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LEE GATES: Is your high performance computing code
ready to scale, and you need to learn the best way
to schedule cloud resources and manage execution
for your workloads?
Do you need to learn cost optimizations
or minimize the runtime for your HPC workloads?
We'll go through an example of how
to use Google Cloud Batch for an application using message
passing interface.
My name is Lee Gates.
I focus on performance sensitive workloads, availability,
and efficiency by working with our product and engineering
teams in Google Cloud.
The example I'll show is how to bring a weather forecasting
MPI-based application to Google Cloud using Batch to schedule
and manage resources.
You can review this sample application
at our GitHub repository.
So the first part of building our HPC application using Batch
means we need to enable the Batch API services.
This will take just a moment.
And the second step is to load up
the Filestore that you're going to use,
and I've already done that.
So let's take a look at the Filestore in my environment.
And you can see there it's in the US west1-b zone.
And so that's the machine that we will use--
or the instance we will use for our Filestore.
And then the following step is to create our console.
So in this case, it's in the same zone as the Filestore,
and using the c2-standard-60--
and that will start up here momentarily.
There it is-- it's running.
And now, we're in our console.
So the next step that we need to do
is to mount the share that we have created for our Filestore.
So click on root, create the share location.
Let's go get our share and mount it.
And go to our share location.
And from here, we will configure the environment
by cloning in SPAC.
Create a source-- the environment--
when it's all done.
This will take a few minutes.
And now, we are ready to run our test data set.
This will take about a minute and a half.
Let's go start pulling down the larger complete data
set to prepare for our large test using Batch.
I've just logged into gcloud and have myself authenticated.
Now, I can go in and create the image--
the instance template.
And it's being created.
And so the next step we would need to do
is to prepare the file for running--
the script for running-- and put it on the Filestore instance.
That's our script that will load on each of the jobs.
And so now, what we need to do is--
we're ready to create our job file,
and we are ready to run our Batch job.
So let's do that.
So here, we can see our job has been submitted.
So our job has been scheduled.
You can see all of our parameters there,
and we'll be able to see it running soon.
So here's where we're going to wrap up our demo today.
We've shown you a Batch example of our weather forecasting
application running to completion, all the way
from setting it up to getting a successful run across four
different nodes.
For those of you interested in seeing our examples
in our repository, it's on github.comgoogle
cloudplatform/batch-samples.
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