(Dr Taylor) The CSIRO GPU cluster is now open for business.
(Narrator) In 2009 Dr John Taylor switched on CSIRO’s GPU Cluster.
(Dr Taylor) GPU computing really is a revolution in computing.
We’ve been able to take this new technology
that was originally developed to support computer games
and apply it across the board in science.
(Narrator) A GPU or Graphics Processing Unit,
processes data much faster
than the central processing unit or CPU
found in your home computer.
Joining many hundreds of GPUs with CPUs in one super computer
means they can churn through masses of data in very short time.
Speeding up image rendering,
scientific calculations and computational models,
hundreds of times faster than CSIRO’s scientists were used to.
(Dr Taylor) Probably the most exciting moments are when
I get a call or an email or somebody tells me that
something’s running a thousand times faster
and they’re really thrilled about it,
that’s probably the most exciting thing.
So, it’s a real sign that the technology is
very beneficial to peoples research and
that people are getting great results.
(Dr Mayo) It’s a 3D rendered view of
3D data set of a micro fossil,
which is a tiny tooth from a prehistoric animal.
The whole tooth is less than a millimetre across.
It’s a ceramic microsphere,
it’s made of silicone and it has little bubbles in it
and the whole thing’s about 100 microns across,
so that’s only about half again as thick as a human hair,
so it’s quite small.
(Narrator) CSIRO Materials Scientists are
using GPUs to create highly detailed images
from 3D data sets
collected at the Australian Synchrotron.
When electrons are fired around this Olympic stadium sized tracked,
powerful magnets force them take a circular path.
As they do they omit light
a million times brighter than the sun,
this powerful beam can be focused at any wavelength down beam lines.
X-rays, for example,
filled up a highly detailed picture of any target in their path.
But it’s a data intensive task.
Where Scientists may have waited hours for their results in the past,
the GPU cluster churns through the raw data quickly,
displaying amazing images in real time.
(Dr Mayo) It’s actually been really fun
just from a sheer visual point of view
and then we can get science from it too, of course.
(Dr Stephenson) I think the fact that we’ve got everything in one place,
so we’ve got our own synchrotron now and it’s quite close
and we’ve got ready access to a world class beam line.
And if we have world class computing facilities to use with that,
I think we can capitalise on that to a great extent
and get a lot more out of our data
and get our data much more quickly than we could in the past.
(Dr Murray) What we’re looking to do is
model large scale environmental systems.
Using the GPU cluster we can do that more accurately,
more precisely and we quantify uncertainty,
which is very important from a management perspective.
When you do have a powerful machine like this,
your productivity increases in a sense,
what might have taken a few days, might take a few hours now.
What might have taken a week,
or was completely infeasible because it was going to take a month,
well that’s out of the question in terms of
productivity and the turnaround in your work.
If we can get results in a few hours,
or overnight and be looking at them the next morning,
that really makes a difference as to how we can then say,
look at those results and make any adjustments we need to the model,
or our inputs or anything like this
and in terms of our work flow then, you know,
it really opens up some opportunities for us.
(Dr Huang) The problem that I’ve been working on the GPU
most for is to construct genetic maps in wheat.
And the issue there is that
you actually have to calculate the distance
between every position that you have on the genome
in order to construct a map
and so that actually means you’re looking at
the square of the number of positions that you have,
which is where the issues with computation come in.
But it does break up quite nicely for a GPU
because you can look at each position individually
and do it for each wheat variety.
And the idea there is really to improve the quality of wheat,
worldwide, and to do it in a faster way than has been done before.
(Dr Murray) Really, using the GPU cluster is quite interesting because it’s a
shift in the way we think about computation.
I mean, we’ve gone from this sort of sequential computation,
which is almost like following a recipe,
a sort of a cookbook recipe,
to large scale parallelism,
so doing lots of tasks at a time,
as opposed to one long task very quickly.
So people really need to rethink the algorithms that they use.
Rethink the approach that they use to their
particular computation challenges in science.
You need to be thinking about how can I divide
up the work into lots of little small things that I can do concurrently
as opposed to one sort of long recipe to follow.
(Dr Taylor) The Top 500 list it’s very important,
it provides us with some indication of how
successful we’ve been in building and exploiting computational facilities.
The fact that also that we’re very
close to the top of The Green 500 indicates that, not only,
are we achieving a very high performance,
but we’re delivering that at very low energy costs.
We’re reducing our carbon footprint,
so we’re able to deliver this fantastic capability
at very low cost and very low energy cost.
(Andy Keane) GPUs are an entirely new way of computing information.
Rather than separating that information
among hundreds of processors with very few cores,
a GPU has hundreds of computing cores inside.
So you can take that application
and divide it among all those hundreds of energy efficient cores
for very efficient processing of HPC applications.
This is why the GPU
is among the systems that are leading on The Green 500.
(Dr Taylor) The CSIRO GPU cluster is currently delivering
52.55 TFlops on the standard Linpac test in double precision,
its running at very high efficiency
and its consuming about 94.65 kilowatts
of electricity when it’s doing that.
That means that we're able to achieve about 555
mega flops per watt of energy consumed.
So that puts us very close to the top of The Green 500.
The cluster was operated from the original
Tesla S1070 to the latest generation S2050s.
We’ve seen about a five to six X improvement in performance.
So yeah, I think it’s been a fantastic
year or so and I think a lot of people have really
enjoyed the benefits of our new GPU based cluster.
(Dr Huang) It allows you to think of problems
that you wouldn’t have been able to address before.
(Dr Murray) When we first started on this,
the few of us who are now talking at these workshops,
were the only ones in the GPU cluster and we could submit jobs
and they would all run immediately, and we see now,
we submit jobs and they all go into quite a long queue
because people are actually starting to use it
and starting to realise the benefits of it.
(Dr Taylor) A year ago we didn’t really know
what the uptake was going to be within CSIRO,
now we know that it’s been quite strong and we’ve been very successful,
so I think, yeah, a year on we can see that we’re on the right track
and we can also see a track that’s leading forward
with this technology for the next few years.
[Music Plays]