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- Hi, I'm Karl. Have you got three minutes?
Then we've got
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Azure HPC.
Each time we talk, we want to give you a deeper knowledge,
covering technical business or even science-related aspects
of Azure high-performance computing.
For our first one, let's talk about some fundamentals.
The what, the why, and the how.
Starting with what.
For HPC, high-performance computing,
people think often about supercomputers.
Lots of machines connected together in cabinets
in a special data center,
working on a large simulation as fast as possible.
There's even a list of the 500 fastest machines
in the world.
And currently,
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January, 2023, there are four Azure systems listed.
The highest one is ranked number 14.
The 14th fastest supercomputer in the world.
And this is actually just one part
of one system in one location.
Azure has more than 64 locations
and over 100 data centers globally.
Many of which actually have this capability in them.
So you kinda get the idea. This capability is big.
And it's already available to use right now.
People are currently using these computers
to predict weather, to make safer cars,
to discover life-changing drugs,
or even to make your English-to-Spanish translations
that little bit smarter.
The next question is how.
Well,
people typically spend up to tens or hundreds
of these specialized machines
containing CPUs, GPUs, specialized InfiniBand networking
in just a few minutes into a group called HPC Cluster.
Then the simulation software, whatever it might be,
will run its calculations,
taking data in or out as it might need.
Some of these simulations are what we call tightly coupled,
meaning that all the machines need to talk together a lot
during the actual simulation.
Others are loosely coupled,
meaning that each machine works separately
on its own little piece of the overall problem.
When it's finished, everything can be saved or deleted,
and you'll only pay for what you use.
There are free Azure tools like CycleCloud or Batch,
which can make all of this easy to do.
But people can also bring their own tools,
or the interfaces for the users
don't need to be any different
from how people currently work in a system.
People running this might also not think of the term HPC.
The folks doing weather modeling, for example,
or a different science and software
like predicting financial services or risk in the markets,
or designing a new car.
They might all use different language to do that.
These things lead us to why.
Why are we doing this kind of thing?
Microsoft's mission is to empower every person,
organization on the planet to achieve more.
And with a HPC capability in the Azure Cloud,
many people are doing more simulations, larger simulations,
they're getting faster insights, quicker time to market.
They're developing new ideas.
And with a large scale supercomputing capability available
through the clouds,
this is now in the hands of everybody.
We love to see what customers do with this
and there's plenty of examples online.
So there you have it.
The what, the why, and the how of Azure HPC
in three minutes.
Next time we'll go a bit deeper,
and we'd love to hear what you think.
Bye for now!
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