH
Keys. There is a system key “User Workspace”, which is used
by the system to connect from a user’s workspace to your
cluster.
Error “the requested VM size not available in the current region”,
when requesting a non-default compute VM/instance
Each Cloud provider offers a variety of VMs/Instances to
meet the user requirements. The Parallel Works platform’s
default configurations have VM/Instances that are tested for
the peak FV3GFS benchmark performance.
Hence, the current VM/instance quota is for these default
instance types, for example c5n.18xlarge, Standard_HC44rs
and c2-standard-60.
If your application requires a different VM/instance type,
it is advised to open a support case with the required
number of instances, so we can work with the cloud provider
for an a on-demand quota. Depending on the VM/instance type
and count, quota allocation may take a day or up to 2 weeks
depending on the cloud provider.
Bad owner or permissions on /home/User.Name/.ssh/config
This is due to wide permission set to the user container [bastion
node] .ssh folder. Use the command below to reset the permission:
chmod600~/.ssh
What is causing access denied message when trying to access a
project’s cluster?
This message appears if a user account was created after the
cluster was started. The cluster owner can check whether
that user account exists by checking in /etc/passwd file as
below.
$grep-i<user-name>/etc/passwd
Cluster owner can fix the access denied error by restarting
the cluster. When you restart the cluster, a user record
will be added in the /etc/passwd file.
Why is my API script reporting “No cluster found”?
PW made a change on storing the resource pool name
internally in order to prevent naming edge cases where
resources with underscores and without underscores were
treated as the same resource. Underscores will still show up
on the platform if you were using one before, however now
internally the pool name is stored without an underscore and
so some API responses may show different results than
previously.
As a result, any API requests that references the pool name
should now be updated to use the name without underscores.
What is causing the “Permission denied
(publickey,gssapi-keyex,gssapi-with-mic).”?
The message appears in the Resource Monitor log file is:
During a cluster launch process, an ssh tunnel is created
between the controller node and the user container. The user
container is trying to create the tunnel before the host can
accept it, so a few attempts are failed before the host is
ready to accept the request. You may ignore this message.
Also you may also notice an “x” number of failed login
attempts when log in on the controller node. This is from
the failed ssh tunnel attempts.
If the message is getting when trying to access the
controller node from an external network, check if the
public key entered in the configuration is correctly
formatted. You can verify root cause by ssh’ing to the
controller node from the PW’s IDE located at the top right
of the page. Access from IDE uses an internal public and
private key, and therefore you can narrow down the cause.
What is causing the “do not have sufficient capacity for the
requested VM size in this region.”?
You can find error message from the “Logs”, navigate to tab
“scheduler”.
The above message means there is not enough requested
resource in the Azure region. You may attempt a different
region or submit the request later.
You may manually resume the nodes like this:
$ sinfo
Set the nodename and reset the status to “idle” as given
below:
General rule of thumb will pretty much be that any Intel
based instance has HT disabled, and core counts will be
half of the vCPU count advertised for the instance.
How do I remove my project’s GCP contrib volume?**
Contrib volume is a permanent storage for custom software by
project members. In Google cloud this storage is charged on
the allocated storage, that is 2.5TB and costs about $768.00
per month. If the project does not require this storage, PI
may create a cloud help desk ticket to remove it. Only
Parallel Works Cloud administrator can remove this storage.
How do I find the project object storage,
[aka bucket or block
storage] and access keys from Parallel Works?
From the login page, click on the IDE icon located at the
top right of the page, you will see file manager with
folders.
From the File Manager, navigate under the
“storage/project_keys/<CSP>” folder to locate your project’s
object storage name and access key. The file name is your
project’s bucket name. Open the file by double clicking to
view the bucket access key information.
To access the project’s permanent object storage, copy and
paste the contents from the key file on the controller node,
then execute the CSP commands. For example:-
You may use the Globus Connect or Cloud service provider’s
command line interface to access the object storage.
Can I transfer files with external object storage [aka bucket or
block storage] from Parallel Works’s cluster?
If you have the access credentials of external AWS/Azure/GCP
object storage, you can transfer files. Use the Globus
connector or cloud provider’s command line interface for
file transfer.
Azure: How to copy a file from the controller node to the project’s
permanent storage?
Start a cluster and login into the controller node.
An example use the project cz-c4-id’s secret file.
Your project’s permanent storage file name is the same as
the secret key file name.
Copy and paste the secret key file located at PW’s file
manager storage:storage/project_keys/azure/gfdl-non-cz-c4-id
in the controller node terminal.
Copying a file to Niagara’s untrusted location is done using
a ssh key file. The firewall settings on the GFDL are not
open to allow a file copy.
How do I use GCP gsutil transfer files to a project bucket?
GCP uses the gsutil utility to transfer data into HPC
on-prem system. The “gsutil” command can run either from the
user’s local machine or the RDHPCS systems, such as Niagara.
The gsutil utility is preinstalled on clusters launched
through Parallel Works.
How do I get nvhpc NVidia HPC compiler, and netcdf, and hdf5
packages in my environment?
Parallel Works Platform is installed with Intel processors
and compilers for the FV3GFS performance benchmark test. It
also has all the on-prem libraries [/apps] to provide a
seamless on-prem experience.
The platform offers flexibility to use other processors such
as ARM, and NVIDIA GPU, and install nvhpc compilers to fit
the researchers’ specific experiments.
You can install custom software and create a modified image
[root disk] to use in your experiments. The other option is
to install on your project’s contrib volume and reference
it. Contrib is a permanent storage for your project’s custom
software management. Note that you are responsible for your
custom software stack, although we will try our best to help
you.
Various netcdf and hdf5 packages are available from the yum
repos. yum search netcdf and yum search hdf
Which AWS Availability Zones [AZ] AMD and Intel processors are
concentrated [Answer to InsufficientInstanceCapacity]
AMD
hpc6a.48xlarge:
us-east-2b
Intel
c5n.18xlarge:
us-east-1b us-east-1f us-east-2a
c6i.24xlarge:
us-east-1f
c6i.32xlarge:
us-east-2b us-east-1f us-east-2a
What does GCP resource GVNIC and Tier_1 flags represent?
Tier1 is the 100gbps network. GVNIC is a high performance
interconnect that bypasses their virtual interconnect for
better network performance.
Tier 1 bandwidth configuration is only supported on N2, N2D
EPYC Milan, C2 and C2D VMs. Tier 1 bandwidth configuration
is only compatible with VMs that are running the gVNIC
virtual network driver.
Default bandwidth ranges from 10 Gbps to 32 Gbps depending
on the machine family and VM size. Tier 1 bandwidth
increases the maximum egress bandwidth for VMs, and ranges
from 50 Gbps to 100 Gbps depending on the size of your N2,
N2D, C2 or C2D VM.
AMD64 is the name of the architecture, not the cpu platform.
Intel and AMD chips are both “amd64”. Additional reference:
https://en.m.wikipedia.org/wiki/X86-64
Data access via globus CLI tools in the cloud
This capability is similar to what has been recently made
available on NOAA HPC systems. Implementation is simply the
installation of the globus-cli tools in /apps for global
availability. Alternately, the user can install the tools
using Anaconda/Miniconda:
$condainstall-cconda-forgeglobus-cli
Globus Connect Personal
However, unlike the on-prem HPC systems, the user will need
to use Globus Connect Personal tool as well. If not already
installed, the user can install it and set up the service to
create an endpoint on that master node by downloading the
tool, untarring it, and running setup:
Container singularity replaced by singularity-ce, and syntax remains
the same
When it comes to the software package on the PW platform, it
follows on-prem guidance to provide a consistent user
experience between the environments.
The prior lineage of Singularity was forked twice.
SingularityCE and Apptainer. Singularity has not been
renamed.
Singularity container executable name is same as
singularity, community edition consistent with on-prem
usage.
S3 credentials should be set automatically in your
environment on the cluster, but these credentials are
scoped at a project level, and not to individual users.
What is the best practice in hiding credentials, when code is pushed
in Github?
Use your programming language command to call out
environment variables. For example in Python: key_value=os.environ['AWS_ACCESS_KEY_ID'].
It is very important not to commit a full print out of the
shell environment.
Where should I clone the GitHub repository?
If you want to keep the repository around between cluster
sessions, working with it from contrib would be the right
choice. If you aren’t doing anything too complex in the repo
(like editing files), or if anything compiling is fairly
small, doing everything from the controller would be fine.
Big compiles would probably be better on a compute node
since you can assign more processors to the build.
GCP Region/AZs on GPUs and models
Select a location “North America” and machine type “A2” to view
different types of GPUs available on different regions/AZs
What are the GPU models available on AWS, Azure, and GCP
AWS GPUs can be found by typing P3,P4,G3,G4,G5,or G5g
here
Azure GPUs can be found by typing Standard_NC,
Standard_ND, Standard_NV, and Standard_NG
here
GCP GPUs can be found by typing a2. Other GPUs are found to
be unavailable.
What are the Cloud regions supported by Parallel Works?
AWS:
us-east1 and us-east2. Preferred region is us-east-1
Azure:
EastUS and SouthCentralUS. Preferred region is EastUS.
GCP:
regions are us-central1, and us-east-1. Preferred region is us-central1
How to tunnel back from a compute node to the controller/head node?
A case where the users have added their keys to the account
and can login to the head node and run jobs. However, when
they start a job on compute node and then try to tunnel back
to the head node it fails.
Users on the cluster can create an ssh key on the cluster
that will allow access back to the head node from compute.
If you want to use a different key name that would work, but
you might need to configure the ssh client to look for it.
This works.
On Azure, missing /apps fs system or modules not loaded case
We are working to fix this bug. If you own the Azure cluster, please
run the command sudo/root/run_ansible. It will take about 2 mins
to complete, and will mount /apps file system.
How can I revert clusters to CentOS 7?
To load the default CentOS 7 config from the marketplace:
Go to the cluster’s configuration page:
Push the Load From Market button
Select AWS Default Intel FV3 Configuration v.1.0.0 from the dropdown menu,
and click the Restore button. Don’t forget to save your changes!
Manually Manually configure a cluster to use CentOS 7
If you have already made extensive modifications to your cluster’s definition,
you may prefer to revert the required settings by hand without loading a config
from the marketplace. There are two primary settings that need to be configured
to revert back to CentOS 7: The OS image, and the /apps disk snapshot. Keep
in mind that the OS image will need to be set on the controller and every
partition you have configured on the cluster.
Configuring the CentOS 7 OS Image
The final CentOS 7 PW image is called pw-hpc-c7-x86-64-v31-slurm on every
cloud provider. To configure the controller (login node) to use this image,
find the Image* dropdown under the Controller settings and select the
image. If you have trouble finding it in the list, you can type or copy+paste
the image name into the search bar to locate it. The examples below were taken
from an Azure definition, but the same steps can be done on AWS and GCP as
well.
Follow the same procedure on each of your compute partitions to select the
CentOS 7 image under theElasticImage* dropdown:
Configuring the /apps disk for CentOS 7
The software and modules under /apps were built specifically for their
target operating systems, so the CentOS 7 disk also needs to be selected when
using the old image. This can be done under the Controller Settings by choosing
/apps in the ImageDiskNamesettings, as shown here:
Using legacy Lustre on Azure-Like compute
clusters
Legacy Lustre configurations require setting a Lustre server image that matches
the Lustre client version included in CentOS 7 and Rocky 8 based images.
Therefore, it is recommended that your Lustre cluster runs the same base OS as
your compute cluster.
This section only applies to the legacy Lustre
implementation on Azure. AWS FSx for Lustre and Azure Managed Lustre
configurations do not need to be modified.
Migrating Lustre Filesystems to Rocky 8
If you intend to keep your compute clusters on the latest image now running
Rocky 8, we recommend that you also replace any existing CentOS 7 based
persistent Lustre resources to use Rocky 8 as well. Our suggested method to
do this involves duplicating your existing storage configuration and copying
your data to the new Lustre, either by copying directly from the old storage,
or by syncing it with a bucket. Once you have verified that all of your data
has been migrated, the old filesystem can be shutdown.
If your data is backed
up to a bucket already, you can also re-provision your existing Lustre
configuration and re-sync the data.
Note
Regarding Azure controller instances,
there is a known issue causing Rocky 8 clusters provisioned with certain
instances to fail. As a workaround, we have made the default Rocky 8 cluster
use a Standard_DS3_v2 as the controller, as this machine type is known to work.
This node type is marginally more expensive than the default controller
originally used on CentOS 7 based clusters. A future update will resolve this
issue.
What are the best practices for completing file transfers between lustre
and object storage bucket that can take hours to days?
Use screen or tmux whenever doing a big copy or software build that is
expected to take several hours. These tools allow you to create a login shell
that isn’t bound to your specific terminal or ssh session. That way you can
detach and reattach to the shell as needed.
screen is probably the easiest of the two to work with, especially if you
only need a single window. tmux gets more interesting when you want to run
multiple panes or tabs.
In either case, both of these tools take a little getting used to with the
various keyboard shortcuts to break away from the session. Here are a few
getting started tips:
You can start a single screen session simply by running ‘screen’
To detach from a session, use ctrl+a, and then d. You should see a
message like [detachedfrom80633.pts-0.mgmt-firstlast-gcp-00009]
when you detach.
You can list your screen sessions by running ‘screen -ls’ Ex:
To reattach, use screen-r. It is possible to have multiple screen
sessions at the same time. If you have multiple, you will need to provide
its pid or name when you reattach to it:
$screen-Sscreen1# create a session named 'screen1'[detachedfrom81383.screen1]
$screen-Sscreen2# create a session named 'screen 2'[detachedfrom81452.screen2]
$screen-ls
Therearescreenson:
81452.screen2(Detached)81383.screen1(Detached)2Socketsin/run/screen/S-firstlast.
$screen-rscreen1# reattach to 'screen1' session
To terminate a session, simply log out of it while you are attached. You
will get a message like [screenisterminating] when it exits.
How to create a PW cluster from JSON files?
You can certainly save a cluster definition anywhere you want as a JSON file.
To do that, go to the configuration page, click the JSON tab, and copy+paste
everything where you want it to be. That same JSON can then be copied to the
same box under a new cluster definition to configure it the same way. Note
that any attached storages are included in the JSON, so anyone copying the
definition will also need to be able to see those storage resources.
The JSON data includes everything besides the “general settings”, so anyone
using it will still need to set the “resource account” and project before
starting the cluster.
How to publish your own cluster in the Marketplace?
You are also able to publish your own cluster definitions to the marketplace
and share them with anyone else in your group, or even the entire NOAA
platform. Anyone that wants to use it would need to find it in the
marketplace first. Publishing to the marketplace is also a good way to
version control the cluster definitions anyway, so it might be good
for backing up the configuration data somewhere. You can publish resources
to the marketplace from here
